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000-634 - Object Oriented Analysis and Design - Part 2 - Dump Information

Vendor Name : IBM
Exam Code : 000-634
Exam Name : Object Oriented Analysis and Design - Part 2
Questions and Answers : 72 Q & A
Updated On : October 16, 2018
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000-634 Object Oriented Analysis and Design - Part 2

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000-634 exam Dumps Source : Object Oriented Analysis and Design - Part 2

Test Code : 000-634
Test Name : Object Oriented Analysis and Design - Part 2
Vendor Name : IBM
Q&A : 72 Real Questions

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Managing to the subsequent Century - The 5 large issues For Agile Transitions | killexams.com Real Questions and Pass4sure dumps

Key Takeaways
  • a hit transformation wants robust leadership to help and offer protection to agile tradition
  • aid groups and stakeholders to self-prepare
  • manipulate your portfolio with effects (not Output)
  • Systematically get rid of sources of waste and lengthen faced by using Agile teams
  • Measure and enrich price delivered with standard feedback (check out and Adapt)
  • relocating to Agile is difficult, but necessary

    As we movement into the digital age, organizations increasingly are looking to be more agile. perhaps it is prompted via loss; lack of valued clientele, personnel, market share or brand cost. It additionally could be driven by a need to “sustain with the Joneses” and the desire to be as cool as Amazon or Netflix. Motivation now not withstanding agile transitions are standard vicinity with many companies trying to turn into “greater agile”.

    besides the fact that children, for many agencies, the adventure to becoming “more agile” is suffering from false begins, unhappy stakeholders and irritated and puzzled leaders. fitting agile is difficult, not just as a result of agility, however usually because any change is hard for groups to embark upon. to cite Niccolo Machiavelli:

    there's nothing greater complicated to absorb hand, extra perilous to behavior, or greater doubtful in its success, than to take the lead in the introduction of a new order of issues. - The Prince (1532)

    And the circulation to agile is a brand new order of things, a an awful lot extra simple alternate than the adoption of a brand new methodology or manner framework. Carlota Perez world famous economist describes the trade as usual-feel response to the digital age.

    no one nowadays would propose a centralized, inflexible, true-down organizational structure, where you can't communicate across features apart from through your bosses. although, that turned into exactly what Alfred Sloan set up at commonplace Motors, to a great potential at his time. With today’s communications and flexible applied sciences, agile inventive networks make more feel and result in a good deal greater productivity.

    Perez goes on to argue that the old age concentrated on mass creation. Which by using its very nature is distinctive from digital production. Mass product makes a speciality of reducing the unit can charge, and lengthening pleasant by using procedure optimization, conformity and standardization. Digital nonetheless, makes a speciality of the unit dimension of 1, the place every thing is pleasing when it comes to the difficulty, answer and supreme cost circulate. however how many agencies still manage their digital items with the equal mass creation paradigm with useful resource optimizations, standardized technique and specialism of labor? The agile age requires a distinct strategy to results, work, groups and administration.

    a focus on results – taking ownership of the company price

    as an alternative of a focus on getting work performed in the most cost effective, consistent, possibility hostile method, agile teams pay attention to offering price in the most constructive method. They focal point not on the work, but instead the outcomes they are attempting to bring. Scrum, the realm’s most customary agile framework, is empirical in strategy. accordingly, problems are broken down into small experiments with everyday commentary which may result in adjustments. Smaller batches of work coupled with the deserve to concentrate on value ability:

  • ownership becomes a proper precedence - In most natural organizations, decisions are made in a gradual, consensus driven method. documents are used to save the particulars and are signed off to make sure that everyone is aware of who was concerned. trade is handled as a problem with expensive management techniques, evaluation committees and escalation techniques. Agility requires decisions to be made, and work to be delivered permitting remarks and growth. That requires possession.
  • value must be certainly understood and measured, which appears like an easy requirement - The fact is that a good deal work doesn't have a clear connection to value. measurement is also very complex as businesses wrestle with visibility, transparency and ownership.
  • teams need to be aligned to shoppers – regularly groups have a negative understanding of their relationship with a customer and however they have got the benefit of knowing the consumer they neither are aligned to them or can get entry to them. purchasers are managed with the aid of the front conclusion of the enterprise, revenue, advertising and marketing and assist. Product building has to work with these agencies to get access and comments.
  • frequent knowing requires well-known remark – For digital products, that ability offering them to valued clientele for use. providing frequently has large implications on each part of the building method from how necessities are managed, to how the product is validated. How the underlying utility is architected also alterations to assist smaller extra customary adjustments. For non-digital or hybrid items the deserve to acquire conventional feedback also adjustments the way work is finished with extra of a spotlight on conventional evaluation, simulation and trying out.  
  • Work isn't owned through a supervisor

    within the new agile world, it's neither possible to tell individuals to do a selected assignment or plan at the identical level of breadth or depth. Work is defined, managed and achieved through empowered groups who don't seem to be concentrated on the task, however in its place the influence they are attempting to obtain. nice including technical debt is handled in the same way that cost is treated allowing the group and the business to make explicit, transparent decisions on trade-offs. but relocating far from natural managed work to a greater agile strategy requires more than managers stepping away however requires groups to have:

  • clarity of accountability and possession – In most contemporary corporations everybody is accountable, however no person is in charge. In an agile company, it is obvious that the crew is liable for the consequences, the company for determining where to focus the team in terms of price and the corporation liable for building the environment for the group to be a success. by having clear obligations and permitting groups to make decisions agile groups can right away reduce away loads of the waste linked to typical proper down management procedures.
  • management focused on building the appropriate atmosphere – Many managers get their position as a result of they are good at doing the work. That ends up in a way of life of “parental-ism” with managers telling individuals what to do. For standard work this may also be positive, but when work becomes advanced and procedure variable it is awfully complicated requiring the supervisor to be always there. The administration position for this reason has to trade to teaching, and servant management helping the team cope with the work and focus on the outcomes.
  • tasks replaced by means of items – for many businesses, work is performed via initiatives, and at anyone time there are heaps of projects being run. every project has funding, substances and a lot of documentation. individuals work on varied initiatives and teams are created and destroyed frequently. Agility doesn't drive an organization no longer to do projects, but does inspire a greater concentrated, crew centric method to work. by way of reducing initiatives and moving to a product or customer alignment, groups can greater center of attention on consequences. additional benefits are more convenient planning cycles, decreased complexity of verbal exchange and decreasing of the dreaded context switching difficulty. tasks will still exist for initiatives that cross varied client / product / influence boundaries, but they aren't the norm. 
  • teams are true

    at the very heart of the agile firm is a set of teams, self-prepared and empowered to make selections. they have got the entire appropriate skills to convey value and are supported by a firm that fills in any gaps and helps them to get enhanced.  At scale that means groups of groups and the adoption of practices to make certain that dependencies are quite simply managed. however in contrast to in the world of mass creation, agile groups do not advantage from “throwing loads of our bodies at a problem”, and as a substitute inspire leaner, “smarter” organizational models. businesses may wish to change their approach to teams by using:

  • concentrating on building long lived groups – teams are not a new theory for businesses, definitely for a lot of they like the theory so a whole lot they put americans on dissimilar groups. Agile companies motivate a more concentrated, people centric mannequin with teams having an identification and consistent membership. That ability that work is delivered to the crew in place of the team forms around the work. this may require a change in thinking and manner for many mission management businesses.  
  • setting apart of work management from people administration – It is terribly tough to be transparent when the adult who reviews you, determines your bonus and decides on promotions is working with you on a regular basis. by having a clear separation of labor management and individuals management on agile groups encourages transparency and openness. Work is managed by way of the group, people construction and management is either managed via some variety of group or guild, or via greater common management.
  • Incrementally evolving the architecture towards valued clientele – for a lot of organizations, individuals are aligned to purposes and people purposes are reused in many different consumer or cost contexts. That ends up in complexity with every little thing affecting every little thing. up to date, agile business architectures focus on optimizing for agility. That may additionally mean that some things are duplicated and that the full can charge of possession for a person software may be better, but eventually the cost of responding to the market outweighs that charge. Optimization moves when it comes to location within the stack as it has completed outdated with alterations to the can charge of disk area or processing.
  • range matters – To respond to complicated complications requires skilled groups with loads of diverse views and abilities. range of opinion, idea and answer are crucial for offering value. but for many agencies group boundaries re-implement departmental, device and event boundaries. For agile to work, and for corporations to carry amazing customer solutions it's critical to build distinct groups that problem the status quo, seem and suppose distinctive.
  • Introducing the 5 challenges of Agile Transition

    relocating to the “new order” isn't handy, and many organizations have begun the adventure with the adoption of Scrum, and are taking a look at scaling frameworks such as much less, safe and Nexus, and organizational models just like the Spotify. sadly, there isn't any single silver bullet for “remodeling” your firm into an agile, digital native enterprise. looking at organizational frameworks and scaling fashions are excellent tools and only one piece of the puzzle, as the move requires a greater holistic method to agility. It also can't be concept of as replacing one methodology with another, but as a substitute some thing extra basic to the way the corporation responds to the market and delivers price. groups should be aware of 5 broad challenges.

  • aid and offer protection to agile subculture with effective management
  • assist teams and stakeholders to self-organize
  • control your portfolio with outcomes (not output)
  • Systematically eradicate sources of waste and prolong faced with the aid of Agile groups
  • Measure and enrich price delivered with normal feedback (inspect and adapt)
  • aid and give protection to agile culture with amazing leadership

    The tradition of the corporation is described with the aid of the norms enacted by means of the organization in how they do every thing. management defines and re-enforces these norms in the moves and phrases. Having leaders that embody the values of agility and enhance its concepts is vital for any transition. as an example, agility requires a continual method to gaining knowledge of and understanding, but if leaders focal point on error and apportioning blame, then it is likely that any empirical technique will not work.

    assist groups and stakeholders to self-arrange

    developing an ambiance where groups self-prepare and are empowered to make decisions that convey value is the basis for agility.  unluckily, just telling teams to be empowered and self-arrange is not an easy way to introduce those ideas. as a substitute exchange needs to be brought incrementally and practices corresponding to Delegation Board from management three.0 can aid slowly circulate groups to taking the lead.  

    manipulate your portfolio with outcomes (not output)

    Agility like the rest is simply pretty much as good as the influence you are focused on. with the aid of building an agile enterprise it is focused on customer outcomes instead of work you not simplest permit stronger alignment, but you additionally power a clear imaginative and prescient and objective. typical businesses have always focused on the system, with only small constituents of the firm being linked to the client and the effects they are searching for. contemporary, agile organizations make consequences within the context of valued clientele’ wants front and core and make everybody answerable for them.

    Systematically eliminate sources of waste and prolong faced by using Agile teams

    Waste is the enemy now not of effectivity but of cost. Waste to agile groups is anything that stops them from supplying price and improving. Waste similar to hand-offs to external departments to waste in time spent in review meetings. To become more agile everything is on the “waste elimination” agenda and nothing is “set in stone”. That skill that companies corresponding to finance, audit and compliance deserve to be a part of the trade allowing them to be evaluate present methods to be able to alternate. Planning is commonly a neighborhood the place waste is current with long term planning cycles and alter management strategies taking valuable time away from key stakeholders and beginning groups. In Scrum, waste is managed during by making it transparent within the daily Scrum and alternatives for development being discussed in dash review and Retrospective. but outside of any selected framework agile teams analyze every thing with an eye to study and increase. They even have the courage to problem the popularity quo.

    Measure and enhance price delivered with common feedback (inspect and Adapt)

    if you had been going to measure one aspect to assess if an business is agile it will be how frequently they get their customers, stakeholders and teams to evaluation the delivered objects. Getting true information on the use on what you've got delivered, coupled with a desire to create the simplest thing to get feedback are cornerstones to agility. noted agile firm client centric organization Amazon famously grants utility every 11.6 seconds. no longer since it wishes so as to add extra elements, however because it wants to try new ideas with its valued clientele and get feedback.


    It seems ironic, but many groups consider of a move to agile as a hill to be climbed the usage of average tactics. build a plan, discover the substances after which execute. but becoming an agile commercial enterprise is much greater than adopting a selected manner framework or changing job titles. it's a fundamental change to the way through which you respond to the market. Organizational models, techniques, equipment and even the underlying items will exchange generally in response the wants of the customer, market and stakeholders. An agile commercial enterprise is at its heart a client-centric discovering organization. Peter Senge in his publication the 5 discipline, The artwork and follow of a studying firm describes the want for a firm to fitting concentrated on getting to know.

    “The most effective sustainable aggressive advantage is a company's capacity to study quicker than the competition”.

    eventually, via focusing on the 5 challenges of agile leadership, self-organization, fitting client outcome centric, waste adverse and regularly delivering discovering the lifestyle of the company, organizations will become more focused on getting to know and may develop into more agile.  

    in regards to the author

    Dave West is the Product proprietor and CEO at Scrum.org. he's a widely wide-spread keynote at primary industry conferences and is a extensively published creator of articles and research reports. He also is the co-author of two books, The Nexus Framework For Scaling Scrum and Head First Object-Oriented evaluation and Design. He led the development of the Rational Unified process (RUP) for IBM/Rational. After IBM/Rational, West returned to consulting and managed Ivar Jacobson Consulting for North the usa. Then as VP, research director Forrester analysis, he ran the application construction and birth practice. prior to becoming a member of Scrum.org he became Chief Product Officer at Tasktop the place he was chargeable for product administration, engineering and architecture. As a member of the business’s government administration team become additionally instrumental in turning out to be Tasktop from a capabilities business right into a VC backed product business with a group of essentially a hundred.

    Cloud buoys statistics microservices -- for on-premises programs, too | killexams.com Real Questions and Pass4sure dumps

    It is not too startling to be trained that cloud architectures are coming to information facilities. despite the fact that they're stuck on a firm's premises, contemporary enterprise architects need to get in on the motion as information microservices evolve.

    The cloud architectures they're bringing all the way down to earth come mostly by the use of containers that are in keeping with a microservices strategy corresponding to ancient-time SOA -- which stands for provider-oriented architecture, not Sons of Anarchy, the outlaw biker membership from the television display of the same identify. records microservices are like SOA, most effective extra micro.

    improving huge information support for containers was one of the engineering to-do listing gadgets cited by Hadoop providers Cloudera and Hortonworks once they introduced plans to merge this month. That and a circulation to wider use of cloud object storage characterize a huge shift coming to massive records.

    Kubernetes orchestration

    while containers were born as stateless vessels, work is underway to make them more stateful, with help for persistence of facts in applications. If a hit, this might simplify using distinct for-intention analytics engines and frameworks -- think Hive, Presto, Druid, TensorFlow and so on.

    Used in conjunction with the increasingly common Kubernetes container orchestration technology, information microservices will quickly emerge as an choice fashion of facts processing, even if on the cloud or off.

    or not it's early, and there's a lot of gaining knowledge of to do, as evidenced through Kubernetes sessions that were commonly full at last month's Strata data conference in ny. After researching comes building, plenty of which is crucial before the brand new architecture can take root.

    Enter Cloud deepest for data

    For IBM and its clients, finding a stability between on-premises and cloud information architectures is an ongoing quest. The business's full of life embody of both Hadoop and Spark has been stated earlier than, but IBM remains working to neatly equipment these and other huge facts mainstays for cloud and on-premises deployments.

    close the conclusion of the Strata convention, we spoke with Rob Thomas, widespread manager of IBM Analytics, as he prepared for a panel discussion on the enterprise's IBM Cloud inner most for information platform and the function it might play in bringing AI to fruition. The Cloud deepest for statistics equipment comprises Db2, Db2 Warehouse and Db2 event shop, and it supports numerous interfaces for facts scientists and other predictive analytics clients, each on and off the cloud.

    "in case you developed a model on inner most cloud, that you can install it on public cloud. Or, in case you constructed it on public cloud, you could install it on deepest cloud," Thomas noted. The facts practise and governance equipment are the equal no matter if the deployment is public or private, he delivered.

    Thomas pointed out the business recently followed via on plans to add support for MongoDB, EnterpriseDB's EDB Postgres and IBM information chance supervisor to IBM Cloud deepest for statistics, and it's working to certify the platform to work with crimson Hat's OpenShift container application expertise.

    Chart showing differences between monolithic and microservices Monolithic vs. microservices

    IBM's traditional data-aspect rivals are additionally looking to join records analytics on premises with data analytics in the cloud. Oracle's efforts middle on its Oracle Cloud at consumer engaging in. And Microsoft lately previewed a edition of SQL Server 2019 that may deliver the Azure types of Spark and Hadoop down into the statistics core.

    IBM has giant cloud building and records alliances with pink Hat and Hortonworks, both of which contact on information microservices. each organizations mixed with IBM simply before Strata to launch an Open Hybrid architecture Initiative. The venture's purpose is to meld Kubernetes, containers and Hadoop workloads, and there is a good deal work to be achieved in that regard, Thomas pointed out.

    Remaking the monolithic

    After Strata, we checked in with Tom Phelan, co-founder and chief architect at BlueData application, maker of the utility platform BlueData Epic, which is short for Elastic inner most speedy Clusters. He mentioned he favored the dreams of the Open Hybrid structure Initiative, however introduced that there have to be greater work earlier than it could possibly circulation ahead.

    "a large challenge is that, when Hadoop became written, it became written as a monolithic architecture," Phelan referred to.

    it really is the case even if Hadoop can be broken down into services such because the name node, the YARN aid manager, Hive, Hadoop dispensed File equipment functions and so on.

    When Hadoop was written, it became written as a monolithic architecture. Tom Phelanchief architect, BlueData

    "None of those are microservice-architected," Phelan noted. "those capabilities should be started in a undeniable order. They ought to interact with each different service in a really particular manner. there is, for example, no strategy to restart a kind of capabilities and never have it impact other services which are running."

    For its half, BlueData this month released KubeDirector, an open supply venture for establishing stateful application clusters on Kubernetes.

    New scheme coming?

    even if records moves to the cloud or no longer, the affect of cloud architecture looms as vast.

    "businesses absolutely have lots of on-premises data going into the cloud, but now not all the records is going to the cloud," observed Forrester analyst Noel Yuhanna. "every now and then, when the cloud invoice comes in, it may be massive -- probably greater than on premises."

    strikes such because the Open Hybrid architecture Initiative handle the deserve to harmonize views within the two domains, in response to Yuhanna, and set the stage for ordinary administration policies for each.

    "You desire an architecture that may control both cloud and on-premises facts with standard guidelines," he brought.

    returned when SOA walked the earth, it brought about a remodeling -- or rewrapping -- of legacy techniques. New statistics microservices might make current huge statistics techniques similar to legacy techniques. that could be nothing more than growth.

    it's a superb wager that, as hybrid data processing becomes extra real, records can be shuttling from right here to there and returned. And, of course, YANA -- Yet one other New structure -- could be waiting in the wings.

    right here's IBM's Blueprint for successful the AI Race | killexams.com Real Questions and Pass4sure dumps

    one of the most cornerstones of international enterprise Machines' (NYSE: IBM) ongoing transformation is cognitive computing, which encompasses artificial intelligence and different connected technologies. IBM is a company that serves different organizations, and its approach to AI stays true to its purpose. IBM Watson, the business's familiar AI device, is getting used in industries like healthcare and monetary functions to increase the abilities of gurus in those fields. The lengthy-term competencies of the technology is huge.

    IBM has made of venture that cognitive computing may be a large a part of its future. here's how the business came, and the way it plans to win.

    The IBM Watson brand. image source: IBM.

    IBM is a infrequent instance of a tech business that has been able to adapt and evolve, closing central via many decades and technological eras. considering that its founding in 1911 because the Computing-Tabulating-Recording company, IBM has gone through multiple, sometimes painful, transformations that proven the enterprise's unravel.

    In its early days, IBM sold and leased mechanical tabulating machines, as well as typewriters and different instruments. The enterprise's first foremost transformation got here on the break of day of the desktop age. IBM introduced its first tremendous laptop in line with vacuum tubes in 1952. computers in accordance with transistors got here later that decade, marking the birth of IBM's mainframe enterprise. IBM went on to dominate the very own computer market as smartly, at least for a long time. The company's mechanical tabulating computer business changed into a cash cow, but IBM wasn't afraid to disrupt itself when it grew to be clear that computer systems have been the future.

    IBM's 2nd fundamental transformation came within the Nineteen Nineties. After decades of success, complacency led the enterprise to nearly implode because the core mainframe enterprise struggled and the pc enterprise grew to become more and more commoditized. IBM had become bloated, and it overpassed where the business turned into going. An outsider CEO was brought in, saving the enterprise by means of slashing costs and making a bet on services. IBM became an integrated provider of solutions spanning hardware, application, and functions, a mannequin that then drove its growth for the better a part of two a long time.

    That brings us to IBM's present transformation. over the last 5 years or so, IBM has undergone yet another reinvention, this time making a bet on cloud and cognitive computing to gasoline its company in the years to return. Legacy corporations had been offered off or de-emphasised, while supplies had been poured into growth areas like artificial intelligence. The business has built a cloud computing business with just about $20 billion of annual revenue, and its Watson AI equipment has been utilized to a wide variety of industries and applications.

    Watson is the face of IBM's effort to cement its reputation as a frontrunner within the fast-growing to be AI market.

    the realm turned into delivered to Watson in 2011 when IBM put the AI system up towards two champions on the online game show Jeopardy! Watson cleaned residence with an miraculous but imperfect performance, in a position to parse the clues and provide suitable responses regularly enough to win the video game and symbolize an immense AI leap forward.

    at the time, Watson turned into powered by using 750 of IBM's vigor servers, that includes a total of 16 terabytes of reminiscence and 2,880 POWER7 CPU cores. today, Watson-based mostly capabilities are available by the use of IBM's cloud, requiring a long way fewer components than the preliminary version. with the aid of 2013, IBM had managed to virtually triple efficiency whereas reducing hardware necessities to a single power server.

    One crucial element to grasp: Watson is not a one-dimension-fits-all system. The fashioned Watson device used on Jeopardy! turned into informed notably for that intention. a special software requires practising with distinct facts. as an instance, IBM presents a visual-awareness cloud provider powered with the aid of Watson; this version of Watson is educated with pictures tagged with the objects they comprise, and the influence is a system that can establish objects in different pictures. that you would be able to view Watson as a collection of AI technologies that can be utilized to different tasks, as opposed to a monolithic AI device.

    a whole lot greater than computing device gaining knowledge of

    The term synthetic intelligence is frequently used interchangeably with two other phrases, desktop researching and deep getting to know. but it is now not rather correct. computing device gaining knowledge of is a set of algorithms that enrich via journey. A computing device-researching equipment that identifies objects in images, as an instance, gets better because it's trained on extra statistics.

    Deep discovering is a subset of machine learning, featuring a framework that may lead to more desirable effects compared to different algorithms. an artificial neural network is one classification of deep-learning architecture, based mostly roughly on how the human mind works. many of the advances in AI we've got considered over the past few years, like self-riding automobiles, have been enabled via advances in deep gaining knowledge of.

    artificial intelligence is much broader, encompassing any algorithm that can mimic the cognitive abilities of humans. This comprises herbal-language processing, planning, belief of the atmosphere, and machine and deep discovering algorithms.

    a large choice of AI applied sciences sit under the Watson umbrella, together with laptop getting to know, deep researching, voice recognition, sentiment analysis, and natural-language processing, to identify a couple of. The original edition of Watson was a query-answering equipment. these days, Watson offers a broader set of capabilities, and is able to ingest large quantities of structured and unstructured facts.

    IBM's AI method

    IBM isn't a purchaser-dealing with enterprise, so you might not be seeing any contraptions coming from IBM powered with the aid of Watson. as a substitute, IBM's focal point is on proposing solutions to its commercial enterprise consumers. The company's 2017 annual file says:

    IBM Watson's enterprise-electricity artificial intelligence is remodeling the manner individuals work in pretty much each business. It helps businesses derive perception from complicated and unstructured information. And it enables specialists to scale their talents and center of attention their efforts on better-cost work.

    whereas different enormous know-how groups are aiming their AI efforts at wise audio system and self-using cars, IBM is working to give AI solutions to the wide selection of industries and agencies that it serves. IBM counts as valued clientele 97% of the world's biggest banks, eighty% of international marketers, and 83% of the realm's largest communications provider suppliers. As companies of every stripe seem to be to put money into AI, IBM desires to be the first and best option for commercial enterprise businesses.

    IBM sees AI as a way to increase human intelligence, not change it. In areas like healthcare and monetary services, where Watson has been deployed for numerous purposes, the system acts as a device for professionals, allowing them to do their job stronger.

    Thomas Watson, Jr. changed into CEO of IBM from 1956 to 1971, all through the duration when the company guess on computers. one among his fees sums up IBM's view of AI: "Our machines should be nothing more than tools for extending the powers of the human beings who use them."

    a technique IBM makes an attempt to differentiate its AI offerings from the competitors is records ownership. IBM desires to be the most trusted name in AI. as it talked about in the 2017 annual file:

    We also accept as true with that statistics and the insights it generates belong to their creators. no person may still need to quit ownership or manage of their facts to advantage from AI and cloud computing. we have constructed and are deploying Watson for that reason.

    right here's IBM's AI method, summed up in three aspects:

  • focal point on serving enterprise purchasers.
  • follow AI to areas the place it may augment human intelligence, expanding efficiency or lowering expenses.
  • provide customers control and ownership of their facts and insights.
  • AI is still an early-innings know-how, however IBM has already put it to work in a wide variety of industries.


    total healthcare spending in the u.s. reached $3.5 trillion in 2017, and the U.S. centers for Medicare and Medicaid features tasks spending to attain $5.7 trillion by way of 2026. If there was ever an trade that could improvement from multiplied efficiencies and reduce expenses enabled by means of AI, healthcare is it.

    IBM views Watson fitness, a company unit geared toward applying Watson AI expertise to the healthcare business, as the business's "moonshot." it's an bold conducting that might be slow to generate lots within the approach of gains, however has virtually limitless talents. Watson fitness presently touches well over one hundred,000 patients and patrons, and that number could rise exponentially within the coming years as AI makes extra inroads within the healthcare trade.

    View photographs

    a doctor using a pill computing device, with a patient within the history


    a doctor the usage of IBM Watson for Oncology on a tablet desktop. graphic source: IBM.

    What exactly is Watson up to in healthcare? lots, because it turns out. listed here are a number of examples of how Watson is altering the healthcare trade:

  • IBM Watson Care supervisor is used to create individualized care plans and recommend best tactics; it processes significant quantities of structured and unstructured records, together with proof-based research, first-class requirements, and regulatory necessities. Roughly 20% of patients eat 80% of complete healthcare charges, in response to IBM Watson health general manager Deborah DiSanzo. Deploying Watson for these patients can lessen prices while producing more desirable outcomes.

    round 147,000 sufferers now have their care plans managed with the information of IBM Watson Care supervisor, with the AI equipment proving to be most advantageous for behavioral health and social care management.

  • IBM Watson for Drug Discovery is geared toward accelerating the procedure of bringing new medication to market, which takes ten years on ordinary for biotech and pharmaceutical agencies. IBM announced a collaboration with Pfizer in late 2016 to use Watson for Drug Discovery to determine new drug objectives, mixture cures for examine, and patient alternative suggestions in immuno-oncology.

    In another partnership, IBM and Barrow Neurological Institute tapped Watson for Drug Discovery to explore unidentified genes and proteins that may well be linked to amyotrophic lateral sclerosis. The look at discovered 5 genes linked to ALS that had never been linked earlier than, and did so inside a few months; it will have taken years with out Watson, stated Barrow scientists.

  • IBM Watson for Oncology is used to deliver individualized, facts-based melanoma care for patients in line with tens of millions of facts facets, with the purpose of improving the consistency and pleasant of cancer care. Watson acts as a device for medical doctors, one it is capable of believe an enormous quantity of facts and advice and make ideas for treatment. The equipment has been deployed in 155 hospitals and healthcare businesses, and or not it's been knowledgeable on lots of melanoma varieties.

  • IBM Watson for medical Trial Matching aims to in the reduction of the time it takes for clinicians to find scientific trial alternatives for sufferers, by way of doing away with the need to manually compare enrollment standards with patient clinical information. The AI equipment reduced prescreening wait times by way of 78% throughout a 16-week trial length, and it instantly eliminated ninety four% of sufferers who have been ineligible for clinical trials, in response to DiSanzo.

  • Watson fitness, and AI in generic, aren't silver bullets for the healthcare trade. Watson won't be replacing docs. in its place, Watson health is a collection of tools for healthcare gurus that could make methods extra efficient, lower charges, and doubtlessly improve patient outcomes.

    IBM made a protracted-term wager when it thrust Watson into the healthcare business. Watson health possible isn't contributing lots to the company's monetary outcomes right now. however that may change within the coming years and many years.

    economic capabilities

    IBM introduced the acquisition of Promontory monetary neighborhood in late 2016, having a bet that Watson can be helpful churning through the mountain of laws concerning the economic services business. Promontory is a world chance management and regulatory compliance consulting company that employed 600 experts on the time of the acquisition. The plan changed into to have Promontory's highly knowledgeable professionals educate Watson on regulatory counsel, ultimately the usage of the AI system in real-world functions.

    Regulatory compliance for the fiscal functions business is a near-ultimate application for AI. The amount of information is monstrous. more than 20,000 new regulatory requirements have been created in 2015 by myself, and IBM projects that the overall catalog of laws will surpass 300 million pages with the aid of 2020. greater than 10% of operational spending at major banks is related to rules and compliance, totaling $270 billion yearly, in response to IBM. Watson doesn't deserve to circulate mountains to have a huge have an effect on: Even shaving off just a few percentage features of the can charge would add up to billions of dollars in mark downs for economic organisations.

    Watson is additionally getting used in tax training. H&R; Block started the usage of Watson remaining tax season to help its tax gurus make sure that customers receive every possible tax deduction. The U.S. federal tax code contained 74,000 pages as of early 2017, and thousands of adjustments are made each year. The tax reform bill handed in late 2017 handiest makes issues greater complex.

    huge quantities of records and inefficient procedures make financial capabilities a tailor-made industry for IBM Watson.

    other applications

    past healthcare and economic services, IBM Watson is being used for a large choice of alternative applications. The number of corporations the usage of Watson grew by using more than 70% in 2017, and that boom should continue as the adoption of AI expands.

    IBM Watson is getting used:

  • by means of pipeline engineers to anticipate and stop pipeline failures: Watson is in a position to predicting screw ups up to 6 days in develop, a 24-fold growth.
  • by accepted Motors for its OnStar Go system: This Watson-powered system will learn drivers' preferences and carry individualized region-primarily based interactions.
  • by way of lawyers to sift via greater than one million criminal documents per 2d and locate critical assistance for instances: New associates spend one-third of their time laws, prior cases, and felony journals, in response to a study stated by using IBM.
  • by using place of work messaging enterprise Slack to energy its client-provider bot. Watson functions are additionally attainable to developers constructing bots and different tools for the platform.
  • by using groups seeking to construct business-specific, branded, and customized virtual assistants: IBM announced Watson Assistant earlier this year, powered via a number of cloud-primarily based APIs. organizations that construct functions based on Watson Assistant own and control the statistics.
  • For streamlining consumer support: for instance, IBM gained a $24 million contract from new york city in 2017 to overtake its 311 equipment with a brand new system powered by way of Watson.
  • These are only a number of of the use instances for IBM's AI technology. IBM CEO Ginni Rometty spoke of in 2016 that the enterprise expects the number of consumers touched via Watson, either without delay or ultimately, to attain greater than 1 billion by way of the end of 2017. regardless of that number, IBM continues to be originally of its AI event.

    A silver thread

    IBM does not reveal how a whole lot income Watson generates, so it's difficult to estimate the economic affect. back in 2013, Rometty reportedly set an formidable goal for Watson: $10 billion of salary within ten years, with $1 billion of income by 2018. even if IBM is not off course is unclear.

    One reason IBM doesn't reveal Watson-connected earnings is that Watson is worried in so many of IBM's products and functions. Executives have described Watson during the past as a "silver thread" that runs through IBM, that means that it touches a lot of different areas. Attributing profits to Watson, when it be the products and features that combine Watson generating that earnings, might also now not make all that a lot feel. nevertheless, for the reason that Watson is the face of IBM's transformation, the shortcoming of disclosure suggests that the business may additionally have fallen in the back of on attaining its intention.

    as a result of Watson is an AI gadget, using machine discovering and different applied sciences that require wide training with records, it could take a very long time for the gadget to be valuable for a particular utility. you'll expect earnings technology to be very gradual or nonexistent in the beginning, then enhance abruptly if the equipment proves ready. notwithstanding Watson is rarely producing all that much profits nowadays, revenue might upward push right away as the technology is adopted.

    The most advantageous probability of our time

    during her speech on the suppose 2018 conference, Rometty discussed how vital AI technology might be:

    it is a moment that happens every 25 years. or not it's whatever that happens when enterprise and expertise architectures are changing at the same time. It has the capabilities to trade every little thing.

    She added: "AI is the highest quality opportunity of our time."

    The competencies for AI to trade and disrupt industries is incalculable. Inefficient methods can also be streamlined, and charges may also be cut. company-new enterprise models enabled through AI methods can emerge. within the same way that the cyber web and the proliferation of mobile devices generated geysers of innovation, so too will AI.

    IBM desires to be the AI enterprise for huge enterprises. The business's enormous base of present valued clientele, all based on IBM know-how, offers it a significant aggressive expertise. And its insistence that data and insights belong to the customer differentiates it from the competitors.

    or not it's difficult to pick winners and losers in AI, since the story of the technology will play out over many years. but IBM is well-positioned to reap the benefits of the AI revolution.

    extra From The Motley idiot

    Timothy eco-friendly owns shares of popular Motors and IBM. The Motley fool has no position in any of the shares outlined. The Motley idiot has a disclosure policy.

    000-634 Object Oriented Analysis and Design - Part 2

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    Object Oriented Analysis and Design - Part 2

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    Object-Oriented Analysis and Design (Part 1) | killexams.com real questions and Pass4sure dumps

    Who does this thing? Does it have any benefit? If I do this, will my boss think that I am wasting my time or making excuses to not work? Have these thoughts ever come to your mind when you were desperate to properly design your next software?

    It is also possible that you have tried designing some piece of software before, but you found that it was too just time-consuming and it had no benefits. But throughout your career, you might have had these recurring thoughts that you should learn more about design patterns, mastering MVC, and designing something reusable, modular, and easy to read.

    In this multi-part article series, I will cover the basics about how you can properly design your next software even if you have failed last time.

    What Will You Learn?
  • Why your last design attempt failed
  • How to handle your manager/boss when you wanted to design
  • How to succeed in designing
  • The software development process
  • What is object-oriented analysis?
  • What is object-oriented design?
  • What are design patterns?
  • And anything in between that is confusing you
  • What Will You Not Learn?
  • You will not learn the syntax of Java, C#, or C++
  • You will not learn the difference between functions and variables
  • You will not be overwhelmed with a list of design patterns
  • You will not learn object-oriented programming here
  • "What?" you might say after reading the last line. "No object oriented programming? Then why am I wasting my time here?" This post is about object-oriented design, but not programming. We all know about object-oriented programming, i.e., how to write a class in C#.

    As one quote says, “Knowing how to hold a hammer does not make you an architect.” True? Similarly, learning Java programming will not make you a good software engineer (or software programmer or developer or software architect).


    During the initial years of my undergraduate programs, I thought designing was the same as writing an algorithm because I did not study object-oriented programming. Later, when I learned about object-oriented programming, I thought someone could conquer the world if they just learned everything that is there in 1,000 pages of a Deitel and Deitel book.

    object oriented programming book

    But that was not the case. I could not write a program without tearing my hair apart. I also noticed that if I opened my program again after six months, it looked like such a mystery that even Sherlock Holmes could not solve it.

    Then, in my fourth semester, I learned about object-oriented analysis and design as a subject. But unfortunately, the focus was on UML modeling. I thought that UML was a cool thing — you just generate some diagrams and hand them over to developers and they will come up with code using your designs (which will make you proud).

    But there was even an option in the UML modeling tool that our class was using at that time to automatically generate the code from your UML class diagrams. What a beauty, I thought. I could design using UML models and then generate the code, compile it, ship it to a customer, and get rich like Bill Gates. Awesome.


    Afterward, reality set in. I was never able to generate designs that were modular, easy to extend, and easy to understand (The code generated from these tools was never compiled, since it only generated stubs). Then, a period of chaos began.

    Later in my undergraduate study, I learned subjects related to software engineering, software architecture, software process models and software project management. But I was unable to fit all things together until very late.

    Still, I see people struggling with these concepts, unable to fit things together. They are overwhelmed with the unstructured data available to them. One key to comprehending all this information is to involve yourself in a project. The only output for that project should be a software that your users can use.

    In this post, I will share some basic object-oriented analysis and design principles, practices, and some of my experiences that you can use in your next project.

    Introduction to Software Development Process Models

    We all use some process or steps to develop software. The simplest process model that I use is just writing 6 lines on the back of a piece of paper and call them feature list. Then, I open Visual Studio and start writing code. That's it. It's a process model I used during my college years.

    I wrote my first commercial software (which had 1 user, who abandoned it later) using Visual Basic 6.0 in my second year of college using this process model.

    There are many software development process models that I have studied and applied throughout many projects.

    One process model (which is scolded by many authorities) is waterfall, which uses the process of gathering requirements, analysis, design, implementation, and testing.

    The problem with the waterfall process model is that you do all the things in the same exact sequence as written above. First, all the requirements are collected from the customers. A team analyzes requirements, then documents and prepares specifications for the design team. The design team then develops the design using the specification and hands over the design to the implementation team. The implementation team writes code with respect to the design. Finally, test team tests the software against the specifications.

    software process model

    Everything is done sequentially, and a lot of time is spent (months and even years) before the final product is shipped to the customer. Statistics tell us that when a product is shipped to the customer using waterfall process models, a huge number of customers rejected it = because it did not meet their requirements.

    You may have heard the phrase, “The customer is always right.” This truly applies to software development. If the customer does not like the final product, then all the effort (months and years) is wasted.

    To cater to this problem, there is another philosophy — iterative and evolutionary development. Based on this philosophy, there are many software development process models. Some examples are Scrum, extreme programming(XP), and Rational Unified Process. They are the Agile development processes.

    The concept of iterative development is simple. Software development is organized into a series of small projects called iterations. Each iteration has its analysis, design, implementation, and testing. At the end of each iteration, the customer input is taken. If a customer did not agree, then the loss is minimal (usually weeks) as compared to waterfall process model.

    Now you understand the basic difference between iterative and sequential process models. Many organizations now use iterative development process models, as the idea is to minimize waste (months vs. weeks).

    Why I Need to Understand Process Models

    For a long time, I believed that designing software was something like that: I design everything in the beginning and then, using this design, start coding. Then, once it compiles, I handed over the running software to the end user.

    It turns out that this is not the best approach. You will have to change your design strategy, which evolves over time. Therefore, the incremental and evolutionary process model is important to understand. Flawless design is a myth. After subsequent iterations, one may realize that his or her initial design sucks.

    Another point is that one should not design for all the requirements at the beginning. Make a detailed design map for the iteration you're currently working on.

    Therefore, the key takeaway is that you should use an iterative development process where the complete design is not done at the start of the project. Similarly, whatever you design will not perfect and will be changed or evolved during the lifecycle of the project.

    This ends the first article of this four-part series. In this article, I discussed the importance of process models in object-oriented design. I also mentioned the common misconception attached to UML.

    In part 2, you will learn the following

  • Difference between process and methodology

  • 2 most important object-oriented design principles that everyone should know

  • 1 advantage of OOP that every developer would love to have in his or her code

  • To learn more about object oriented programming visit here.

    Object-Oriented Analysis And Design — Design Principles (Part 6) | killexams.com real questions and Pass4sure dumps

    Design Principles

    Programming is full of rules. When you learn a language, you spend a lot of time memorizing what can and can’t be done with that language, from syntax rules, keywords, and sometimes things like memory management.

    But in anyway, the situation is easy. If you do these things, you’ll have an obvious problem, your code won’t compile or your program will crash.

    With object oriented design, it’s not that straightforward.

  • If you have a situation where you could use inheritance and you don’t and instead create several classes that duplicate 90% of each other, the program won’t crash, there will be no error messages.
  • If you make every member of every class public and violate encapsulation having every object reach directly into every other object, again, the program will compile, and it will run.
  • If you combined every single concept in your application into one massive class that acted like a completely procedural program, well, you could do that and no alarm bells would ring.
  • But none of these would be good, and you’d be creating code that’s hard to read, code that breaks easily, that’s much harder to maintain, and you’ll hate adding a new feature or doing basic bug fixing, because you’ll have fragile software, and that one small modification could break the entire system.

    So, good object orientation practices do not automatically get imposed, it’s up to us. We might not have enforced rules, but we do have guidelines, and we have principles that we can use.

    They are general principles, things to stay aware of, and occasionally check back with as you create and iterate through your class design and building your software.

    These principles aren’t as generic as just the concepts of abstraction, polymorphism, inheritance, and encapsulation. They use those ideas as a starting point and give you some more guidelines to have a better design.

    Now, we’re going to discuss some popular object-oriented design principles.


    It’s stands for “Keep It Simple, Stupid”. You may notice that developers at the beginning of their journey tries to implement complicated, ambiguous design.

    What this principles states that “most systems work best if they are kept simple rather than making them complex; therefore simplicity should be a key goal in design and unnecessary complexity should be avoided”.

    If you tried to keep it simple as much as you can, you definitely will end up having a system that’s easier to maintain and debug, easier to test, easier to be documented, and negotiate if there is a problem.

    This is really important, because imagine yourself after some days, or some weeks, you figured out a problem, and you or one of your team is assigned to solve this problem. Now, Can you identify the problem and understand your code and know what it’s actually trying to do?.


    “Don’t Repeat Yourself”. Try to avoid any duplicates, instead you put them into a single part of the system, or a method.

    Imagine that you have copied and pasted blocks of code in different parts in your system. What if you changed any of them?, You will need to change and check the logic of every part that has the same block of code.

    Definitely you don’t want to do that. This is an extra cost that you don’t need to pay for, all what you need to is to have a single source of truth in your design, code, documentation, and even in the database schema.


    “You Ain’t Gonna Need It”. If you run into a situation where you are asking yourself, “What about adding extra (feature, code, …etc.) ?”, you probably need to re-think about it.

    Because you implement only what’s needed, even if you are sure that you’ll need it in the future. You implement only what’s needed at this moment, under the current requirements.

    This is a waste of time and efforts, who knows, maybe these features that you think you will need it, it will be changed then, or not needed at all.

    Adding extra features, means adding more code to write, to maintain, to test and debug.

    SOLID S — ingle Responsibility Principle

    An object should have one and only one responsibility.

    You don’t need to have an object that does different or many tasks. An object can have many behaviors and methods, but all of them are relevant to it’s single responsibility.

    So, whenever there is a change that needs to happen, there will be only one class to be modified, this class has one primary responsibility.

    O — pen/Closed Principle

    Software entities (classes, modules, functions, etc.) should be open for extension, but closed for modification.

    Whenever you need to add additional behaviors, or methods, you don’t have to modify the existing one, instead, you start writing new methods.

    Because, What if you changed a behavior of an object, where some other parts of the system depends on it?. So, you need to change also every single part in the software that has a dependency with that object, and check the logic, and do some extra testing.

    L — iskov Substitution Principle

    A super class can be replaced by any of it’s inheriting sub classes at any parts of the system without any change in the code.

    It means that the sub classes should extend the functionality of the super class without overriding it.

    That’s why we’ve mentioned ealier in Class Diagram that it’s not a good case practice to override the methods of the super class in inheritance.

    I — nterface Segregation Principle

    Interfaces should be specific rather than doing many and different things.

    That’s because any implementing class will only implement the specific needed interfaces rather than being forced to implement methods that it doesn’t need it.

    So, large interfaces should be decomposed into smaller, more specific ones.

    D — ependency Inversion Principle

    Try to minimize the dependency between objects by using abstraction.

    If for example you have a App class that depends on very specialized classes; Database and Mail (dependencies).

    Instead, we could have App object that deals with Service class, which is more abstract, rather than something very specific. So, now the App class is not dependent on the concrete classes, but on abstraction.

    And the benefit of that is we are able to replace and extend the functionality of Service class without changing the App class at all.

    Perhaps we can replace the Database and Mail classes, or add additional classes like Logger and Auth as well.

    A common design pattern that applies this principle is called Dependency injection. We’re going to discuss design patterns in a more detail in the next tutorial.


    General Responsibility Assignment Software Patterns (GRASP) is another set of design principles.

    The principles here take a slightly different perspective than the principles in SOLID, although there is certainly some crossover.

    GRASP tends to take a responsibility focus, like who creates this object, who is in charge of how these objects talk to each other, who takes care of passing all messages received from a user interface?, etc.

    Now SOLID and GRASP don’t conflict with each other, they are not competing sets, you might choose to use one or both or neither.

    Information Expert

    When you assign a responsibility in form of a method, or fields, you assign it to the object that has the most information about it.

    Imagine that you have a class called customer and order.

    The customer tries to know all the orders placed by him, a common mistake is to assign this responsibility to the customer class, since the customer who will trigger this method.

    But, this is not the responsibility of the customer, the order class is the one which as all the information about the orders.


    It tries to determine who is taking the responsibility of creating the objects.

    You try to answer these question:

  • Who is responsible for creating the objects?, or, how those objects are created in the first place?
  • Does one object contain another (composition relationship)?
  • Does one object very closely use another, or, Will one object know enough to make another object?
  • And if so, it would seem to make sense to nominate those objects as taking that creator role and making it obvious which objects are responsible for creating other objects.

    A common design pattern that applies this principle is called Factory Pattern.

    Low Coupling

    It means you try to reduce the dependency between your objects.

    If one object needs to connect tightly to five other objects and call 20 different methods just to work, you have a high coupling.

    Lots of dependencies meaning lots of potential for breaking things if you make a change to any of these objects.

    Now low coupling does not mean no coupling. Objects do need to know about each other, but as much as possible they should do what they can with the minimum of dependencies.

    High Cohesion

    The more you have a class that has relevant and focused responsibilities, the higher cohesion you will have.

    You try to make the responsibilities of your classes relevant, related as much as you can. You may need to break a class into some classes and distribute the responsibilities, instead of having a single class that does everything.


    If, for example, we have a user interface and also some business related classes.

    We don’t want to have high coupling between them to actually tie them directly together, where the user interface object has to know about the business objects and the vice-versa.

    It’s very common to create a controller class just for the purpose of handling the connection between the user interface and the business related objects.

    It’s perfectly normal for object to exist that takes a role in a program that isn’t a real world object as long as it has a well defined responsibility.

    There is a common architectural design pattern called Model View Controller (MVC) which is an example of having a controller class.

    Pure Fabrication

    What if there’s something that needs to exist in the application that doesn’t announce itself as an obvious class or real-world object?. What if you have behavior that doesn’t naturally fit in existing classes?

    Well, rather than force that behavior into an existing class where it doesn’t belong, which means we are decreasing cohesion, we instead invent, we fabricate a new class.

    That class might not have existed in our conceptual model, but it needs to exist now. And there’s nothing wrong with creating a class that represents pure functionality as long as you know why you’re doing it.


    This is the idea that we can decrease coupling between objects.

    If you have multiple objects that need to talk to each other, it’s very easy to have high coupling between them, where there is a lot of dependencies.

    And what we can do instead is reduce those direct connections by putting an indirection object between them to simplify the amount of connections that each object has to make.


    Having an object that can take the shape of several different objects. This allows us to trigger the correct behavior.

    If, for example, we have an interface that’s implemented by several classes, you can assign or pass an instance of any of the sub classes to a reference variable that has the interface as it’s type. This will allow you to trigger the right methods, for the implementing class.

    // Animal class is a generic class where Dog, Duck, & Kangaroo inherits from.Dog shepherd = new Dog("Jack", "gold"); Duck mallard = new Duck("Daffy", "green"); Kangaroo rock = new Kangaroo("Steve", "red", 1.5); Animal animals [] = { shepherd, mallard, rock }; /* Now, you should notice we called the display() method, without knowing exactly what the type of object, and it did displayed the correct method for each animal object. */for(Animal animal: animals) { animal.display(); } Protected Variations

    How to design a system so that changes and variations have the minimum impact on what already exists.

    Identify the parts of the system that are more likely to change, separate them from what stays the same, and then, encapsulate every part that vary in the system.

    Most of the concepts we have been exploring are simply way of doing this, things like encapsulation and data-hiding, making your attributes private.

    Interfaces are another area where we can wrap the unstable parts with an interface, and using polymorphism to create various implementations of this interface.

    The Liskov substitution principle, where the child classes should always work when treated as their parent classes is another way.

    The open/closed principle that we can add, but we try not to change code that works already is yet another.

    Code Smell

    Code Smells are a great term for when reading code, the code may be valid, it may work, but there is something about it that just doesn’t smell right.

    It’s often a clue, a warning sign of a deeper problem, that there is a part in the code indicates violation of fundamental design principles and negatively impact design quality.

    And here are just a few examples of what we mean by a code smell.

    Long Method

    One would be the idea of a long method. We open up a method to read it, it has got many lines. This is the kind of thing that really needs to be split up into much smaller methods.


    Working with very short or very long identifiers. Aside from using letters like ‘i’ for indexes and iteration, we shouldn’t be expecting to see variables called A and B and C in real code.


    Another clue would be pointless comments. Yes, code should be commented and code should be well-written so that it’s readable and the code comments itself.

    We do want comments, but we don’t want comments where the comment is actually longer than the code that it’s describing.

    The God Object

    This is where you have one master object that tries to do everything in the program, or at least one object that seems to be doing very different responsibilities that have nothing to do with each other.

    It’s a clue that this needs to be revisited and broken apart into the right kind of objects.

    Feature Envy

    And then there’s feature envy. If a class seems to do very little except it uses all the methods of one other class, it’s another sign that you need to rethink the roles of one or the other.

    Java and Object-Oriented Programming | killexams.com real questions and Pass4sure dumps

    This chapter is from the book 

    Many seasoned Java developers will scoff at the fact that this section even exists in this book. It is here for two very important reasons. The first is that I continually run across Java applications built with a procedural mind-set. The fact that you know Java doesn't mean that you have the ability to transform that knowledge into well-designed object-oriented systems. As both an instructor and consultant, I see many data-processing shops send COBOL and/or Visual Basic developers to a three-day class on UML and a five-day class on Java and expect miracles. Case in point: I was recently asked to review a Java application to assess its design architecture and found that it had only two classes—SystemController and ScreenController—which contained over 70,000 lines of Java code.

    The second reason for the emphasis on how the language maps to object-oriented principles is that people like language comparisons and how they stack up to their counterparts. To appease those that live and die by language comparisons, let's put Java under the scrutiny of what constitutes an object-oriented language.

    No definitive definition of what makes a language object-oriented is globally accepted. However, a common set of criteria I personally find useful is that the language must support the following:

  • Classes
  • Complex types (Java reference types)
  • Message passing
  • Encapsulation
  • Inheritance
  • Polymorphism
  • These are discussed in the next subsections.

    Java and Classes

    Java allows classes to be defined. There are no stray functions floating around in Java. A class is a static template that contains the defined structure (attributes) and behavior (operations) of a real-world entity in the application domain. At runtime, the class is instantiated, or brought to life, as an object born in the image of that class. In my seminars, when several folks new to the object world are in attendance, I often use the analogy of a cookie cutter. The cookie cutter is merely the template used to stamp out what will become individually decorated and unique cookies. The cookie cutter is the class; the unique blue, green, and yellow gingerbread man is the object (which I trust supports a bite operation).

    Java exposes the class to potential outside users through its public interface. A public interface consists of the signatures of the public operations supported by the class. A signature is the operation name and its input parameter types (the return type, if any, is not part of the operation's signature).

    Good programming practice encourages developers to declare all attributes as private and allow access to them only via operations. As with most other languages, however, this is not enforced in Java. Figure 2-1 outlines the concept of a class and its interface.

    FIGURE 2-1 Public interface of a class

    The figure uses a common eggshell metaphor to describe the concept of the class's interface, as well as encapsulation. The internal details of the class are hidden from the outside via a well-defined interface. In this case, only four operations are exposed in the classes interface (Operation_A, B, C, and D). The other attributes and operations are protected from the outside world. Actually, to the outside world, it's as if they don't even exist.

    Suppose you want to create an Order class in Java that has three attributes—orderNumber, orderDate, and orderTotal—and two operations—calcTotalValue() and getInfo(). The class definition could look like this:

    /** * Listing 1 * This is the Order class for the Java/UML book */ package com.jacksonreed; import java.util.*; public class Order { private Date orderDate; private long orderNumber; private long orderTotal; public Order() { } public boolean getInfo() { return true; } public long calcTotalValue() { return 0; } public Date getOrderDate() { return orderDate; } public void setOrderDate(Date aOrderDate) { orderDate = aOrderDate; } public long getOrderNumber() { return orderNumber; } public void setOrderNumber(long aOrderNumber) { orderNumber = aOrderNumber; } public long getOrderTotal() { return orderTotal; } public void setOrderTotal(long aOrderTotal) { orderTotal = aOrderTotal; } public static void main(String[] args) { Order order = new Order(); System.out.println("instantiated Order"); System.out.println(order.getClass().getName()); System.out.println(order.calcTotalValue()); try { Thread.currentThread().sleep(5*1000); } catch(InterruptedException e) {} } }

    A few things are notable about the first bit of Java code presented in this book. Notice that each of the three attributes has a get and a set operation to allow for the retrieval and setting of the Order object's properties. Although doing so is not required, it is common practice to provide these accessor-type operations for all attributes defined in a class. In addition, if the Order class ever wanted to be a JavaBean, it would have to have "getters and setters" defined in this way.

    Some of the method code in the main() operation does a few things of note. Of interest is that a try block exists at the end of the operation that puts the current thread to sleep for a bit. This is to allow the console display to freeze so that you can see the results.

    If you type in this class and then compile it and execute it in your favorite development tool or from the command prompt with

    javac order.java //* to compile it java order //* to run it

    you should get results that look like this:

    instantiated Order com.jacksonreed.Order 0


    Going forward, I promise you will see no code samples with class, operation, or attribute names of foo, bar, or foobar.

    More on Java and Classes

    A class can also have what are called class-level operations and attributes. Java supports these with the static keyword. This keyword would go right after the visibility (public, private, protected) component of the operation or attribute. Static operations and attributes are needed to invoke either a service of the class before any real instances of that class are instantiated or a service that doesn't directly apply to any of the instances. The classic example of a static operation is the Java constructor. The constructor is what is called when an object is created with the New keyword. Perhaps a more business-focused example is an operation that retrieves a list of Customer instances based on particular search criteria.

    A class-level attribute can be used to store information that all instances of that class may access. This attribute might be, for example, a count of the number of objects currently instantiated or a property about Customer that all instances might need to reference.

    Java and Complex Types (Java Reference Types)

    A complex type, which in Java is called a reference type, allows variables typed as something other than primitive types (e.g., int and boolean) to be declared. In Java, these are called reference types. In object-oriented systems, variables that are "of" a particular class, such as Order, Customer, or Invoice, must be defined. Taken a step further, Order could consist of other class instances, such as OrderHeader and OrderLine.

    In Java, you can define different variables that are references to runtime objects of a particular class type:

    Public Order myOrder; Public Customer myCustomer; Public Invoice myInvoice;

    Such variables can then be used to store actual object instances and subsequently to serve as recipients of messages sent by other objects. In the previous code fragment, the variable myOrder is an instance of Order. After the myOrder object is created, a message can be sent to it and myOrder will respond, provided that the operation is supported by myOrder's interface.

    Java and Message Passing

    Central to any object-oriented language is the ability to pass messages between objects. In later chapters you will see that work is done in a system only by objects that collaborate (by sending messages) to accomplish a goal (which is specified in a use-case) of the system.

    Java doesn't allow stray functions floating around that are not attached to a class. In fact, Java demands this. Unfortunately, as my previous story suggested, just saying that a language requires everything to be packaged in classes doesn't mean that the class design will be robust, let alone correct.

    Java supports message passing, which is central to the use of Java's object-oriented features. The format closely resembles the syntax of other languages, such as C++ and Visual Basic. In the following code fragment, assume that a variable called myCustomer, of type Customer, is defined and that an operation called calcTotalValue() is defined for Customer. Then the calcTotalValue() message being sent to the myCustomer object in Java would look like this:


    Many developers feel that, in any other structured language, this is just a fancy way of calling a procedure. Calling a procedure and sending a message are similar in that, once invoked, both a procedure and a message implement a set of well-defined steps. However, a message differs in two ways:

  • There is a designated receiver, the object. Procedures have no designated receiver.

  • The interpretation of the message—that is, the how-to code (called the method) used to respond to the message—can vary with different receivers. This point will become more important later in the chapter, when polymorphism is reviewed.

  • The concepts presented in this book rely heavily on classes and the messaging that takes place between their instances, or objects.

    Java and Encapsulation

    Recall that a class exposes itself to the outside world via its public interface and that this should be done through exposure to operations only, and not attributes. Java supports encapsulation via its ability to declare both attributes and operations as public, private, or protected. In UML this is called visibility.

    Using the code from the previous Order example, suppose you want to set the value of the orderDate attribute. In this case, you should do so with an operation. An operation that gets or sets values is usually called a getter or a setter, respectively, and collectively such operations are called accessors. The local copy of the order date, orderDate, is declared private. (Actually, all attributes of a class should be declared private or protected, so that they are accessible only via operations exposed as public to the outside world.)

    Encapsulation provides some powerful capabilities. To the outside world, the design can hide how it derives its attribute values. If the orderTotal attribute is stored in the Order object, the corresponding get operation defined previously looks like this:

    public long getOrderTotal() { return orderTotal; }

    This snippet of code would be invoked if the following code were executed by an interested client:

    private long localTotal; private Order localOrder; localOrder = New Order(); localTotal = localOrder.getOrderTotal()

    However, suppose the attribute orderTotal isn't kept as a local value of the Order class, but rather is derived via another mechanism (perhaps messaging to its OrderLine objects). If Order contains OrderLine objects (declared as a Vector or ArrayList of OrderLine objects called myOrderLines) and OrderLine knows how to obtain its line totals via the message getOrderLineTotal(), then the corresponding get operation for orderTotal within Order will look like this:

    public long getOrderTotal() { long totalAmount=0; for (int i=0; i < myOrderLines.length; i++) { totalAmount = totalAmount + myOrderLines[i].getOrderLineTotal(); } return totalAmount; }

    This code cycles through the myOrderLines collection, which contains all the Orderline objects related to the Order object, sending the getOrderLineTotal() message to each of Order's OrderLine objects. The getOrderTotal() operation will be invoked if the following code is executed by an interested client:

    long localTotal; Order myOrder; myOrder = new Order(); localTotal = localOrder.getOrderTotal()

    Notice that the "client" code didn't change. To the outside world, the class still has an orderTotal attribute. However, you have hidden, or encapsulated, just how the value was obtained. This encapsulation allows the class's interface to remain the same (hey, I have an orderTotal that you can ask me about), while the class retains the flexibility to change its implementation in the future (sorry, how we do business has changed and now we must derive orderTotal like this). This kind of resiliency is one of the compelling business reasons to use an object-oriented programming language in general.

    Java and Inheritance

    The inclusion of inheritance is often the most cited reason for granting a language object-oriented status. There are two kinds of inheritance: interface and implementation. As we shall see, Java is one of the few languages that makes a clear distinction between the two.

    Interface inheritance (Figure 2-2) declares that a class that is inheriting an interface will be responsible for implementing all of the method code of each operation defined in that interface. Only the signatures of the interface are inherited; there is no method or how-to code.

    FIGURE 2-2 Interface inheritance

    Implementation inheritance (Figure 2-3) declares that a class that is inheriting an interface may, at its option, use the method code implementation already established for the interface. Alternatively, it may choose to implement its own version of the interface. In addition, the class inheriting the interface may extend that interface by adding its own operations and attributes.

    FIGURE 2-3 Implementation inheritance

    Each type of inheritance should be scrutinized and used in the appropriate setting. Interface inheritance is best used under the following conditions:

  • The base class presents a generic facility, such as a table lookup, or a derivation of system-specific information, such as operating-system semantics or unique algorithms.

  • The number of operations is small.

  • The base class has few, if any, attributes.

  • Classes realizing or implementing the interface are diverse, with little or no common code.

  • Implementation inheritance is best used under the following conditions:

  • The class in question is a domain class that is of primary interest to the application (i.e., not a utility or controller class).

  • The implementation is complex, with a large number of operations.

  • Many attributes and operations are common across specialized implementations of the base class.

  • Some practitioners contend that implementation inheritance leads to a symptom called the fragile base class problem. Chiefly, this term refers to the fact that over time, what were once common code and attributes in the superclass may not stay common as the business evolves. The result is that many, if not all, of the subclasses, override the behavior of the superclass. Worse yet, the subclasses may find themselves overriding the superclass, doing their own work, and then invoking the same operation again on the superclass. These practitioners espouse the idea of using only interface inheritance. Particularly with the advent of Java and its raising of the interface to a first-class type, the concept and usage of interface-based programming have gained tremendous momentum.

    As this book evolves, keeping in mind the pointers mentioned here when deciding between the two types of inheritance will be helpful. Examples of both constructs will be presented in the theme project that extends throughout this book.

    Implementation Inheritance

    Java supports implementation inheritance with the extends keyword. A class wanting to take advantage of implementation inheritance simply adds an extendsClassName statement to its class definition. To continue the previous example, suppose you have two different types of orders, both warranting their own subclasses: Commercial and Retail. You would still have an Order class (which isn't instantiated directly and which is called abstract). The previous fragment showed the code for the Order class. Following is the code for the Commercial class.

    package com.jacksonreed; public class Commercial extends Order { public Commercial() { } /* Unique Commercial code goes here */ }

    Implementation inheritance allows the Commercial class to utilize all attributes and operations defined in Order. This will be done automatically by the Java Virtual Machine (JVM) in conjunction with the language environment. In addition, implementation inheritance has the ability to override and/or extend any of Order's behavior. Commercial may also add completely new behavior if it so chooses.

    Interface Inheritance

    Java supports interface inheritance with the implements keyword. A class wanting to realize a given interface (actually being responsible for the method code) simply adds an implements InterfaceName statement. However, unlike extension of one class by another class, implementation of an interface by a class requires that the interface be specifically defined as an interface beforehand.

    Looking again at the previous example with Order, let's assume that this system will contain many classes—some built in this release, and some built in future releases—that need the ability to price themselves. Remember from earlier in this chapter that one of the indicators of using interface inheritance is the situation in which there is little or no common code but the functional intent of the classes is the same. This pricing functionality includes three services: the abilities to calculate tax, to calculate an extended price, and to calculate a total price. Let's call the operations for these services calcExtendedPrice(), calcTax(), and calcTotalPrice(), respectively, and assign them to a Java interface called IPrice. Sometimes interface names are prefixed with the letter I to distinguish them from other classes:

    package com.jacksonreed; interface IPrice { long calcExtendedPrice(); long calcTax(); long calcTotalPrice(); }

    Notice that the interface contains only operation signatures; it has no implementation code. It is up to other classes to implement the actual behavior of the operations. For the Order class to implement, or realize, the IPrice interface, it must include the implements keyword followed by the interface name:

    public class Order implements IPrice { }

    If you try to implement an interface without providing implementations for all of its operations, your class will not compile. Even if you don't want to implement any method code for some of the operations, you still must have the operations defined in your class.

    One very powerful aspect of interface inheritance is that a class can implement many interfaces at the same time. For example, Order could implement the IPrice interface and perhaps a search interface called ISearch. However, a Java class may extend from only one other class.

    Java and Polymorphism

    Polymorphism is one of those $50 words that dazzles the uninformed and sounds really impressive. In fact, polymorphism is one of the most powerful features of any object-oriented language.

    Roget's II: The New Thesaurus cross-references the term polymorphism to the main entry of variety. That will do for starters. Variety is the key to polymorphism. The Latin root for polymorphism means simply "many forms." Polymorphism applies to operations in the object-oriented context. So by combining these two thoughts, you could say that operations are polymorphic if they are identical (not just in name but also in signatures) but offer variety in their implementations.

    Polymorphism is the ability of two different classes each to have an operation that has the same signature, while having two very different forms of method code for the operation. Note that to take advantage of polymorphism, either an interface inheritance or an implementation inheritance relationship must be involved.

    In languages such as COBOL and FORTRAN, defining a routine to have the same name as another routine will cause a compile error. In object-oriented languages such as Java and C++, several classes might have an operation with the same signature. Such duplication is in fact encouraged because of the power and flexibility it brings to the design.

    As mentioned previously, the implements and extends keywords let the application take advantage of polymorphism. As we shall see, the sample project presented later in this book is an order system for a company called Remulak Productions. Remulak sells musical equipment, as well as other types of products. There will be a Product class, as well as Guitar, SheetMusic, and Supplies classes.

    Suppose, then, that differences exist in the fundamental algorithms used to determine the best time to reorder each type of product (called the economic order quantity, or EOQ). I don't want to let too much out of the bag at this point, but there will be an implementation inheritance relationship created with Product as the ancestor class (or superclass) and the other three classes as its descendants (or subclasses). The scenario that follows uses implementation inheritance with a polymorphic example. Note that interface inheritance would yield the same benefits and be implemented in the same fashion.

    To facilitate extensibility and be able to add new products in the future in a sort of plug-and-play fashion, we can make calcEOQ() polymorphic. To do this in Java, Product would define calcEOQ() as abstract, thereby informing any inheriting subclass that it must provide the implementation. A key concept behind polymorphism is this: A class implementing an interface or inheriting from an ancestor class can be treated as an instance of that ancestor class. In the case of a Java interface, the interface itself is a valid type.

    For example, assume that a collection of Product objects is defined as a property of the Inventory class. Inventory will support an operation, getAverageEOQ(), that needs to calculate the average economic order quantity for all products the company sells. To do this requires that we iterate over the collection of Product objects called myProducts to get each object's unique economic order quantity individually, with the goal of getting an average:

    public long getAverageEOQ() { long totalAmount=0; for (int i=0; i < myProducts.length; i++) { totalAmount = totalAmount + myProducts[i].calcEOQ(); } return totalAmount / myProducts.length; }

    But wait! First of all, how can Inventory have a collection of Product objects when the Product class is abstract (no instances were ever created on their own)? Remember the maxim from earlier: Any class implementing an interface or extending from an ancestor class can be treated as an instance of that interface or extended class. A Guitar "is a" Product, SheetMusic "is a" Product, and Supplies "is a" Product. So anywhere you reference Guitar, SheetMusic, or Supplies, you can substitute Product.

    Resident in the array myProducts within the Inventory class are individual concrete Guitar, SheetMusic, and Supplies objects. Java figures out dynamically which object should get its own unique calcEOQ() message. The beauty of this construct is that later, if you add a new type of Product—say, Organ—it will be totally transparent to the Inventory class. That class will still have a collection of Product types, but it will have four different ones instead of three, each of which will have its own unique implementation of the calcEOQ() operation.

    This is polymorphism at its best. At runtime, the class related to the object in question will be identified and the correct "variety" of the operation will be invoked. Polymorphism provides powerful extensibility features to the application by letting future unknown classes implement a predictable and well-conceived interface without affecting how other classes deal with that interface.

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