Software Engineering Natallia Kokash email: nkokash@liacs.nl 1 N. Kokash, Software Engineering Software Engineering Introduction Course overview Logistics Literature Practical assignment Evaluation What is Software Engineering? What does Software Engineer do? Software Engineering Processes 2 N. Kokash, Software Engineering Software Engineering Natallia Kokash, researcher at LIACS Research experience Postdoc at Centrum Wiskunde & Informatica (CWI), Amsterdam Ph.D. from University of Trento, Italy (2008) Research in Software Engineering Semantics of Modeling Languages Software Design and Verification Service-Oriented Computing Industrial Experience Collaboration Thales-France, Telcordia-Poland, PWC. Two with large international companies years of experience as Software Engineer Development of banking systems N. Kokash, Software Engineering 3 Software Engineering N. Kokash, Software Engineering 4 Software Engineering What will you learn? Engineering = skill + knowledge This course 70% knowledge and 30% skills Basic concepts & vocabulary of SE Main activities in SE projects Main methods and techniques excluding: programming Guest lectures by professionals N. Kokash, Software Engineering 5 Software Engineering Literature 70% - H. van Vliet, Software Engineering: Principles and Practice, 3rd ed., 2008. A. Shalloway and J.R. Trott, “Design Patterns Explained” (2004) WWW Check my course web page http://homepages.cwi.nl/~kokash/courses.html These slides are based on the slides by Prof. Dr. Hans van Vliet 6 N. Kokash, Software Engineering Software Engineering Course overview Theme Course Overview, Introduction to Software Engineering (SE) & Software Development (SD) Lifecycle Requirements Engineering & Configuration Management Software Modeling Chapter 1, 2, 3.1-3.2 4, 9 3.3-3.9,10 Software Design & Architectural Styles 11, 12 Software Quality Assurance & Metrics 6 Team Organization & Global SD Software Reuse, Component-based & Service-oriented Computing 5, 20 17, 18,19 Design Patterns & Refactoring tbd Software Testing 13 Software Maintenance 14 Cost Estimation, Planning & Control 7, 8 Empirical Research in SE tbd 7 N. Kokash, Software Engineering Software Engineering Logistics Lecturer (B.Sc. Informatica & Economie, Den Haag) Lecturer (B.Sc. Informatica, Leiden) Christoph Johann Stettina, M.Sc Course Manager Drs. Werner Heijstek Werkgroepdocent, Leiden Dr. Natallia Kokash Dr. Michel R.V. Chaudron You may take hoorcolleges (but not werkcolleges) at either location The schedule for Leiden can be found at www.liacs.nl Check slides by Drs. W. Heijstek http://www.liacs.nl/~heijstek/se11-slides/ N. Kokash, Software Engineering 8 Software Engineering Team of 3-4 people Focus on a proper development process Results: requirements specification, software design, implementation, documentation and testing report Any tools or programming languages (pointers to useful tools & libraries will be given) 9 N. Kokash, Software Engineering Software Engineering Problem Convert a picture of a UML class diagram (.bmp, .jpg) to a UML class diagram in XMI format 10 N. Kokash, Software Engineering Software Engineering Details Retrieve images of UML class diagrams from Google images Recognize basic shapes (rectangles, arrows) Use optical character recognition (OCR) tools to recognize names of classes, attributes, annotations, etc. Create a graph-based representation of a recognized class diagram Write an XMI file 11 N. Kokash, Software Engineering Software Engineering Final evaluation 50% written exam But > 5.5 50% practical assignment 25% Requirement specification 25% Software architecture and design 25% Implementation 25% Quality evaluation 12 N. Kokash, Software Engineering Software Engineering Software Crises “The major cause of the software crisis is that the machines have become several orders of magnitude more powerful! To put it quite bluntly: as long as there were no machines, programming was no problem at all; when we had a few weak computers, programming became a mild problem, and now we have gigantic computers, programming has become an equally gigantic problem.” Edsger Dijkstra, The Humble Programmer, Communications of the ACM (1972) 13 N. Kokash, Software Engineering Software Engineering Who is Edsger Dijkstra? N. Kokash, Software Engineering Born in Rotterdam in 1930. Studied theoretical physics at the University of Leiden where he became interested in “programming” Received numerous awards including Turing Award in 1972 1.300+ publications Helped the emancipation of computer science as a science Best known for his "shortest path algorithm” and his hate to the goto operator. 14 Software Engineering The crisis manifest Projects running over-budget Projects running over-time Software was very inefficient Software was of low quality Software often did not meet requirements Projects were unmanageable and code difficult to maintain Software was never delivered 15 N. Kokash, Software Engineering Software Engineering The beginning of Software Engineering 1968/69 NATO conferences: introduction of the term Software Engineering Idea: software development is not an art, or a bag of tricks Build software like we build bridges N. Kokash, Software Engineering 16 Software Engineering Definition Software Engineering is the application of a systematic, disciplined, quantifiable approach to the development, operation, and maintenance of software; that is, the application of engineering to software N. Kokash, Software Engineering 17 Software Engineering Famous software failures Military Mariner 1 rocket (1962) Cost: $18.5 million Soviet anti-missile warning system (1983) Patriot missile system (1991) 28 soldiers dead, 100 injured Medicine Therac-25 (1985) (3 dead, 3 critically injured) Radiation therapy software by Multidata Systems (2000) (8 dead, 20 critically injured) 18 N. Kokash, Software Engineering Software Engineering Famous software failures Finance Wall Street Crash (1987) caused by the NYSE computer system EDS Drops Child Support (2004) Cost: £540 million Airspace and flight control ARIANE 5, Flight 501 crash (1996) Cost: $500 million Mars Climate Orbiter crash (1998) Cost: $125 million 19 N. Kokash, Software Engineering Software Engineering ARIANE Flight 501 Disintegration after 39 sec Caused by wrong data being sent to On Board Computer Large correction for attitude deviation Software exception in Inertial Reference System after 36 sec. Overflow in conversion of a variable from 64-bit floating point to 16-bit signed integer Of 7 risky conversions, 4 were protected Reasoning: physically limited, or large margin of safety In case of exception: report failure and shut down N. Kokash, Software Engineering 20 Software Engineering Explanations Inadequate testing Wrong type of reuse Specification does not contain trajectory data In tests, components that measure altitude and movements of the launcher were simulated by software modules If a component works perfectly well in one environment, it doesn’t necessarily do so in another Ariane 5 is much faster than Ariane 4, and horizontal velocity builds up more rapidly excessive values for parameter in question This software doesn’t have any purpose for the Ariane 5, but was still kept Wrong design philosophy “If something breaks down, it is caused by a random hardware failure” Action: shut down that part There is no provision for design errors! N. Kokash, Software Engineering 21 Software Engineering Further information Ariane 5: IEEE Computer, January 1997, p. 129-130 http://www.cs.vu.nl/~hans/ariane5report.html 20 Famous Software Disasters http://www.devtopics.com/20-famous-software- disasters/ N. Kokash, Software Engineering 22 Software Engineering Is SE = Engineering? Software is logical, rather than physical Progress is hard to see (speed progress) Software is not continuous Further reading: Henry Petroski, Design Paradigms: Case Histories of Error and Judgement in Engineering A. Spector & D. Gifford, A Computer Science Perspective of Bridge Design, Communication of the ACM 29, 4 (1986) p 267-283 N. Kokash, Software Engineering 23 Software Engineering Quo Vadis? It takes at least 15-20 years for a technology to become mature Software engineering has made tremendous progress There is no silver bullet N. Kokash, Software Engineering 24 Software Engineering The CHAOS report 1994 1996 1998 2000 2002 2004 2006 2009 Successful 16% 27% 26% 28% 34% 29% 35% 32% Challenged 53% 33% 46% 49% 51% 53% 46% 44% Failed 31% 40% 28% 23% 15% 18% 19% 24% http://www.projectsmart.co.uk/docs/chaos-report.pdf N. Kokash, Software Engineering 25 Software Engineering Famous Engineering Disasters Tacoma Narrows bridge (1940) (1 dog dead) Hyatt Regency Hotel Walkway Collapse (1981) 114 dead, >200 injured 26 N. Kokash, Software Engineering Software Engineering Famous Engineering Disasters Chernobyl Nuclear Power Plant (1986) (at least 5000 dead, 336000 relocated) Air crashes: DC10-S (1979) (271 dead) Aloha Airlines Flight 243 (1988) (1 dead) 27 N. Kokash, Software Engineering Software Engineering Relative distribution of software/ hardware costs 100 Percent of total cost Hardware Development 60 Software 20 1955 N. Kokash, Software Engineering Maintenance 1970 Year 1985 28 Software Engineering Types of Software Custom For a specific customer Generic Sold on open market Often called COTS (Commercial Off The Shelf) Shrink-wrapped Embedded Built into hardware Hard to change N. Kokash, Software Engineering 29 Software Engineering Types of software Real time software E.g. control and monitoring systems Must react immediately Safety often a concern Business Information Systems Data processing Used to run businesses Accuracy and security of data are key N. Kokash, Software Engineering 30 Software Engineering Central themes LARGE programs COMPLEX programs Software EVOLVES Software COSTS Software is developed by TOGETHER by many people Software must EFFECTIVELY support users SE depends on knowledge transfer from DIFFERENT disciplines SE is about finding a BALANCE N. Kokash, Software Engineering 31 Software Engineering Simple life cycle model Problem requirements engineering Requirements specification design Design implementation System testing Working system maintenance N. Kokash, Software Engineering 32 Software Engineering Requirements Engineering Yields a description of the DESIRED system: which functions possible extensions required documentation performance requirements Includes a feasibility study Resulting document: requirements specification N. Kokash, Software Engineering 33 Software Engineering Design Earliest design decisions captured in software architecture Decomposition into parts/components; what are the functions of, and interfaces between, those components? Emphasis on what rather than how Resulting document: specification N. Kokash, Software Engineering 34 Software Engineering Implementation Focus on individual components Goal: a working, flexible, robust, … piece of software Not a bag of tricks Present-day languages have a module and/or class concept N. Kokash, Software Engineering 35 Software Engineering Testing Does the software do what it is supposed to do? Are we building the right system? (validation) Are we building the system right? (verification) Start testing activities in phase 1, on day 1 N. Kokash, Software Engineering 36 Software Engineering Maintenance Correcting errors found after the software has been delivered Adapting the software to changing requirements, changing environments, ... N. Kokash, Software Engineering 37 Software Engineering Global distribution of effort design 15% coding 20% requirements engineering 10% specification 10% testing 45% Rule of thumb: 40-20-40 distribution of effort Trend: enlarge requirements specification/design slots; reduce test slot Beware: maintenance alone consumes 5075% of total effort N. Kokash, Software Engineering 38 Software Engineering Distribution of maintenance activities corrective 21% perfective 50% adaptive 25% preventive 4% Corrective maintenance: correcting discovered errors Preventive maintenance: correcting latent errors Adaptive maintenance: adapting to changes in the environment Perfective maintenance: adapting to changing user requirements N. Kokash, Software Engineering 39 Software Engineering SE in a nutshell N. Kokash, Software Engineering 40 Software Engineering What does Software Engineer do? individually interacting with clients in a team Microsoft 1978 programming, documenting, planning, presenting, reviewing, reporting N. Kokash, Software Engineering listening, Specializing in different roles explaining, designing, programming, testing, proving feedback, brainstorming selling discussing planning 41 Software Engineering Hammurabi’s Code 64: If a builder builds a house for a man and does not make its construction firm, and the house which he has built collapses and causes the death of the owner of the house, that builder shall be put to death. … 73: If it cause the death of a son of the owner of the house, they shall put to death a son of that builder. N. Kokash, Software Engineering 42 Software Engineering Software Engineering Ethics Act consistently with the public interest Act in a manner that is in the best interest of the client and employer Ensure that products meet the highest professional standards possible Maintain integrity in professional judgment N. Kokash, Software Engineering Managers shall promote an ethical approach Advance the integrity and reputation of the profession Be fair to and supportive of colleagues Participate in lifelong learning and promote an ethical approach 43 Software Engineering A broader view on SD information planning boundary conditions documentation people input program software output program procedures 44 N. Kokash, Software Engineering Software Engineering Contents of project plan Introduction Process model Organization of project Standards, guidelines, procedures Management activities Risks Staffing Methods and techniques Work packages Resources Quality assurance Budget and schedule Changes Delivery 45 N. Kokash, Software Engineering Software Engineering Project control Time, both the number of man-months and the schedule Information, mostly the documentation Organization, people and team aspects Quality, not an add-on feature; it has to be built in Money, largely personnel 46 N. Kokash, Software Engineering Software Engineering Managing time Measuring progress is hard (“we spent half the money, so we must be halfway”) Development models serve to manage time More people less time? Brooks’ law: adding people to a late project makes it later 47 N. Kokash, Software Engineering Software Engineering Managing information Documentation Technical documentation Current state of projects Changes agree upon … Agile projects: less attention to explicit documentation, more on tacit knowledge held by people 48 N. Kokash, Software Engineering Software Engineering Managing people Managing expectations Building a team Coordination of work N. Kokash, Software Engineering 49 Software Engineering Managing quality Quality has to be designed in Quality is not an afterthought Quality requirements often conflict with each other Requires frequent interaction with stakeholders 50 N. Kokash, Software Engineering Software Engineering Managing cost Which factors influence cost? What influences productivity? Relation between cost and schedule N. Kokash, Software Engineering 51 Software Engineering Software Development Methods Projects are large and complex A phased approach to control it is necessary Traditional models are document-driven: there is a new pile of paper after each phase is completed Evolutionary models recognize that much of what is called maintenance is inevitable 52 N. Kokash, Software Engineering Software Engineering Waterfall model Iteration Feedback Validation Requirements eng. V&V we building the right system? Design V&V Are Verification Are we building the system right? Requirements are fixed as early as possible Implementation V&V Testing V&V Maintenance V&V 53 N. Kokash, Software Engineering Software Engineering V-model Requirements engineering Acceptance testing Integration testing Global design Detailed design Problems Unit testing Coding Too rigid Developers cannot move between various abstraction levels 54 N. Kokash, Software Engineering Software Engineering Evolutionary model Waterfall Model (Mid 70ies) Evolutionary Models (80ies) Time Requ. Eng. & Architecting Specification Design Implementation Test Increments (Spiral cycles) Iteration Scope N. Kokash, Software Engineering 55 Software Engineering Win-Win Spiral Model 2. Identify stakeholders objectives and win conditions / values 1. Identify next-increment stakeholders (Boehm, 1998) Emphasizes continuous stakeholder alignment 3. Reconcile win conditions Establish next-increment objectives, constraints & alternatives 4. Evaluate product and process alternatives Resolve risks 7. Verify & commit 6. Implement product & process definitions N. Kokash, Software Engineering 5. Define next-increment of product & process, inclusive partitions 56 Software Engineering Incremental development A software system is delivered in small increments The waterfall model is employed in each phase The user is closely involved in directing the next steps Incremental development prevents over-functionality 57 N. Kokash, Software Engineering Software Engineering Incremental development design build install increment 1 evaluate first incremental delivery design delivered system build install evaluate increment 2 second incremental delivery design build install evaluate third incremental delivery increment 3 Each component delivered must give some benefit to the stakeholders N. Kokash, Software Engineering 58 Software Engineering Velocity tracking Measure team productivity Unit of work – hours, days, story points, ideal days Interval – week, month N. Kokash, Software Engineering 59 Software Engineering Prototyping Requirements elicitation is difficult software is developed because the present situation is unsatisfactory however, the desirable new situation is as yet unknown Used to obtain the requirements of some aspects of the system Should be a relatively cheap process use rapid prototyping languages and tools not all functionality needs to be implemented production quality is not required 60 N. Kokash, Software Engineering Software Engineering Prototyping as a tool for SE Requirements engineering design design implementation implementation testing testing maintenance 61 N. Kokash, Software Engineering Software Engineering Prototyping approaches Throwaway prototyping: the n-th prototype is followed by a waterfall-like process Evolutionary prototyping: the n-th prototype is delivered 62 N. Kokash, Software Engineering Software Engineering Prototyping, advantages The resulting system is easier to use User needs are better accommodated The resulting system has fewer features Problems are detected earlier The design is of higher quality The resulting system is easier to maintain The development incurs less effort 63 N. Kokash, Software Engineering Software Engineering Prototyping, disadvantages The resulting system has more features The performance of the resulting system is worse The design is of less quality The resulting system is harder to maintain The prototyping approach requires more experienced team members 64 N. Kokash, Software Engineering Software Engineering Recommendations for prototyping The users and the designers must be well aware of the issues and the pitfalls Use prototyping when the requirements are unclear Prototyping needs to be planned and controlled as well 65 N. Kokash, Software Engineering Software Engineering The plan N. Kokash, Software Engineering 66 Software Engineering Reality N. Kokash, Software Engineering 67 Software Engineering Recent developments Rise of agile methods Shift from producing software to using software Software development becomes more heterogeneous Success of open source software N. Kokash, Software Engineering 68 Software Engineering The Agile Manifesto (2001) “We are uncovering better ways of developing software by doing it and helping others do it. Through this work we have come to value: Individuals and interactions over processes and tools Working software over comprehensive documentation Customer collaboration over contract negotiation Responding to change over following a plan That is, while there is value in the items on the right, we value the items on the left more.” . N. Kokash, Software Engineering 69 Software Engineering 12 principles of Agile SE: Customer satisfaction by rapid delivery of useful software Face-to-face conversation is the best form of communication (co-location) Welcome changing requirements, even late in development Projects are built around motivated individuals, who should be trusted Working software is delivered frequently (weeks rather than months) Continuous attention to technical excellence and good design Working software is the principal measure of progress Simplicity Sustainable development, able to maintain a constant pace Self-organizing teams Close, daily co-operation between business people and developers Regular adaptation to changing circumstances N. Kokash, Software Engineering 70 Software Engineering Popular agile methods Rapid Application Development (RAD) & Dynamic System Development Method (DSDM) Extreme Programming (XP) Feature Driven Development (FDD) Unified Processes: Agile Unified Process (AUP) Open Unified Process (OpenUP)/Basic Essential Unified Process (EssUP) Scrum 71 N. Kokash, Software Engineering Software Engineering RAD Evolutionary development, with time boxes: fixed time frames within which activities are done; Time frame is decided upon first, then one tries to realize as much as possible within that time frame; Other elements: Joint Requirements Planning (JRD) and Joint Application Design (JAD), workshops in which users participate; Requirements prioritization through a triage; Development in a SWAT team: Skilled Workers with Advanced Tools 72 N. Kokash, Software Engineering Software Engineering DSDM Dynamic Systems Development Method, #1 RAD framework in UK Fundamental idea: fix time and resources (timebox), adjust functionality accordingly One needs to be a member of the DSDM consortium 73 N. Kokash, Software Engineering Software Engineering DSDM phases Feasibility: delivers feasibility report and outline plan, optionally fast prototype (few weeks) Business study: analyze characteristics of business and technology (in workshops), delivers System Architecture Definition Functional model iteration: time-boxed iterative, incremental phase, yields requirements Design and build iteration Implementation: transfer to production environment 74 N. Kokash, Software Engineering Software Engineering DSDM practices Active user involvement is imperative Empowered teams Frequent delivery of products Acceptance determined by fitness for business purpose Iterative, incremental development All changes are reversible Requirements baselined at high level Testing integrated in life cycle Collaborative, cooperative approach shared by all stakeholders is essential 75 N. Kokash, Software Engineering Software Engineering Extreme Programming (XP) Everything is done in small steps The system always compiles, always runs Client as the center of development team Developers have same responsibility w.r.t. software and methodology 76 N. Kokash, Software Engineering Software Engineering 13 practices of XP Whole team: client part of the team Metaphor: common analogy for the system The planning game, based on user stories Test-driven development: tests developed first Design improvement (refactoring) Collective code ownership Simple design Small releases (e.g. 2 weeks) Customer tests Pair programming Continuous integration: system always runs Sustainable pace: no overtime Coding standards 77 N. Kokash, Software Engineering Software Engineering Differences Lightweight (Agile) Heavyweight Developers Knowledgeable, collocated, collaborative. Plan-driven, adequate skills, access to external knowledge. Customers Dedicated, knowledgeable, collocated, collaborative, representative, empowered Access to knowledgeable, collaborative, representative, empowered customers Requirements Largely emergent, rapid change Knowable early, largely stable Architecture Designed for current requirements Designed for current and foreseeable requirements Size Smaller teams and products Larger teams and products Primary objective Rapid value High assurance N. Kokash, Software Engineering 78 Software Engineering Heterogeneity Old days: Software development department had everything under control Nowadays: Teams scattered around the globe Components acquired from others Includes open source parts Services found on the Web N. Kokash, Software Engineering 79 Software Engineering Producing software means using software! Builders build pieces, integrators integrate them Component-Based Development (CBSD) Software Product Lines (SPL) Commercial Off-The-Shelves (COTS) Service Orientation (SOA) N. Kokash, Software Engineering 80 Software Engineering N. Kokash, Software Engineering Software engineering is a balancing act, where trade-offs are difficult Solutions are not right or wrong; at most they are better or worse Most of maintenance is (inevitable) evolution SD project control concerns: time, information, organization, quality, money There are many lifecycle models Agile projects do less planning than document-driven projects 81 Software Engineering Homework Which SE model is the most suitable for the assignment project and why? Write down your development plan Use RUP Software Development Plan template Read chapters 1,2 & 3.1-3.2 82 N. Kokash, Software Engineering Software Engineering Software Engineering (3rd Ed.) N. Kokash, Software Engineering 1. Introduction 2. Introduction to Software Engineering Management 3. The Software Life Cycle Revisited 4. Configuration Management 5. People Management and Team Organization 6. On Managing Software Quality 7. Cost Estimation 8. Project Planning and Control 9. Requirements Engineering 10. Modeling 11. Software Architecture 12. Software Design 13. Software Testing 14. Software Maintenance 17. Software Reusability 18. Component-Based Software Engineering 19. Service Orientation 20. Global Software Development 83