Input Space Partitioning
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1 CMPT 473 Software Quality Assurance Input Space Partitioning Nick Sumner
2 Recall Testing involves running software and comparing observed behavior against expected behavior Select an input, look at the output 2
3 Recall Testing involves running software and comparing observed behavior against expected behavior Select an input, look at the output Problem: The input domain is infinite or pragmatically infinite. for test in allpossibleinputs: run_program(test) 3
4 Recall Testing involves running software and comparing observed behavior against expected behavior Select an input, look at the output Problem: The input domain is infinite or pragmatically infinite. Testing is about selecting a finite subset of inputs that can help measure quality 4
5 Input Space Partitioning Take the direct approach: Focus on the input! 5
6 Input Space Partitioning Input Space Partitioning Divide (partition) the set of possible inputs into equivalence classes 6
7 Input Space Partitioning Input Space Partitioning Divide (partition) the set of possible inputs into equivalence classes Test one input from each class 7
8 Input Space Partitioning Input Space Partitioning Divide (partition) the set of possible inputs into equivalence classes Test one input from each class e.g. abs(x) Input Domain:, -3, -2, -1, 0, 1, 2, 3,... How many tests if done exhaustively? 8
9 Input Space Partitioning Input Space Partitioning Divide (partition) the set of possible inputs into equivalence classes Test one input from each class e.g. abs(x) Input Domain: Partitions:, -3, -2, -1, 0, 1, 2, 3,..., -3, -2, -1, 0, 1, 2, 3,... What might reasonable partitions be? 9
10 Input Space Partitioning Input Space Partitioning Divide (partition) the set of possible inputs into equivalence classes Test one input from each class e.g. abs(x) Input Domain: Partitions:, -3, -2, -1, 0, 1, 2, 3,..., -3, -2, -1, 0, 1, 2, 3,... 10
11 Input Space Partitioning Input Space Partitioning Divide (partition) the set of possible inputs into equivalence classes Test one input from each class e.g. abs(x) Input Domain:, -3, -2, -1, 0, 1, 2, 3,... Partitions:, -3, -2, -1, 0, 1, 2, 3,... How many tests for the partitions? 11
12 Input Space Partitioning Input Space Partitioning Divide (partition) the set of possible inputs into equivalence classes Test one input from each class e.g. abs(x) Input Domain: Partitions:, -3, -2, -1, 0, 1, 2, 3,..., -3, -2, -1, 0, 1, 2, 3,... Impressive! How do we do it? 12
13 Input Space Partitioning 1) Identify the component 13
14 Input Space Partitioning 1) Identify the component Whole program Module Class Function 14
15 Input Space Partitioning 1) Identify the component Whole program Module Class Function 2) Identify the inputs What might the inputs be? 15
16 Input Space Partitioning 1) Identify the component Whole program Module Class Function 2) Identify the inputs Function/method parameters 16
17 Input Space Partitioning 1) Identify the component Whole program Module Class Function 2) Identify the inputs Function/method parameters Object state 17
18 Input Space Partitioning 1) Identify the component Whole program Module Class Function 2) Identify the inputs Function/method parameters Object state Global variables 18
19 Input Space Partitioning 1) Identify the component Whole program Module Class Function 2) Identify the inputs Function/method parameters Object state Global variables File contents 19
20 Input Space Partitioning 1) Identify the component Whole program Module Class Function 2) Identify the inputs Function/method parameters Object state Global variables File contents User provided inputs 20
21 Input Space Partitioning 1) Identify the component Whole program Module Class Function 2) Identify the inputs Function/method parameters Object state Global variables File contents User provided inputs 21
22 Input Space Partitioning 3) Develop an Input Domain Model 22
23 Input Space Partitioning 3) Develop an Input Domain Model A way of describing the possible inputs Partitioned by characteristics 23
24 Partitioned Input Domain Partition the domain D on characteristics D = A C B 24
25 Partitioned Input Domain Partition the domain D on characteristics What are characteristics? D = A C B 25
26 Partitioned Input Domain Partition the domain D on characteristics Must satisfy 2 criteria: Disjoint: A B C = Cover: A B C = D D = A C B 26
27 Partitioned Input Domain Partition the domain D on characteristics Must satisfy 2 criteria: Disjoint: A B C = Cover: A B C = D D = A C B What do these criteria intuitively provide? 27
28 Using Partitions Select one input from each block Each input in a block is assumed equally useful 28
29 Using Partitions Select one input from each block Each input in a block is assumed equally useful How? Identify characteristics of the possible inputs (from requirements, types, etc.) 29
30 Using Partitions Select one input from each block Each input in a block is assumed equally useful How? Identify characteristics of the possible inputs (from requirements, types, etc.) Partition into blocks based on each characteristic 30
31 Using Partitions Select one input from each block Each input in a block is assumed equally useful How? Identify characteristics of the possible inputs (from requirements, types, etc.) Partition into blocks based on each characteristic Create tests by selecting values for each block 31
32 Using Partitions Select one input from each block Each input in a block is assumed equally useful How? Identify characteristics of the possible inputs (from requirements, types, etc.) Partition into blocks based on each characteristic Create tests by selecting values for each block How many tests might this imply? Might there be more? Fewer? 32
33 Using Partitions Select one input from each block Each input in a block is assumed equally useful How? Identify characteristics of the possible inputs (from requirements, types, etc.) Partition into blocks based on each characteristic Create tests by selecting values for each block How many tests might this imply? Might there be more? Fewer? We're hiding some details in this last step. It's not quite right yet. 33
34 Using Partitions Select one input from each block Each input in a block is assumed equally useful How? Identify characteristics of the possible inputs (from requirements, types, etc.) Partition into blocks based on each characteristic Create tests by selecting values for each block Characteristics: List s is sorted ascending X is null String length... 34
35 Partitioning is Subtle Suppose we have: classifyparallelogram(p1) Characteristic: The subtype of parallelogram 35
36 Partitioning is Subtle Suppose we have: classifyparallelogram(p1) Characteristic: The subtype of parallelogram What are the types of parallelograms? 36
37 Partitioning is Subtle Suppose we have: classifyparallelogram(p1) Characteristic: The subtype of parallelogram How can we partition based on this characteristic? What problems might arise? 37
38 Partitioning is Subtle Suppose we have: classifyparallelogram(p1) Characteristic: The subtype of parallelogram How can we partition based on this characteristic? What problems might arise? In class exercise: Partitioning a triangle classifying program 38
39 Partitioning is Subtle Suppose we have: classifyparallelogram(p1) Characteristic: The subtype of parallelogram How can we partition based on this characteristic? What problems might arise? In class exercise: Partitioning a triangle classifying program It is easy to create overlapping partitions. Care and design required to avoid it. 39
40 Partitioning is Subtle Suppose we have: classifyparallelogram(p1) Characteristic: The subtype of parallelogram How can we partition based on this characteristic? What problems might arise? In class exercise: Partitioning a triangle classifying program It is easy to create overlapping partitions. Care and design required to avoid it. Why do disjoint partitions matter? 40
41 Process (Reiterated) 3 step process (for now): 1)Find the component / function to test methods, classes, programs, functions 41
42 Process (Reiterated) 3 step process (for now): 1)Find the component / function to test methods, classes, programs, functions 2) Find all test parameters Must identify everything locals, globals, files, databases, schedules, servers,... 42
43 Process (Reiterated) 3 step process (for now): 1)Find the component / function to test methods, classes, programs, functions 2) Find all test parameters Must identify everything locals, globals, files, databases, schedules, servers,... 3) Model the input domain Identify characteristics Partition the input domain Select values for each region 43
44 Process (Reiterated) 3 step process (for now): 1)Find the component / function to test methods, classes, programs, functions 2) Find all test parameters Must identify everything Domain knowledge, tactics, and creativity apply here. locals, globals, files, databases, schedules, servers,... 3) Model the input domain Identify characteristics Partition the input domain Select values for each region 44
45 Approaches to Input Modeling We still haven't talked about how to model input! 45
46 Approaches to Input Modeling 2 Main approaches: 46
47 Approaches to Input Modeling 2 Main approaches: 1)Interface based Guided directly by identified parameters & domains 47
48 Approaches to Input Modeling 2 Main approaches: 1)Interface based Guided directly by identified parameters & domains Simple Automatable 48
49 Approaches to Input Modeling 2 Main approaches: 1)Interface based Guided directly by identified parameters & domains Simple Automatable 2)Functionality/Requirements based Derived from expected input/output relationship by spec. 49
50 Approaches to Input Modeling 2 Main approaches: 1)Interface based Guided directly by identified parameters & domains Simple Automatable 2)Functionality/Requirements based Derived from expected input/output relationship by spec. Requires more design & more thought May be better (smaller, goal oriented, ) 50
51 Interface Based Modeling Consider parameters individually 51
52 Interface Based Modeling Consider parameters individually Examine their types/domains Ignore relationships & dependences 52
53 Interface Based Modeling Consider parameters individually Examine their types/domains Ignore relationships & dependences How does this apply to our triangle classifier? 53
54 Functionality Based Modeling Identify characteristics corresponding to behaviors/functionality in the requirements 54
55 Functionality Based Modeling Identify characteristics corresponding to behaviors/functionality in the requirements Includes knowledge from the problem domain 55
56 Functionality Based Modeling Identify characteristics corresponding to behaviors/functionality in the requirements Includes knowledge from the problem domain Accounts for relationships between parameters 56
57 Functionality Based Modeling Identify characteristics corresponding to behaviors/functionality in the requirements Includes knowledge from the problem domain Accounts for relationships between parameters Same parameter may appear in multiple characteristics Need to reason about constraints & conflicts! 57
58 Functionality Based Modeling Identify characteristics corresponding to behaviors/functionality in the requirements Includes knowledge from the problem domain Accounts for relationships between parameters Same parameter may appear in multiple characteristics Need to reason about constraints & conflicts! How might this apply to our triangle classifier? 58
59 Finding Typical Characteristics What might typical characteristics be? 59
60 Finding Typical Characteristics What might typical characteristics be? Preconditions Postconditions 60
61 Finding Typical Characteristics What might typical characteristics be? Preconditions Postconditions Invariants 61
62 Finding Typical Characteristics What might typical characteristics be? Preconditions Postconditions Relationships to special values Relationships between variables 62
63 Finding Typical Values How might you select values for a block? 63
64 Finding Typical Values How might you select values for a block? Expected values (e.g. exampled from spec) Invalid, valid, & special values Boundary values 64
65 Finding Typical Values How might you select values for a block? Expected values (e.g. exampled from spec) Invalid, valid, & special values Boundary values Thought experiment: What do boundary values as a selection approach indicate? 65
66 An Interface Based Example Consider our triangle classifier Takes 3 integers for sides 1, 2, & 3 66
67 An Interface Based Example Consider our triangle classifier Takes 3 integers for sides 1, 2, & 3 Characteristic b1 b2 b3 Side 1 <?> 0 Side 1 > 0 Side 1 = 0 Side 1 < 0 Side 2 <?> 0 Side 2 > 0 Side 2 = 0 Side 2 < 0 Side 3 <?>0 Side 3 > 0 Side 3 = 0 Side 3 < 0 67
68 An Interface Based Example Consider our triangle classifier Takes 3 integers for sides 1, 2, & 3 Characteristic b1 b2 b3 Side 1 <?> 0 Side 1 > 0 Side 1 = 0 Side 1 < 0 Side 2 <?> 0 Side 2 > 0 Side 2 = 0 Side 2 < 0 Side 3 <?>0 Side 3 > 0 Side 3 = 0 Side 3 < 0 How many tests does this create? 68
69 An Interface Based Example Consider our triangle classifier Takes 3 integers for sides 1, 2, & 3 Characteristic b1 b2 b3 Side 1 <?> 0 Side 1 > 0 Side 1 = 0 Side 1 < 0 Side 2 <?> 0 Side 2 > 0 Side 2 = 0 Side 2 < 0 Side 3 <?>0 Side 3 > 0 Side 3 = 0 Side 3 < 0 How many tests does this create? What will this test well? What won't this test well? 69
70 Refining the Example We can subdivide partitions to cover more behavior Characteristic b1 b2 b3 b4 Value of side 1 Side 1 > 1 Side 1 = 1 Side 1 = 0 Side 1 < 0 Value of side 2 Side 2 > 1 Side 2 = 1 Side 2 = 0 Side 2 < 0 Value of side 3 Side 3 > 1 Side 3 = 1 Side 3 = 0 Side 3 < 0 {Side n > 0} {Side n = 1},{ Side n > 1} 70
71 Refining the Example We can subdivide partitions to cover more behavior Characteristic b1 b2 b3 b4 Value of side 1 Side 1 > 1 Side 1 = 1 Side 1 = 0 Side 1 < 0 Value of side 2 Side 2 > 1 Side 2 = 1 Side 2 = 0 Side 2 < 0 Value of side 3 Side 3 > 1 Side 3 = 1 Side 3 = 0 Side 3 < 0 How many tests now? 71
72 Refining the Example We can subdivide partitions to cover more behavior Characteristic b1 b2 b3 b4 Value of side 1 Side 1 > 1 Side 1 = 1 Side 1 = 0 Side 1 < 0 Value of side 2 Side 2 > 1 Side 2 = 1 Side 2 = 0 Side 2 < 0 Value of side 3 Side 3 > 1 Side 3 = 1 Side 3 = 0 Side 3 < 0 How many tests now? Is it still disjoint? Complete? 72
73 Refining the Example We can subdivide partitions to cover more behavior Characteristic b1 b2 b3 b4 Value of side 1 Side 1 > 1 Side 1 = 1 Side 1 = 0 Side 1 < 0 Value of side 2 Side 2 > 1 Side 2 = 1 Side 2 = 0 Side 2 < 0 Value of side 3 Side 3 > 1 Side 3 = 1 Side 3 = 0 Side 3 < 0 How many tests now? Is it still disjoint? Complete? What does it test well? Not well? 73
74 A Functionality Based Example Consider our triangle classifier again What might our characteristics & partitions be? 74
75 A Functionality Based Example Consider our triangle classifier again What might our characteristics & partitions be? Are there alternatives? 75
76 A Functionality Based Example Consider our triangle classifier again What might our characteristics & partitions be? Are there alternatives? Why might you use them? 76
77 A Classic Example Start with a component / specification: Command Syntax Function FIND FIND <pattern> <file> The FIND command is used to locate one or more instances of a given pattern in a text file. All lines in the file that contain the pattern are written to standard output. A line containing the pattern is written only once, regardless of the number of times the pattern occurs on it. The pattern is any sequence of characters whose length does not exceed the maximum length of a line in the file. To include a blank in the pattern, the entire pattern must be enclosed in quotes ("). To include a quotation mark in the pattern, two quotes in a row ("") must be used. 77
78 A Classic Example Step 1: Analyze the specification What is the component? What are the parameters? What are the characteristics? 78
79 A Classic Example Step 1: Analyze the specification What Parameters: is the component? What are Pattern the parameters? Input file (& its contents!) What are the characteristics? 79
80 A Classic Example Step 1: Analyze the specification What Parameters: is the component? What are Pattern the parameters? Input file (& its contents!) What are the characteristics? Characteristics: Pattern Input file Pattern Size Quoting Embedded Quotes File Name Environment / System Characteristics: # of pattern occurrences in file # of occurrences on a particular line: 80
81 A Classic Example Step 2: Partition the Input Space Guided by intelligence and intuition Combine interface and functionality based approaches as necessary 81
82 A Classic Example Step 2: Partition the Input Space Guided by intelligence and intuition Combine interface and functionality based approaches as necessary Parameters: Pattern Size: Empty Single character Many characters Longer than any line in the file Quoting:... 82
83 A Classic Example Familiar Idea: Select one block per characteristic at a time Combine into test frames (test case plans) e.g. 83
84 A Classic Example Familiar Idea: Select one block per characteristic at a time Combine into test frames (test case plans) e.g. Pattern size : empty Quoting : pattern is quoted Embedded blanks : several embedded blanks Embedded quotes : no embedded quotes File name : good file name Number of occurrences of pattern in file : none Pattern occurrences on target line : one 84
85 A Classic Example Familiar Idea: Select one block per characteristic at a time Combine into test frames (test case plans) e.g. Problem? Pattern size : empty Quoting : pattern is quoted Embedded blanks : several embedded blanks Embedded quotes : no embedded quotes File name : good file name Number of occurrences of pattern in file : none Pattern occurrences on target line : one 85
86 A Classic Example Familiar Idea: Select one block per characteristic at a time Combine into test frames (test case plans) e.g. Problem? Pattern size : empty Quoting : pattern is quoted Embedded blanks : several embedded blanks Embedded quotes : no embedded quotes File name : good file name Number of occurrences of pattern in file : none Pattern occurrences on target line : one 86
87 A Classic Example Step 3: Identify constraints among the characteristics & blocks Pattern Size: Empty [Property Empty] Single character [Property NonEmpty] Many characters [Property NonEmpty] Longer than any line in the file [Property NonEmpty] 87
88 A Classic Example Step 3: Identify constraints among the characteristics & blocks Pattern Size: Empty [Property Empty] Single character [Property NonEmpty] Many characters [Property NonEmpty] Longer than any line in the file [Property NonEmpty] Quoting: Pattern is quoted Pattern is not quoted Pattern is improperly quoted [Property Quoted] [If NonEmpty] [If NonEmpty] 88
89 A Classic Example Step 3: Identify constraints among the characteristics & blocks Pattern Size: Empty [Property Empty] Single character [Property NonEmpty] Many characters [Property NonEmpty] Longer than any line in the file [Property NonEmpty] Quoting: Pattern is quoted Pattern is not quoted Pattern is improperly quoted [Property Quoted] [If NonEmpty] [If NonEmpty] What should this do to the number of tests? To the quality of tests? 89
90 A Classic Example Step 4 Create tests by selecting values that satisfy the selected blocks for each frame Eliminate tests that cover redundant scenarios 90
91 A Classic Example Step 4 Create tests by selecting values that satisfy the selected blocks for each frame Eliminate tests that cover redundant scenarios Why might scenarios be redundant? 91
92 A Classic Example Step 5: Take your generated test cases and automate them 92
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