White Box and Black Box Testing

1. White Box and Black BoxTesting Tor Stålhane

2. What is White Box testing White box testing is testing where we use the info available from the code of the component to generate tests. This info is usually used to achieve coverage in one way or another – e.g. • Code coverage • Path coverage • Decision coverage Debugging will always be white-box testing

3. Coverage report. Example – 1

4. Coverage report. Example – 2

5. McCabe’s cyclomatic complexity • Mathematically, the cyclomatic complexity of a structured programis defined with reference to a directed graph containing the basic blocks of the program, with an edge between two basic blocks if control may pass from the first to the second (the control flow graph of the program). The complexity is then defined as: • v(G) = E − N + 2P • v(G) = cyclomatic complexity • E = the number of edges of the graph • N = the number of nodes of the graph • P = the number of connected components

6. Graph example We have eight nodes – N = 8 – nine edges – E = 9 – and we have only one component – P = 1. Thus, we have v(G) = 9 – 8 + 2 = 3.

7. Simple case - 1 S1; IF P1 THEN S2 ELSE S3 S4; One predicate – P1. v(G) = 2 Two test cases can cover all code S1 P1 S2 S3 S4

8. Simple case – 2 S1; IF P1 THEN X := a/c ELSE S3; S4; One predicate – P1. v(G) = 2 Two test cases will cover all paths but not all cases. What about the case c = 0? S1 P1 a/c S3 S4

9. Statement coverage – 1 IF in_data > 10 {out_data = 4;} ELSE {out_data = 5;} IF out_data == 8 {update_panel();} How can we obtain full statement coverage? P1 S2 S1 P2 empty S3

10. Statement coverage – 2 out_data = 0 IF in_data > 10 {out_data = 4;} update_panel(); If we set in_data to 12 we will have full statement coverage. What is the problem?

11. Decision coverage IF (in_data > 10 OR sub_mode ==3) {out_data = 4;} ELSE {…..} P1 is really two decisions P1-1: in_data > 10 P1-2: sub_mode == 3 We need to cover both decisions P1 P1-1 P1-2 empty empty S1

12. Using v(G) The minimum number of paths through the code is v(G). As long as the code graph is a DAG – Directed Acyclic Graph – the maximum number of paths is 2**|{predicates}| Thus, we have that V(G) < number of paths < 2**|{predicates}|

13. Problem – the loop S1; DO IF P1 THEN S2 ELSE S3; S4 OD UNTIL P2 S5; No DAG. v(G) = 3 and Max is 4 but there is an “infinite” number of paths. S1 P1 S2 S3 S4 P2 S5

14. S1 P1 S3 S2 S4 P2 S5 S6 Nested decisions S1; IF P1 THEN S2 ELSE S3; IF P2 THEN S4 ELSE S5 FI S6; v(G) = 3, while Max = 4. Three test case will cover allpaths.

15. Using a decision table – 1 A decision table is a general technique used to achieve full path coverage. It will, however, in many cases, lead to over-testing. The idea is simple. • Make a table of all predicates. • Insert all combinations of True / False – 1 / 0 – for each predicate • Construct a test for each combination.

16. Using a decision table – 2

17. Using a decision table – 3 Three things to remember: The approach as it is presented here is only practical for • Situations where we have binary decisions. • Small chunks of code – e.g. class methods and small components. It will be too laborious for large chunks of code. Note that code that is difficult to reach – difficult to construct the necessary predicates – may not be needed as part of the system.

18. Decision table example – binary S1 P1 S3 S2 S4 P2 S5 S6 The last test is not necessary

19. Decision table example – tertiary S1 S2 S3 P1 P3 P2 S4 S5 S6 S7 S8 S10 S9

20. What about loops Loops are the great problem in white box testing. It is common practice to test the system going through each loop • 0 times – loop code never executed • 1 time – loop code executed once • 5 times – loop code executed several times • 20 times – loop code executed “many” times

21. Loop diagram for (i; P1; i++) {S1} The empty branch is taken when P1 is False P1 <<empty>> S1

22. Error messages Since we have access to the code we should • Identify all error conditions • Provoke each identified error condition • Check if the error is treated in a satisfactory manner – e.g. that the error message is clear, to the point and helpful for the intended users.

23. What is Black Box testing Black box testing is also called functional testing. The main ideas are simple: Define initial component state, input and expected output for the test. Set the component in the required state. Give the defined input Observe the output and compare to the expected output.

24. Info for Black Box testing That we do not have access to the code does not mean that one test is just as good as the other one. We should consider the following info: • Algorithm understanding • Parts of the solutions that are difficult to implement • Special – often seldom occurring – cases.

25. Clues from the algorithm We should consider two pieces of info: • Difficult parts of the algorithm used • Borders between different types of solution – e.g. if P1 then use S1 else use S2. Here we need to consider if the predicate is • Correct, i.e. contain the right variables • Complete, i.e. contains all necessary conditions

26. Black Box vs. White Box testing We can contrast the two methods as follows: • White Box testing • Understanding the implemented code. • Checking the implementation • Debugging • Black Box testing • Understanding the algorithm used. • Checking the solution – functional testing

27. Testing real time systems W-T. Tsai et al. have suggested a pattern based way of testing real time / embedded systems. They have introduced eight patterns. Using these they have shown through experiments that, using these eight patterns, they identified on the average 95% of all defects. We will have a look at three of the patterns. Together, these three patterns discovered 60% of all defects found

28. Patterns and coverage (from Tsai)

29. Basic scenario pattern - BSP PreCondition == true / {Set activation time} IsTimeout == true / [report fail] Check for precondition Check post-condition PostCondition == true / [report success]

30. BSP – example Requirement to be tested: If the alarm is disarmed using the remote controller, then the driver and passenger doors are unlocked. • Precondition: the alarm is disarmed using the remote controller • Post-condition: the driver and passenger doors are unlocked

31. BSP test • Generate input to make precondition • False => nothing happens • True => input activation time • Check system response • Timeout = true => fails • Timeout = false and post condition OK => OK • Timeout false and post condition not OK => fails

32. Key-event service pattern - KSP KeyEventOccurred / [SetActivationTime] Check precondition PreCondition == true Check for key event Check post-condition IsTimeout == true / [report fail] PostCondition == true / [report success]

33. KSP- example Requirement to be tested: When either of the doors are opened, if the ignition is turned on by car key, then the alarm horn beeps three times • Precondition: either of the doors are opened • Key-event: the ignition is turned on by car key • Post-condition: the alarm horn beeps three times

34. KSP test • Generate key event • Not right event => wait • Right event => set activation time • Check precondition • Not OK => wait • OK => check post condition • Check post condition • Timeout = true => fails • Timeout = false and post condition OK => OK • Timeout false and post condition not OK => fails

35. Timed key-event service pattern - TKSP KeyEventOccurred / [SetActivationTime] Check precondition PreCondition == true DurationExpired /[report not exercised] Check for key event Check post-condition IsTimeout == true / [report fail] PostCondition == true / [report success]

36. TKSP – example (1) Requirement to be tested: When driver and passenger doors remain unlocked, if within 0.5 seconds after the lock command is issued by remote controller or car key, then the alarm horn will beep once

37. TKSP – example (2) • Precondition: driver and passenger doors remain unlocked • Key-event: lock command is issued by remote controller or car key • Duration: 0.5 seconds • Post-condition: the alarm horn will beep once

38. TKSP test • Generate key event • Not right event => wait for new event or duration expired • Right event => set activation time • Check precondition • Not OK => wait • OK => check post condition • Check post condition • Timeout = true => fails • Timeout = false and post condition OK => OK • Timeout false and post condition not OK => fails

39. Test automation – 1

40. Test automation – 2 • Generate stimuli • Get necessary data • Collect events • Check events 1 2 3 4

41. Test automation example – BSP • Illegal command • Generate something • Nothing happens => test OKPost condition = “doors unlocked” => test fails • Legal command • Generate “alarm disabled” • Activation time = T • Timeout = True => test failsTimeout = falsepost condition = “doors unlocked” => test OK

42. Needs, models and methods – 1 If we say to the developers that they need to do e.g. unit testing this is just a statement of need, it is not a statement of how – the method to use. If we say that they should use white box testing, this helps a little, but there is still a lot of freedom when it comes to how.

43. Example – white box testing White box testing => • Static white box testing => • Code inspection • Code walkthrough • Dynamic white box testing => • Statement coverage • Path coverage • Decision coverage • All define – use coverage

44. Needs, models and methods – 2 We can use the following structure to organize the decisions: Strategy or need => Technique => Method This will be applicable on all levels, e.g. acceptance test, system test, integration tests and unit tests. For unit test we can for instance use: Unit test => White box test => Path coverage