Lecture 4

1. Lecture 4 Process and Method: An Introduction to the Rational Unified Process

2. Traditional Structured Analysis Described by W. W. Royce, 1970, IEEE WESCON, Managing the development of large software systems. Decomposition in terms of Function and Data Modularity available only at the file level cf. C language's static keyword (=="file scope") Data was not encapsulated: Global Scope File Scope Function Scope (automatic, local) Waterfall Method of Analysis and Design

3. Waterfall Method Requirements Analysis Analysis Specification Design Specification Coding from Design Specification Unit Testing System Testing UAT Testing Ship It (????) Measuring rod is in the form of formal documents (specifications).

4. Waterfall Process Assumptions • Requirements are known up front before design • Requirements rarely change • Users know what they want, and rarely need visualization • Design can be conducted in a pure abstract space, or trial rarely leads to error • The technology will all fit nicely into place when the time comes (the apocalypse) • The system is not so complex. (Drawings are for wimps)

5. Structured Analysis Problems Reuse is complicated because Data is strewn throughout many different functions Reuse is usually defined as code reuse and is implemented through cutting and pasting of the same code in multiple places. What happens when the logic changes? coding changes need to be made in several different places changing the function often changes the API which breaks other functions dependent upon that API data type changes need to be made each time they are used throughout the application

6. Waterfall Process Limitations • Big Bang Delivery Theory • The proof of the concept is relegated to the very end of a long singular cycle. Before final integration, only documents have been produced. • Late deployment hides many lurking risks: • technological (well, I thought they would work together...) • conceptual (well, I thought that's what they wanted...) • personnel (took so long, half the team left) • User doesn't get to see anything real until the very end. • System Testing doesn't get involved until later in the process.

7. The Rational Unified Process • RUP is a method of managing OO Software Development • It can be viewed as a Software Development Framework which is extensible and features: • Iterative Development • Requirements Management • Component-Based Architectural Vision • Visual Modeling of Systems • Quality Management • Change Control Management

8. RUP Features • Online Repository of Process Information and Description in HTML format • Templates for all major artifacts, including: • RequisitePro templates (requirements tracking) • Word Templates for Use Cases • Project Templates for Project Management • Process Manuals describing key processes

9. The Phases

10. An Iterative Development Process... • Recognizes the reality of changing requirements • Capers Jones’s research on 8000 projects • 40% of final requirements arrived after the analysis phase, after development had already begun • Promotes early risk mitigation, by breaking down the system into mini-projects and focusing on the riskier elements first • Allows you to “plan a little, design a little, and code a little” • Encourages all participants, including testers, integrators, and technical writers to be involved earlier on • Allows the process itself to modulate with each iteration, allowing you to correct errors sooner and put into practice lessons learned in the prior iteration • Focuses on component architectures, not final big bang deployments

11. An Incremental Development Process... • Allows for software to evolve, not be produced in one huge effort • Allows software to improve, by giving enough time to the evolutionary process itself • Forces attention on stability, for only a stable foundation can support multiple additions • Allows the system (a small subset of it) to actually run much sooner than with other processes • Allows interim progress to continue through the stubbing of functionality • Allows for the management of risk, by exposing problems earlier on in the development process

12. Goals and Features of Each Iteration • The primary goal of each iteration is to slowly chip away at the risk facing the project, namely: • performance risks • integration risks (different vendors, tools, etc.) • conceptual risks (ferret out analysis and design flaws) • Perform a “miniwaterfall” project that ends with a delivery of something tangible in code, available for scrutiny by the interested parties, which produces validation or correctives • Each iteration is risk-driven • The result of a single iteration is an increment--an incremental improvement of the system, yielding an evolutionary approach

13. Risk Management • Identification of the risks • Iterative/Incremental Development • The prototype or pilot project • Booch’s “Tiger Team” • Early testing and deployment as opposed to late testing in traditional methods

14. The Development Phases • Inception Phase • Elaboration Phase • Construction Phase • Transition Phase

15. Inception Phase • Overriding goal is obtaining buy-in from all interested parties • Initial requirements capture • Cost Benefit Analysis • Initial Risk Analysis • Project scope definition • Defining a candidate architecture • Development of a disposable prototype • Initial Use Case Model (10% - 20% complete) • First pass at a Domain Model

16. Elaboration Phase • Requirements Analysis and Capture • Use Case Analysis • Use Case (80% written and reviewed by end of phase) • Use Case Model (80% done) • Scenarios • Sequence and Collaboration Diagrams • Class, Activity, Component, State Diagrams • Glossary (so users and developers can speak common vocabulary) • Domain Model • to understand the problem: the system’s requirements as they exist within the context of the problem domain • Risk Assessment Plan revised • Architecture Document

17. Construction Phase • Focus is on implementation of the design: • cumulative increase in functionality • greater depth of implementation (stubs fleshed out) • greater stability begins to appear • implement all details, not only those of central architectural value • analysis continues, but design and coding predominate

18. Transition Phase • The transition phase consists of the transfer of the system to the user community • It includes manufacturing, shipping, installation, training, technical support and maintenance • Development team begins to shrink • Control is moved to maintenance team • Alpha, Beta, and final releases • Software updates • Integration with existing systems (legacy, existing versions, etc.)

19. Elaboration Phase in Detail • Use Case Analysis • Find and understand 80% of architecturally significant use cases and actors • Prototype User Interfaces • Prioritize Use Cases within the Use Case Model • Detail the architecturally significant Use Cases (write and review them) • Prepare Domain Model of architecturally significant classes, and identify their responsibilities and central interfaces (View of Participating Classes)

20. Introduction to XP “When the tests all run, you’re done”

21. Options • XP is designed around the concept of options • Option to abandon • Option to switch • Option to defer • Option to grow and learn

22. The Four Variables • Management or the Customer chooses 3 of the four variables, the development team defines the fourth. • Cost • Cost is the amount of capital available, which defines resources. More resources don’t necessarily mean better quality or shorter time (remember Brooks?) • Time • The amount of time available for the project through delivery • Quality • Quality is the degree to which and aplomb with which functionality meets requirements • Scope • Scope is the amount of work to be done, the totality of the set of requirements. As requirements come and go, scope vacillates.

23. The Paradigm Shift • XP is based on the rejection of a fundamental and long-standing principle, that it costs less to make changes earlier in the development cycle rather than later. That the graph of cost to change is exponential across time. This fundamental principle has led to several strategies: • Better safe than sorry • Functional extravagance • Design extravagance • Proliferation of activities that may never provide a return on the investment

24. The Paradigm Shift Continued • The fundamental technical premise of XP is that the graph of cost to change is not exponential but digressive, and as time goes by, the cost to change is asymptotic. “You make the big decisions as late in the process as possible.” This has several strategies: • You implement only what you have to, and add functionality later only if necessary • Design is parsimonious • Thoreau’s principle: Simplify, Simplify, Simplify. • Automated tests • Refactoring • Learning to drive analogy • informality

25. The Four Values • Communication • Communication is bipartite. Developers need to communicate with customers as well as between themselves • Simplicity • “What’s the simplest thing that could possibly work?” Let’s do that. • Feedback • Continuous and instant feedback to all artifacts • Continuous and instant feedback to the project progression • Continuous and instant feedback to code • Courage • The courage to change (alter design, throw away code) • The courage to decide • The courage to do • The courage to be

26. The Basic Principles of XP • Rapid feedback • instant evaluation of all work and deliverables • Assume simplicity • 98% of problems can be solved with “ridiculous simplicity” • What happened to complexity? • Complexity != complex solutions • Incremental change • Avoid big changes, make smaller changes more often (driving analogy) • Embracing change • Might as well. Heraclitus was right, Parmenides was wrong. You simply will not be stepping into the same river twice. • Quality work • Work ethic • Is Beck a little too hopeful on the human condition?

27. Subordinate Principles • Teach learning • Small initial investment • Play to win • Concrete experiments • Open, honest communication • Work with people’s instincts, not against them • Accepted not foisted responsibility • Local adaptation (of process) • Travel light (the nomadic team) • Honest measurement (no lying)

28. The Four Basic Activities • Coding • Testing • Listening • Designing

29. Dominance of Coding and Testing • Code is unambiguous and constant. It offers no opinions. • Code is a another language for communication (as in pair programming) • Tests allow for a secondary view into the code, from another angle • Tests verify that “what was meant” was actually implemented • Tests can validate performance as well as functionality • You are responsible for writing multiple unit tests, you write a simple test for every possible way to “break” your code. • Automated tests can prolong the longevity of the code, and provide continuous validation. • A testing mentality promotes more self-assured programming style, as successful tests yield confidence in the code.

30. The Practices • Planning – quickly determine the scope of the next iteration. Customers do the planning based on feedback from the developers. • “Software development is always an evolving dialog between the possible and the desirable.” • Small Releases – take baby steps in each iteration. Rank iterations according to those which deliver the most valuable business requirements. • Metaphor – define a simple story of how the system will work. It should be enlightening. • Simple design – few classes and methods, no duplicated logic • Testing – Developers write unit tests, Customers write functional tests • Refactoring – revisiting code with rules that simplify the code. “When the system requires that you duplicate code, it’s asking for refactoring.” • Pair Programming • Collective Ownership – anyone can change any code at any time.

31. The Practices, cont. • Continuous Integration – code is integrated every half or full day at most. Integration is putting new code with the current system. • Sane work week • On-site customer – customer needs to be around • Coding standards that all coders follow

32. Pair Programming • One programmer writes the code, at the low level. He/she “has the ball”, or at least the keyboard. • The other programmer looks at the code being written from a higher strategic level: • What additional tests could break this? • Can this be done more simply? (designing) • Have I seen this before? (Refactoring) • Did the guy with the ball just introduce a bug? • Is this the best approach to this problem? • Did the guy with the ball forget something? • Does a question need to be answered by the Customer? • Coding standards help reduce the need for reformatting code and bickering about style. • Pairs write tests together too, following the same principles.

33. “Problems” With Pair Programming • What happens on a geographically distributed development team? • Management will object to “waste”, you only get half as much done, or we’ll need twice as many programmers. • Pairs will naturally “self-select” in a Darwinian sense, militating against teaching learning.

34. Project Planning • Three phases: • Exploration • Commitment • Steering

35. Exploration Phase • Write a story (think “simplified” Use Case) • Estimate a story: how long will it take to code this? • Split a story: if a part of a story is more important than another, split it into two stories

36. Commitment Phase • Business chooses the scope and delivery date of the next iteration • Four movements: • Sort by value (must have, should have, nice to have) • Sort by (estimation) risk • Set velocity – how quickly do we expect to move on this? • Choose Scope – Ok, given the above, what are we to deliver and when is it due?

37. Steering Phase • Four movements: • Iteration • Iterations run 1 to 3 weeks generally. • Each iteration selects one or more stories to implement. Each iteration must yield a system that runs end-to-end, however embryonically. • Recovery: if development has overstated velocity, re-evaluate the set of stories (deliverables) • New story: If business realizes it’s got a new story, the new story is estimated, ranked, and added. • Reestimate: If development feels the plan is inadequate, it can reestimate the remaining stories and reset the estimated velocity.

38. Iteration Planning • Task planning • Three Phases: • Exploration Phase • Write a task by breaking down the stories into tasks • Split a task if necessary • Commitment Phase • Accept a task • Estimate a task • Steering Phase • Implement a task • Record Progress • Recovery – what to do if overworked: manage scope • Verify story with functional tests

39. What about Design Strategy? • Start with a test. A simple test. • Design and implement just enough to get that test running, and make sure you don’t break another test. • Add functionality and repeat • Refactor. • “The definition of the best design is the simplest design that runs all the test cases.”

40. Use Case Analysis • What is a Use Case? • A sequence of actions a system performs that yields a valuable result for a particular actor. • What is an Actor? • A user or outside system that interacts with the system being designed in order to obtain some value from that interaction • Use Cases describe scenarios that describe the interaction between users of the system and the system itself. • Use Cases describe WHAT the system will do, but never HOW it will be done.

41. What’s in a Use Case? • Define the start state and any preconditions that accompany it • Define when the Use Case starts • Define the order of activity in the Main Flow of Events • Define any Alternative Flows of Events • Define any Exceptional Flows of Events • Define any Post Conditions and the end state • Mention any design issues as an appendix • Accompanying diagrams: State, Activity, Sequence Diagrams • View of Participating Objects (relevant Analysis Model Classes) • Logical View: A View of the Actors involved with this Use Case, and any Use Cases used or extended by this Use Case

42. Use Cases Describe Function not Form • Use Cases describe WHAT the system will do, but never HOW it will be done. • Use Cases are Analysis Products, not Design Products.

43. Use Cases Describe Function not Form • Use Cases describe WHAT the system should do, but never HOW it will be done • Use cases are Analysis products, not design products

44. Benefits of Use Cases • Use cases are the primary vehicle for requirements capture in RUP • Use cases are described using the language of the customer (language of the domain which is defined in the glossary) • Use cases provide a contractual delivery process (RUP is Use Case Driven) • Use cases provide an easily-understood communication mechanism • When requirements are traced, they make it difficult for requirements to fall through the cracks • Use cases provide a concise summary of what the system should do at an abstract (low modification cost) level.

45. Difficulties with Use Cases • As functional decompositions, it is often difficult to make the transition from functional description to object description to class design • Reuse at the class level can be hindered by each developer “taking a Use Case and running with it”. Since Ucs do not talk about classes, developers often wind up in a vacuum during object analysis, and can often wind up doing things their own way, making reuse difficult • Use Cases make stating non-functional requirements difficult (where do you say that X must execute at Y/sec?) • Testing functionality is straightforward, but unit testing the particular implementations and non-functional requirements is not obvious

46. Use Case Model Survey • The Use Case Model Survey is to illustrate, in graphical form, the universe of Use Cases that the system is contracted to deliver. • Each Use Case in the system appears in the Survey with a short description of its main function. • Participants: • Domain Expert • Architect • Analyst/Designer (Use Case author) • Testing Engineer

47. Sample Use Case Model Survey

48. Analysis Model • In Analysis, we analyze and refine the requirements described in the Use Cases in order to achieve a more precise view of the requirements, without being overwhelmed with the details • Again, the Analysis Model is still focusing on WHAT we’re going to do, not HOW we’re going to do it (Design Model). But what we’re going to do is drawn from the point of view of the developer, not from the point of view of the customer • Whereas Use Cases are described in the language of the customer, the Analysis Model is described in the language of the developer: • Boundary Classes • Entity Classes • Control Classes

49. Why spend time on the Analysis Model, why not just “face the cliff”? • By performing analysis, designers can inexpensively come to a better understanding of the requirements of the system • By providing such an abstract overview, newcomers can understand the overall architecture of the system efficiently, from a ‘bird’s eye view’, without having to get bogged down with implementation details. • The Analysis Model is a simple abstraction of what the system is going to do from the point of view of the developers. By “speaking the developer’s language”, comprehension is improved and by abstracting, simplicity is achieved • Nevertheless, the cost of maintaining the AM through construction is weighed against the value of having it all along.

50. Boundary Classes • Boundary classes are used in the Analysis Model to model interactions between the system and its actors (users or external systems) • Boundary classes are often implemented in some GUI format (dialogs, widgets, beans, etc.) • Boundary classes can often be abstractions of external APIs (in the case of an external system actor) • Every boundary class must be associated with at least one actor: