ICS 52: Introduction to Software Engineering

1. ICS 52: Introduction to Software Engineering Lecture Notes for Summer Quarter, 2003 Michele Rousseau Topic 11 Partially based on lecture notes written by Sommerville, Frost, Van Der Hoek, Taylor & Tonne. Duplication of course material for any commercial purpose without the written permission of the lecturers is prohibited

2. Today’s Lecture • Quality assurance • An introduction to testing

3. ICS 52 Life Cycle Design phase Verify Requirements phase Verify Implementation phase Test Testing phase Verify

4. Implementation/Testing Interaction Implementation (previous lecture) Testing (this lecture)

5. The Seriousness of the problem… • Mars Pathfinder – Metric or English system • Audi 5000 – auto accelerate – feature or fault? • Mariner 1 launch – veered off course • AT&T telephone network - down for 9 hours • Ariane 5 • Pentium – FPU error • X-ray machine – over-radiation • LAS

6. Impact of Failures • Not just “out there” • Mars Pathfinder • Mariner 1 • Ariane 5 • But also “at home” • Your car • Your call to your mom • Your homework • Your hospital visit Peter Neumann’s Risks Forum: http://catless.ncl.ac.uk/Risks

7. Quality Assurance • What qualities do we want to assure? • Correctness (most important?) • How to assure correctness? • By running tests • How else? • Can qualities other than correctness be “assured” ? • How is testing done? • When is testing done? • Who tests? • What are the problems?

8. Software Qualities Correctness Reliability Robustness Performance Usability Verifiability Maintainability Repairability Safety Evolvability Reusability Portability Survivability Understandability We want to show relevant qualities exist

9. Quality Assurance • Assure that each of the software qualities is met • Goals set in requirements specification • Goals realized in implementation • Sometimes easy, sometimes difficult • Portability versus safety • Sometimes immediate, sometimes delayed • Understandability versus evolvability • Sometimes provable, sometimes doubtful • Size versus correctness

10. Verification and Validation • Verification “Are we building the product right?” (Boehm) • The Software should conform to its specification • testing, reviews, walk-throughs, inspections • internal consistency; consistency with previous step • Validation “Are we building the right product?” • The software should do what the user really requires • ascertaining software meets customer’s intent • Correctness has no meaning independent of specifications

11. Problem #1:Eliciting the Customer’s Intent Real needs Actual Specs “Correct” Specs No matter how sophisticated the QA process is, there is still the problem of creating the initial specification

12. Problem #2: QA is tough • Complex data communications • Electronic fund transfer • Distributed processing • Web search engine • Stringent performance objectives • Air traffic control system • Complex processing • Medical diagnosis system Sometimes, the software system is extremelycomplicated making it tremendously difficult to perform QA

13. Problem #3: Management Aspects of QA • Who does what part of the testing? • QA (Quality Assurance) team? • Are developers involved? • How independent is the independent testing group? • What happens when bugs are found? • What is the reward structure? Project Management ? QA Group Development Group ?

14. Problem #4: QA vs Developers • Quality assurance lays out the rules • You will check in your code every day • You will comment your code • You will… • Quality assurance also uncovers the faults • Taps developers on their fingers • Creates image of “competition” • Quality assurance is viewed as cumbersome • “Just let me code” • What about rewards? Quality assurance has a negative connotation

15. Problem #5: Can’t test exhaustively loop < 20x There are 1014 possible paths! If we execute one test per millisecond, it would take 3.170 years to test this program!!  Out of question

16. Simple Example: A 32-Bit Multiplier • Input: 2 32-bit integers • Output: the 64-bit product of the inputs • Testing hardware: checks one billion products per second (or roughly one check per 2-30 seconds) • How long to check all possible products? 2642-30 = 234 seconds  512 years • What if the implementation is based on table lookups? • How would you know that the spec is correct?

17. An Idealized View of QA Complete formal specsof problem to be solved Correctness-preserving transformation Design, in formal notation Correctness-preserving transformation Code, in verifiable language Correctness-preserving transformation executable machine code Correctness-preserving transformation Execution on verified hardware

18. A Realistic View of QA Mixture of formal and informal specifications Manual transformation Design, in mixed notation Manual transformation Code, in C++, Ada, Java, … Compilation by commercial compiler Pentium machine code Commercial firmware Execution on commercial hardware

19. The V & V process • Is a whole life-cycle process - V & V must be applied at each stage in the software process. • Has two principal objectives • The discovery of defects in a system • The assessment of whether or not the system is usable in an operational situation.

20. Static and dynamic verification • Software inspections Concerned with analysis of the static system representation to discover problems (static verification) • May be supplement by tool-based document and code analysis • Software testing Concerned with exercising and observing product behaviour (dynamic verification) • The system is executed with test data and its operational behaviour is observed

21. Static and dynamic V&V

22. V & V confidence • Depends on system’s purpose, user expectations and marketing environment • Software function • The level of confidence depends on how critical the software is to an organisation • User expectations • Users may have low expectations of certain kinds of software • Marketing environment • Getting a product to market early may be more important than finding defects in the program

23. V & V planning • Careful Planning is essential • Start Early – remember the V model • Perpetual Testing • Balance static verification and testing • Define standards for the testing process rather than describing product tests

24. Static Analysis • Software Inspection • Examine the source representation with the aim of discovering anomalies and defects • May be used before implementation • May be applied to any representation of the system (requirements, design, test data, etc.) • Very effective technique for discovering errors

25. Inspection success • Many different defects may be discovered in a single inspection. • In testing, one defect ,may mask another so several executions are required • They reuse domain and programming knowledge so reviewers are likely to have seen the types of error that commonly arise

26. Inspections and testing • Inspections and testing are complementary and not opposing verification techniques • Both should be used during the V & V process • Inspections can check conformance with a specification • Can’t check conformance with the customer’s real requirements • Cannot validate dynamic behaviour • Inspections cannot check non-functional characteristics such as performance, usability, etc.

27. Inspections and testing • Inspections and testing are complementary and not opposing verification techniques • Both should be used during the V & V process • Inspections can check conformance with a specification but not conformance with the customer’s real requirements • Inspections cannot check non-functional characteristics such as performance, usability, etc.

28. Testing • The only validation technique for non-functional requirements • Should be used in conjunction with static verification to provide full V&V coverage “Program testing can be used to show the presence of bugs, but never to show their absence.” — E. W. Dijkstra

29. What is Testing • Exercising a module, collection of modules, or system • Use predetermined inputs (“test case”) • Capture actual outputs • Compare actual outputs to expected outputs • Actual outputs equal to expected outputs  test case succeeds • Actual outputs unequal to expected outputs  test case fails

30. Limits of software testing • “Good” testing will find bugs • “Good” testing is based on requirements,i.e. testing tries to find differences between the expected and the observed behavior of systems or their components • V&Vshould establish confidence that the software is fit for purpose • BUT remember: Testing can only prove the presence of bugs - never their absence – can’t prove it is defect free • Rather, it must be good enough for its intended use and the type of use will determine the degree of confidence that is needed

31. Testing Terminology • Failure: Incorrect or unexpected output, based on specifications • Symptom of a fault • Fault: Invalid execution state • Symptom of an error • May or may not produce a failure • Error: Defect or anomaly or “bug” in source code • May or may not produce a fault

32. Testing and debugging • Defect testing & debugging –Different processes • V&V -establishes existence of defects in a program • Debugging – locate and repair

33. The debugging process

34. Testing Goals • Reveal failures/faults/errors • Locate failures/faults/errors • Show system correctness • Improve confidence that the system performs as specified (verification) • Improve confidence that the system performs as desired (validation) • Desired Qualities: • Accurate • Complete / thorough • Repeatable • Systematic

35. Test Tasks • Devise test cases • Target specific areas of the system • Create specific inputs • Create expected outputs • Choose test cases • Not all need to be run all the time • Regression testing • Run test cases • Can be labor intensive All in a systematic, repeatable, and accurate manner

36. Levels of Testing • Unit/component testing: testing of code unit (subprogram, class, method/function, small subsystem) • Often requires use of test drivers • Integration testing: testing of interfaces between units • Incremental or “big bang” approach? • Often requires drivers and stubs • System or acceptance testing: testing complete system for satisfaction of requirements • often performed by user / customer

37. What is the problem we need to address? • Want to verify software --> • Need to test --> • Need to decide on test cases --> • But, no set of test cases guarantees absence of bugs, • What is a systematic approach to the selection of test cases that will lead to the accurate, acceptably thorough, and repeatable identification of errors, faults, and failures? So,

38. Two Approaches • White box (or Glass Box) testing • Structural testing • Test cases designed, selected, and ran based on structure of the code • Scale: tests the nitty-gritty • Drawbacks: need access to source code • Black box testing • Specification-based testing • Test cases designed, selected, and ran based on specifications • Scale: tests the overall system behavior • Drawback: less systematic

39. Test Oracles • Provide a mechanism for deciding whether a test case execution succeeds or fails • Critical to testing • Used in white box testing • Used in black box testing • Difficult to automate • Typically relies on humans • Typically relies on human intuition • Formal specifications may help

40. Example • Your test shows cos(0.5) = 0.8775825619 • You have to decide whether this answer is correct? • You need an oracle • Draw a triangle and measure the sides • Look up cosine of 0.5 in a book • Compute the value using Taylor series expansion • Check the answer with your desk calculator

41. Use the Principles • Rigor and formality • Separation of concerns • Modularity • Abstraction • Anticipation of change • Generality • Incrementality