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Process Models Chapter 2 – Process Models CS485/540 Software Engineering Cengiz Günay Fall 2014 Günay Ch 2 Process Models Fall 2014 1 / 5 A Generic Process Model SEPA 7/e: © 2009, Roger Pressman. 2 Process Flow SEPA 7/e: © 2009, Roger Pressman. 3 Identifying a Task Set A task set defines the actual work to be done to accomplish the objectives of a software engineering action. A list of the task to be accomplished A list of the work products to be produced A list of the quality assurance filters to be applied SEPA 7/e: © 2009, Roger Pressman. 4 Process Patterns A process pattern describes a process­related problem that is encountered during software engineering work, identifies the environment in which the problem has been encountered, and suggests one or more proven solutions to the problem. Stated in more general terms, a process pattern provides you with a template [Amb98]—a consistent method for describing problem solutions within the context of the software process. SEPA 7/e: © 2009, Roger Pressman. 5 Process Pattern Types Stage patterns—defines a problem associated with a framework activity for the process. Task patterns—defines a problem associated with a software engineering action or work task and relevant to successful software engineering practice Phase patterns—define the sequence of framework activities that occur with the process, even when the overall flow of activities is iterative in nature. SEPA 7/e: © 2009, Roger Pressman. 6 Prescriptive Models Prescriptive process models advocate an orderly approach to software engineering That leads to a few questions … If prescriptive process models strive for structure and order, are they inappropriate for a software world that thrives on change? Yet, if we reject traditional process models (and the order they imply) and replace them with something less structured, do we make it impossible to achieve coordination and coherence in software work? SEPA 7/e: © 2009, Roger Pressman. 8 The Waterfall Model Communication project initiation Planning requirement gathering estimating Modeling scheduling analysis tracking Construction design code Deployment test delivery support feedback SEPA 7/e: © 2009, Roger Pressman. 9 The V-Model SEPA 7/e: © 2009, Roger Pressman. 10 The Incremental Model increment # n C o m m u n i c a t i o n P l a n n i n g M o d e l i n g analys is C o n s t r u c t i o n des ign code D e p l o y m e n t t es t d e l i v e r y f e e d b a c k delivery of increment # 2 nth increment C o m m u n i c a t i o n P l a n n i n g M o d e l i n g analys is C o n s t r u c t i o n des ign c ode D e p l o y m e n t t es t d e l i v e r y delivery of f e e d b a c k increment # 1 2nd increment C o m m u n i c a t i o n P l a n n i n g M o d e l i n g analys is C o n s t r u c t i o n des ign c ode D e p l o y m e n t t es t d e l i v e r y delivery of f e e d b a c k 1st increment project calendar time SEPA 7/e: © 2009, Roger Pressman. 11 Evolutionary Models: Prototyping QuQuickick plan Communication plan communication Modeling Modeling Quick design Quick design Deployment Deployment Construction Delivery of prototype delivery& Feedb &ack Construction feedback Constructionof pofr oprototypetotype SEPA 7/e: © 2009, Roger Pressman. 12 Evolutionary Models: The Spiral planning estimation scheduling risk analysis communication modeling analysis design start deployment construction delivery code feedback test SEPA 7/e: © 2009, Roger Pressman. 13 none Modeling activity represents the state Under of a software engineering activity or task Evolutionary Models: development Concurrent Awaiting changes Under review Under revision Baselined Done SEPA 7/e: © 2009, Roger Pressman. 14 Soware Engineering As A Discipline • Several commonly‐acknowledged models • All the models aempt to describe “how to get it done” – Linear – Iterave – Evoluonary – Parallel • In real world, hybrids abound – A lile of this, a lile of that – What is the project? Who are the people? When is the deadline? These (and more) are all factors in determining the right process model for the project, team, or company. CS‐584/Fall 2009/Emory U 2 Traditional Process Models Summary Basically: Linear vs. incremental/evolutionary. Protoyping: needed when all requirements cannot be obtained without an example. 1st protoype thrown away? Take home message: set milestones for iterative production Günay Ch 2 Process Models Fall 2014 2 / 5 Still Other Process Models Component based development—the process to apply when reuse is a development objective Formal methods—emphasizes the mathematical specification of requirements AOSD—provides a process and methodological approach for defining, specifying, designing, and constructing aspects Unified Process—a “use-case driven, architecture- centric, iterative and incremental” software process closely aligned with the Unified Modeling Language (UML) SEPA 7/e: © 2009, Roger Pressman. 15 Aspect-Oriented Development AOSD: aspect-oriented development aspects are horizontal slices across a vertical development process. Example: interfaces, security, persistancy, memory management, etc. Unified process: nontraditional approch; enter agile computing (Ch 3) Günay Ch 2 Process Models Fall 2014 3 / 5 The Unified Process (UP) Eelaborationlaboration inceptionInception construction Release transition software increment production SEPA 7/e: © 2009, Roger Pressman. 16 UP Phases UP Phases Inception Elaboration Construction Transition Production Workflows Requirements Analysis Design Implementation Test Support Iterations #1 #2 #n-1 #n SEPA 7/e: © 2009, Roger Pressman. 17 UP Work Products Inception phase Elaboration phase Vision document Initial use-case model Construction phase Initial project glossary Use-case model Initial business case Supplementary requirements Transition phase Initial risk assessment. including non-functional Design model Project plan, Analysis model Software components phases and iterations. Software architecture Integrated software Delivered software increment Business model, Description. increment Beta test reports if necessary. Executable architectural Test plan and procedure General user feedback One or more prototypes prototype. Inc ept i o Test cases n Preliminary design model Support documentation Revised risk list user manuals Project plan including installation manuals iteration plan description of current adapted workflows increment milestones technical work products Preliminary user manual SEPA 7/e: © 2009, Roger Pressman. 18 Personal Software Process (PSP) Planning. This activity isolates requirements and develops both size and resource estimates. In addition, a defect estimate (the number of defects projected for the work) is made. All metrics are recorded on worksheets or templates. Finally, development tasks are identified and a project schedule is created. High­level design. External specifications for each component to be constructed are developed and a component design is created. Prototypes are built when uncertainty exists. All issues are recorded and tracked. High­level design review. Formal verification methods (Chapter 21) are applied to uncover errors in the design. Metrics are maintained for all important tasks and work results. Development. The component level design is refined and reviewed. Code is generated, reviewed, compiled, and tested. Metrics are maintained for all important tasks and work results. Postmortem. Using the measures and metrics collected (this is a substantial amount of data that should be analyzed statistically), the effectiveness of the process is determined. Measures and metrics should provide guidance for modifying the process to improve its effectiveness. SEPA 7/e: © 2009, Roger Pressman. 19 Team Software Process (TSP) Build self­directed teams that plan and track their work, establish goals, and own their processes and plans. These can be pure software teams or integrated product teams (IPT) of three to about 20 engineers. Show managers how to coach and motivate their teams and how to help them sustain peak performance. Accelerate software process improvement by making CMM Level 5 behavior normal and expected. The Capability Maturity Model (CMM), a measure of the effectiveness of a software process, is discussed in Chapter 30. Provide improvement guidance to high­maturity organizations. Facilitate university teaching of industrial­grade team skills. SEPA 7/e: © 2009, Roger Pressman. 20 Fact/Fallacy Tidbit • Fact 2 The best programmers outperform the worst by a factor of 28* • Data – Decades‐old studies led to the original performance rao – Widely accepted, widely ignored! – Some interesng reading on the topic: • hp://www.devtopics.com/programmer‐producvity‐the‐tenfinity‐factor/ • hp://ibmsystemsmag.blogs.com/idevelop/2008/09/looking‐for‐way.html • hp://www.joelonsoware.com/arcles/FieldGuidetoDevelopers.html • hp://www.arma.com/weblogs/viewpost.jsp?thread=4738 – An excellent book on the topic, widely regarded as the best: • Peopleware: Producve Projects and Teams by Tom DeMarco and Timothy Lister. *From Robert Glass, “Facts & Fallacies of Soware Engineering” CS‐584/Fall 2009/Emory U 4 Student Performance Data • From Prof. Eisenstat at Yale, results of CS‐323 course • Courtesy of Joel Spolsky: – hp://www.joelonsoware.com/arcles/HighNotes.html CS‐584/Fall 2009/Emory U 5 Improving Performance • Process – Fit the process to the project and the team – Understanding‐Planning‐Developing‐Tesng‐Documenng – Waterfall, Evoluonary, Agile, Hybrid, etc.: Select, know, use • Tools – IDEs (Visual C++) and Frameworks (Rails)
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