Overview

1. User Requirements PhaseDrawn from Sommerville(9th edition) Chapter 4 and S. Lauesen, (various sections) Software Requirements, Styles and Techniques, Addison Wesley, 2002

2. Overview • User requirements capture and analysis is an early phase of every lifecycle model. • Capture means finding out what the user wants … using different dialog techniques … and documenting this. • Analysis means studying the documented requirements for errors and technical consequences

3. Definition (IEEE) A requirement is: • A condition or capability needed by a user to solve a problem or achieve an objective • A condition or capability that must be met or possessed by a system or component to satisfy a contract, standard, specification, or other formally imposed document • A documented representation of 1 or 2.

4. Terminology • Product: the system to be delivered • Inner domain: product + surrounding work area, immediate users, their activities, other systems • Outer domain: customers, “second-level users”, AKA business domain • Product I/O • Domain I/O • Product-level requirements • Domain-level requirements • Actor: human or external system that communicates with the product • Stakeholder: people who ensure the success of the project. (Not the same as actors, why?)

5. Terminology Outer or Business Domain =? Business environment Actors Domain I/O Platform Product I/O Other systems Product Inner Domain =? company Stakeholders

6. Why do IT projects fail? • Annual CHAOS report (Standish Group) • Survey of over 10,000 IT projects since 1994 • Challenged: >190% of cost estimate • Failed: cancelled or never implemented • Succeeded: on time, to budget

7. CHAOS = chaos! • 31% of projects are challenged • 53% are failed • 16% succeed EU ESPITI survey (1996) identified 2 major issues • Poor requirements specification • Poor requirements management Let’s look more closely at underlying factors …

8. Success and Failure Factors (CHAOS) • Failure factors • Incomplete requirements • Lack of user involvement • Lack of resources • Challenged factors • Lack of user input • Incomplete requirements and specifications • Changing requirements and specifications • Success factors • User involvement • Executive management support • Clear statement of requirements

9. Cost Perspective • Davis 1994, summarised cost studies by IBM, HP etc. Relative cost of changing requirements at different phases in an IT project

10. Some Conclusions • Avoid requirements capture/analysis/management and we probably crash the project. • Requirements need to be debugged as soon as possible.

11. Requirements Types according to RUP • Rational Unified Process (RUP) • A methodology to support UML users • Three types of requirements: • Stakeholder requests • Features • Use cases

12. 1. Stakeholders Requests (STRQ) General requirements which describe the stakeholders needs on a high level. Normally elicited in the beginning of a development cycle by listening to stakeholders needs

13. 2. Features (FEAT) High level functionality that the system shall fulfill. Each feature should be derived from stakeholder requests and traceable back to them.

14. 3. Use Cases (UC) Express in a detailed way how users interact with the system. Use cases describe how to put and get information into and from the system. A use case should be derived from on or more features. Sufficient detail is needed to support later architectural and detailed design work.

15. Example • STRQ BUYPROD: The system shall offer functionality for buying products. • FEAT SEARCHNN: The user shall be able to search for a product via article name or number • UC SEARCHNN: • Step 1: User enters an article name or number • Step 2: User asks system to find product • Step 3: System presents product for user

16. Scale of Requirements(responsibility) Questions: 1: what can weactuallytake responsibility for? 2: what is the right level of requirement?

17. Typical URD Structure • Introduction: including business goals • Limits of the system: scope and interfaces • Data requirements: data model + dictionary • Product functional requirements: function lists, feature reqs, process descriptions • Quality requirements: non-functional Documentation standards: PSS-05, IEEE 830

18. Types of Requirements • Functional requirements: describe what the system does, in terms of input data, output date, error messages, etc. • E.g. a spreadsheet, a database, a word processor, 3D game, etc

19. Types of Requirements Non-Functional (AKA Quality) Requirements: • “everything else” • The product • The development process • The system environment • We can place these in a taxonomy (Sommerville) or checklist • See also: • McCall and Matsumoto (1980) • ISO 9126 • IEEE 830 (software requirements specifications)

20. Non-functional Product Organizational External Usability Reliability Portability legislative Efficiency delivery standards interoperability implementation speed memory ethical throughput privacy/ security safety commercial

21. Requirements Capture • An iterative dialog between • End-usersRequirements Analysts using a variety of tools and techniques

22. Why don’t we just ask the Customer? • Stakeholders may have difficulty expressing their needs, or may ask for a solution that doesn’t meet their needs. • Stakeholders can have conflicting demands • Users find it difficult to imagine new ways of doing things, or to imagine the consequences of what they ask for • A system that fulfills the requirements may not fulfill user expectations • Sometimes there are no users because a product is completely new • Demands and the environment change over time

23. Capture Techniques A good analyst: • knows many techniques, • knows when to use them and when not, • Combines and modifies techniques according to specific needs.

24. Techniques • Focus groups (structured) • Stakeholder analysis (small scale, who, what, why, risks, costs, solutions?) • (Group) interview (recorded, taped, filmed) • Observation (see also ethnography / immersive studies) • Task demo (“here’s how I usually …”) • Document studies (company info) • Questionnaires (large scale, capture statistics & opinions, open/closed questions) • Brainstorm (unstructured – anything goes) • Domain workshops (business process) • Design workshops (interface ideas) • Prototyping (product-level reqs., design-level reqs.) • Pilot experiments (COTS?) • Similar companies/ Related products • Ask suppliers (they know their customers)

25. Example: Organizing a Focus Group • Set the area of focus • Invite participants: 6-18 people, all stakeholders represented, max 30% are suppliers • Open the meeting: present the topic, let people get to know each other and relax • Bad experiences: roundtable discussion of past experiences with similar products or work domains. Record issues on whiteboard. Record ideas on whiteboard. Facilitator makes sure no one dominates. Supplier staff are low key

26. Focus Group (continued) 5. Imagine the Future: Invite ideas, invite speculation. Ask: why/when do you want this? Record ideas. 6. List the issues: edit on the fly, regroup and organize, combine similar. Record issues. 7. Prioritize issues: Each stakeholder group picks top ten – but don’t prioritize within these to avoid conflict. 8. Review the lists: roundtable comment, and close the meeting

27. Requirements Analysis and Validation • “Are we building the right product”? • i.e. will we build the product the customer truly wants to have? (at least at some point in time!) • Paradox: only the customer can determine this … but the customer is non-technical!

28. Requirements Analysis • Analysis involves several types of checks and tests that can be carried out: • Validity • Consistency • Completeness • Realism • Verifiability

29. Validity • Problem: User may have incorrectly defined a functional requirement. All requirements must be checked for functional correctness • Methods: • Rapid prototype • Paper model • Animation/simulation • Check existing/historic data • Test case generation • URD reviews • System User Manual

30. Consistency • Problem: User may state requirements that contradict each other (Common with many end-users!) • E.g. year + 1 > year year is a 2-digit number 99 + 1 = 00 > 99 contradiction! Simplified model of the “Year 2000 Problem”

31. Consistency • Methods: • If requirements are formal use constraint solvers and/or CASE tools for automatic check • Manual check, unclear, error prone, combinatorial explosion! • Note: problem may not be solved by prototyping

32. Completeness • Problem: user may have forgotten some requirements, leaving holes in the requirements document. These may possibly be solved arbitrarily … but possibly with conflicts(see inconsistency!) • Methods: • Rapid prototyping • URD reviews • Test case generation • Use cases analysis • Tables • Fault/ decision trees

33. Realism (Feasibility) • Problem: User may express requirements that are not technically feasible (e.g. performance) or violate some non-functional requirement (e.g. legislative) • Methods: • Prototyping • Mathematical model/simulation • (e.g Markov chain, queuing theory) • URD reviews • External advice (e.g. lawyers)

34. Verifiability • Problem: Users may state requirements which can never be checked/verified, • E.g. “user interface must be user friendly and easy to use” • Contractual disputes may emerge • Methods: • Test case generation esp. acceptance tests • Usability metrics

35. Numerical Quality Requirements

36. Usability = fit for use + ease of use The five (ease of) usability factors (Schneiderman 1998): • Ease of learning • Task efficiency • Ease of remembering • Subjective satisfaction • Understandability Some developers claim we cannot optimize all 5, if so … which to prioritize?

37. Usability Metrics

39. Security Requirements While other requirements support use-cases ... safety requirements prevent abuse-cases. Customer has certain assets to be protected against threats. We will examine security under risk management later …

40. Requirements Capture Languages • Requirements need to be recorded as precisely as possible, • Therefore technical requirements languages are useful • Large variety of these in many styles • We first consider styles: merits and demerits

41. Style: Natural Language + easily understood (esp. by end-user) + no technical training needed + very high-level/compact requirements • unclear/ ambiguous • debugging is difficult • no inherent structure • no tool support for validation (spell checker?)

42. Style: Structured Natural Language E.g. tables, decision trees, fault trees, data dictionaries + understood by end-user (sometimes) + small technical training + some structure (e.g. nouns, verbs, relations etc) + improve completeness issues • unclear/ ambiguous • lack of standards • little tool support

43. Tables: a structured style • Advocated by David Parnas • Informal but structured style • Easily understood by end-users • Many formats, e.g. nested tables • Good for completeness and consistency check • Good for business rules

44. Requirement x. The product shall suggest the following discount rates if a customer asks for a discount.

45. Style: Graphical Requirements Language e.g. UML, SDL, Petri Nets, etc + high-level/compact + quite or very precise + increasing tool support + often standardized / multiple vendors, courses, books, consultants • needs technical training • rarely understood by non-IT people and end-users

46. Style: Formal Specification Logic: e.g. OCL, JML, VDM, Z, B, temporal logic Ad-hoc: e.g. queuing theory, Markov chain + good tool support for validation problems + can be used to generate test cases, prove code correctness + extremely precise and accurate • Needs technical training • Poorly understood by end-users • Notation hard to read, overly detailed or low level

47. Data Modeling • Data models describe data inside and outside the product • Good for experts, maybe difficult for end-users • Early models can survive all the way to coding • Good for completeness/consistency checking Options • Class Diagram (OO analysis) • Entity-Relationship diagram (Database theory) • Data dictionary: terms and meanings • Data expression: format and legal values. Use regular expressions or DTDs.

48. Data Dictionary (aka Glossary) • A simple dictionary that defines nouns (data classes, data objects and actors). Usually alphabetical ordering for ease of use. • E.g. • Customer account : every user has a customer account containing name, address, history … • Address : an address has a name or number (obligatory), a street name (obligatory), an district name (optional) , a country name (obligatory), and a postcode (obligatory).

49. Regular Expressions • Regular expressions such as ab (cd)*(e I f )+ • Can be useful to define data and file formats. • Can define data filters to prevent file corruption • Can write exception handlers for bad data. • There are many “commercial” ways to define such expressions such as • BNF : Backus-Naur Format • DTD : XML Data Technical Definition • Finite automata