Nov R McFadyen1 A Traditional Software Development Process Unit test Integration test System test Detailed design Architectural design Analysis Requirements analysis Business modeling process Business results

Nov R McFadyen2 Black Team Peopleware: Productive Projects and Teams by Tom Demarco and Timothy Lister Ch 19: The Black Team "legendary" Black Team at IBM in 60’s a particularly effective testing team the best testers at the company testers delighted in finding new ways to break software programmers dreaded having their software go through Black Team testing promoted themselves by dressing all in black the spirit of the Black Team has survived

Nov R McFadyen3 Testing Unit testing White-box testing Black-box testing

Nov R McFadyen4 White-box Testing Tests are derived from knowledge of the software’s construction aka structural, glass-box, or clear-box testing Tester analyzes the code, the algorithm, to derive tests

Nov R McFadyen5 Whitebox testing Tests are derived from knowledge of the software’s construction Path testing: A whitebox testing technique based on flow of control Construct a flow graph for Cyclomatic Complexity gives us the maximum number of tests necessary to cover all edges in the flow graph Design test cases such that each transition is traversed at least once - examine each condition and select an input for the true branch and another for the false branch Each test should contain an edge that is not contained in any other test

Nov R McFadyen6 White-box Testing Example FindMean(float Mean, FILE ScoreFile) …see next slide What is the flow graph for FindMean? What is the CC? What tests can we generate from the flowgraph/CC … to know all paths have been executed?

Nov R McFadyen7 /*Read in and sum the scores*/ White-box Testing Example FindMean(float Mean, FILE ScoreFile) { SumOfScores = 0.0; NumberOfScores = 0; Mean = 0; Read(ScoreFile, Score); while (! EOF(ScoreFile) { if ( Score > 0.0 ) { SumOfScores = SumOfScores + Score; NumberOfScores++; } Read(ScoreFile, Score); } /* Compute the mean and print the result */ if (NumberOfScores > 0 ) { Mean = SumOfScores/NumberOfScores; printf("The mean score is %f \n", Mean); } else printf("No scores found in file\n"); }

Nov R McFadyen8 Prepare for Flow Graph FindMean (FILE ScoreFile) { float SumOfScores = 0.0; int NumberOfScores = 0; float Mean=0.0; float Score; Read(ScoreFile, Score); while (! EOF(ScoreFile) { if (Score > 0.0 ) { SumOfScores = SumOfScores + Score; NumberOfScores++; } Read(ScoreFile, Score); } /* Compute the mean and print the result */ if (NumberOfScores > 0) { Mean = SumOfScores / NumberOfScores; printf(“ The mean score is %f\n”, Mean); } else printf (“No scores found in file\n”); }

Nov R McFadyen9 Constructing the Logic Flow Diagram CC = = 4 1, 2, 6, 8, 9 1, 2, 6, 7, 9 is not possible 1, 2, 3, 4, 5, 2, 6, 7, 9 1, 2, 3, 4, 5, 2, 6, 8, 9 is not possible 1, 2, 3, 5, 2, 6, 8, 9 1, 2, 3, 5, 2, 6, 7, 9 is not possible ok Note: If node 4 is included then node 7 must be included These 3 tests cover all paths! We didn’t need 4! Every line of code is tested!

Nov R McFadyen10 Constructing the Logic Flow Diagram CC = = 4 1, 2, 6, 8, 9 Test with no records in the file

Nov R McFadyen11 Constructing the Logic Flow Diagram CC = = 4 1, 2, 3, 4, 5, 2, 6, 7, 9 A test with one positive score

Nov R McFadyen12 Constructing the Logic Flow Diagram CC = = 4 1, 2, 3, 5, 2, 6, 8, 9 A test with one negative score

Nov R McFadyen13 Black-box Testing A blackbox test is one that focuses on the input/output behaviour of a component without considering its implementation The system being tested is a black box, whose behaviour is determined by studying its inputs and outputs aka functional testing since it is concerned with functionality and not implementation Can use equivalence classes and boundary conditions

Nov R McFadyen14 Equivalence class testing A technique to minimize the number of test cases An equivalence class is a set of tests with common characteristics A test case is selected for each class We use our domain knowledge to generate equivalence classes Example: suppose a method returns the number of days in a month, given the month and year. –When we consider months, we could arrive at 3 equivalence classes: months with 31 days months with 30 days months with 28 or 29 days –When we consider years, we have two equivalence classes: leap years and non-leap years –Combining, we have 6 equivalence classes

Nov R McFadyen15 Six equivalence classes Equivalence class Input values month year 31 day month, non-leap year day month, leap year day month, non-leap year day month, leap year /29 day month, non-leap year /29 day month, leap year

Nov R McFadyen16 Boundary class testing We focus on the boundary conditions of equivalence classes Rather than selecting any element in an equivalence class, boundary testing requires that elements be selected from the “edges” Example In general, years that are multiples of 4 are leap years; years that are multiples of 100 are not leap years, unless they are multiples of is a leap year, but 1900 is not For Year, 2000 and 1900 are good boundary cases 0 and 13 would be good boundary cases for month

Nov R McFadyen17 Ten testing classes Equivalence class Input values month year 31 day month, non-leap year day month, leap year day month, non-leap year day month, leap year /29 day month, non-leap year /29 day month, leap year Leap year divisible by Non-leap year divisible by Non-positive invalid month positive invalid month

Nov R McFadyen18 Example How would knowledge of the algorithm (the code) affect your choices of equivalence classes and boundary classes? First, suppose you are testing a search method. What equivalence and boundary test classes would you use? What are your black-box test classes? Next, suppose you learn the search is a binary search … how might this knowledge affect your set of test classes …

Nov R McFadyen19 Example (continued): Suppose we have a search module to test. We know: –the list, elt, must have at least one element –if the element, key, is found, found will be true and elt[L] = key –if the key is not found, found will be false How do we structure, or organize, our test cases?

Nov R McFadyen20 How do we structure, or organize, our test cases? We have two types of searches: successful and unsuccessful. So, we can partition our search test cases into two classifications: found and not found When it comes to lists of elements, we know that lists of length 1, are special cases or boundary points. So, we should have 2 partitions of lists: length 1, and length of more than one. When an element is searched for, it can be found in boundary positions. So, we can should have 3 partitions: found at the start, found at the end, and then we should include where it is found in the middle. Example (continued):

Nov R McFadyen21 FoundNot Found List of 1 element combining the partitions List of >1 element In 1st position In last position In middle position List of >1 element Example (continued):

Nov R McFadyen sample tests for the 6 partitions true, 1 55false, ? 55true, 1 44true, 6 77true, 3 99false, ? Outputs Found, L Inputs List Key Example (continued):

Nov R McFadyen23 Now, suppose we are examining the algorithm that searches an ordered list for a specific value in Key. On examination we see it’s a binary search and we see that it really treats the List as having 3 sections: elements < mid mid- point elements > mid Example (continued):

Nov R McFadyen24 :We can use this knowledge to further refine our partitioning - we need to test for where the Key we are looking for is at the boundary points for these partitions. elements < mid mid- point elements > mid We’ll add two more tests relating to the boundary points – finding a key just before, and just after the midpoint. (Could there be more that we should add related to not finding a key? What is the control flowgraph?) Example (continued):

Nov R McFadyen25 Example (continued) true, 1 55false, ? 55true, 1 50true, 4 76true, 7 44true, 3 Outputs Found, L Inputs List Key true, false, ?