200 likes | 211 Views
Explore different software life cycles, including Waterfall, V-model, RAD, Spiral, Unified Process, and Agile models like XP and Scrum. Learn about the pros and cons of each model and the concept of capability maturity levels.
E N D
Software Life Cycles ECE 417/617:Elements of Software Engineering Stan Birchfield Clemson University
The software crisis • Three categories of S/W projects: • 16% successful(fully functional, on-time, and on-budget) • 53% challenged(reduced functionality, late, over-budget) • 31% impaired(cancelled) [from Standish Group (1995)]
Waterfall model Requirements Analysis System Design Object Design Coding Testing Installation Maintenance [adapted from Royce (1970)]
Life cycle phases 5 phases of every S/W life cycle: • Communication • Planning • Modeling • Construction • Deployment
What is wrong with waterfall? Requirements Analysis Maintenance System Design Installation Object Design Testing Coding Interrelated nonlinear, sequential
V-model Requirements Analysis Acceptance Testing is validated by less detail System Design System Testing Object Design Unit Testing more detail Coding build system validate system
Incremental model increment #3 features version #3 A D C T M increment #2 version #2 A D C T M increment #1 version #1 A D C T M time
Rapid application development (RAD) Team #1 Modeling Communication Construction Planning Deployment Team #N Modeling Construction 60 – 90 days
Prototyping Communication • Enables faster feedback • Can be incorporated into other models • But what is the danger? Feedback Quick plan Delivery Quick modeling Construct Prototype
Shark tooth model [from Michael Black]
Spiral model Deployment Communication start Construction Planning [Boehm] Modeling
Unified process software increment inception Communication • Incremental, iterative • “Unified” same originators as UML • Also called Rational Unified Process (RUP) Planning Deployment elaboration transition Modeling Construction construction
Unified process work products Inception phase vision document initial use-case model initial business case initial risk list project plan prototype(s) ... Elaboration phase use-case model requirements analysis model preliminary model revised risk list preliminary manual ... Construction phase design model SW components test plan test procedure test cases user manual installation manual ... Transition phase SW increment beta test reports user feedback ...
Extreme programming (XP) [Kent Beck 1999] [from extremeprogramming.org]
XP principles • Test-driven development • The planning game • On-site customer • Pair programming • Continuous integration • Refactoring • Small releases • Simple design • System metaphor • Collective code ownership • Coding standards • 40-hour work week Pros and cons?
Prescriptive models Waterfall Incremental RAD Spiral Concurrent development Component-based development Formal methods Aspect oriented Unified process (RUP) Agile models Extreme programming (XP) Adaptive software development (ASD) Dynamic systems development (DSDM) Scrum Crystal Feature driven development (FDD) Agile model Model summary
Synch-and-stabilize • How to balance structure and flexibility? • Solution: • Plan product with vision statement • Translate into specification document with enough detail to divide the work • Divide into parts and assign to teams • Teams are free to implement, innovate as they wish • Teams work under common environment • Teams check-in work frequently • Frequent (daily) builds • Always a working system • Easy to test, see defects, measure progress continually [from “How Microsoft Builds Software”, Cusumano and Selby]
Capability maturity model (CMM) Five levels of CMM: • PerformedAd hoc, relies on heroic efforts of individuals, life cycle is black box to client – no way to interact • RepeatableEach project has well-defined model, able to predict similar future projects, but models differ among projects • DefinedAll managerial and technical activities follow documented model, customized version of model produced at beginning of each project • Quantitatively managedUses quanitifiable metrics for measuring progress of activities and deliverables • OptimizedFeedback from measurement data are used to improve the model over lifetime of organization [Carnegie-Mellon’s Software Engineering Institute (SEI)]
Personal software process (PSP) • Individual developers should • measure the quality of output • plan (estimate and schedule work) • identify likely and actual errors • use metrics to improve process • Activities: (1) planning, (2) high-level design, (3) high-level design review, (4) development, (5) postmortem • Disciplined metrics-based approach to software engineering • Requires significant training • Improves productivity and quality, but resisted by many developers (culture shock) [SEI’s Watts Humphreys]
Team software process (TSP) • Project team should • be self-directed, able to plan and track their work, establish goals, and own their processes and plans • have consistent understanding of its overall goals and objectives • define roles and responsibilities • track quantitative project data • identify and implement an appropriate process for the project • define local standards • continually assess and respond to risks • track, manage, and report project status • Activities: (1) launch, (2) high-level design, (3) implementation, (4) integration and test, (5) postmortem • Rigorous approach that requires a full commitment from the team • Requires thorough training • Improves productivity and quality [SEI’s Watts Humphreys]