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    Blackbox Blackbox Presentation Transcript

    • SOFTWARE QUALITY ASSURANCE BLACK BOX Seminar: Oana FEIDI Quality Manager – Continental Automotive
    • Preview
    • Preview
      • the problem …
          • very large or infinite number of test scenarios
          • +
          • finite amount of time
            • =
          • impossible to test everything
      • the solution …
          • Software test techniques exist to reduce the number of tests to be run whilst still providing sufficient coverage of the system under test
    • Overview
      • Black-box testing:
          • Test cases derived from specifications
          • The focus is not the design, nor the implementation
          • positive testing
            • -> testing the implementation against specified conditions
          • negative testing
            • -> testing the implementation against unspecified conditions ( unspecified inputs)
            • -> stability and robustness of specifications
      Input Output
    • Equivalence partition
      • create partitions of the input and output values of the component
      • each partition shall contain a set or range of values, chosen such that all values can reasonably expected to be treated by the component in the same way
      • both valid and invalid values are partitioned in this way
      • For each test case specify:
          • Input to the component
          • Partition exercised
          • The expected outcome of the test case
      • Test completeness criteria : test at least one input/output pair for each equivalence partition
      Indicates when to stop testing
    • Equivalence partition
      • Example:
          • f (int month) – want to test this function
          • … , -1, 0, 1, 2, 3, …., 9, 10, 11, 12, 13, 14, ….
          • ______||____________________||__________
          • invalid1 valid partition invalid2
          • f (int month, int nrdays) – want to test this function
          • 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12
          • ↑ ↑ ↑ ↑ ↑ ↑ ↑ ↑ ↑ ↑ ↑ ↑
          • 31 28/29 31 30 31 30 31 31 30 31 30 31
            • Valid partition: [(1, 3, 5, 7, 8, 10, 12; 31), (4, 6, 9, 11; 30), …]
            • Invalid partition: [(1, 2, 3, 5, 7, 8, 10, 12; 30), …]
    • Boundary Analysis
      • refinement of equivalence partitioning for which each edge of an equivalence class is a representative element of the class
      • invalid-input elements are found just beyond the ends
      • For each test case specify:
          • the input(s) to the component
          • the partition boundaries exercised
          • The expected outcome of the test case
      • Test completeness criteria: test at least one input/output pair for each equivalence partition and the “borders” between the equivalence partitions
    • Boundary Analysis
      • Example:
          • f (int month) – want to test this function
          • if (month > 0 && month < 13)
          • or
          • if (month >= 0 && month < 13)
          • … , -1, 0 , | 1 , 2, 3, …., 9, 10, 11, 12 | , 13 , 14, ….
            • |_________________________|
            • valid partition
      • Test: 0, 1, 12, 13
    • State Transition Testing
      • use a model of the states the component may occupy, transitions between those states, the events which cause those transitions, and the actions which may result from those transitions
      • the model shall comprise states, transitions, events, actions and their relationships
      • For each test case specify:
          • the starting state of the component
          • the input(s) to the component
          • the expected outputs from the component
          • the expected final state
      • Test completeness criteria: 100% of the state transition diagram
    • State Transition Testing start single being born married getting married widow husband dies remarried divorced remarried getting divorced dying death death death death reborn
    • Black Box - summary
      • Equivalence partition
          • create partitions of the input and output values of the component
          • each partition shall contain a set or range of values, chosen such that all values can reasonably expected to be treated by the component in the same way
          • both valid and invalid values are partitioned in this way
      • Boundary Analysis
          • refinement of equivalence partitioning for which each edge of an equivalence class is a representative element of the class
          • invalid-input elements are found just beyond the ends
      • State Transition Testing
          • use a model of the states the component may occupy, transitions between those states, the events which cause those transitions, and the actions which may result from those transitions
          • the model shall comprise states, transitions, events, actions and their relationships
    • Decision table
      • Decision Table
          • A decision table is a tabular form that presents a set of conditions and their corresponding actions.
      • Condition Stubs
          • Condition stubs describe the conditions or factors that will affect the decision or policy. They are listed in the upper section of the decision table.
      • Action Stubs
          • Action stubs describe, in the form of statements, the possible policy actions or decisions. They are listed in the lower section of the decision table.
      • Rules
          • Rules describe which actions are to be taken under a specific combination of conditions. They are specified by first inserting different combinations of condition attribute values and then putting X's in the appropriate columns of the action section of the table.
    • Decision Table Methodology 1. Identify Conditions & Values Find the data attribute each condition tests and all of the attribute's values. 2. Compute Max Number of Rules Multiply the number of values for each condition data attribute by each other. 3. Identify Possible Actions Determine each independent action to be taken for the decision or policy. 4. Enter All Possible Rules Fill in the values of the condition data attributes in each numbered rule column. 5. Define Actions for each Rule For each rule, mark the appropriate actions with an X in the decision table. 6. Verify the Policy Review completed decision table with end-users. 7. Simplify the Table Eliminate and/or consolidate rules to reduce the number of columns.
    • Example
      • A marketing company wishes to construct a decision table to decide how to treat clients according to three characteristics: Gender, City Dweller, and age group: A (under 30), B (between 30 and 60), C (over 60). The company has four products (W, X, Y and Z) to test market.
          • Product W will appeal to female city dwellers.
          • Product X will appeal to young females.
          • Product Y will appeal to Male middle aged shoppers who do not live in cities.
          • Product Z will appeal to all but older females.
    • Example
      • 1. Identify Conditions & Values
          • gender : M, F
          • city dweller : Y, N
          • age group : A, B, C
      • 2. Compute Maximum Number of Rules :
          • 2 x 2 x 3 = 12
      • 3. Identify Possible Actions :
          • market product W
          • market product X
          • market product Y
          • market product Z
    • Example
      • 4. Enter All Possible Rules
      • 5. Define Actions for each Rule
      1 2 3 4 5 6 7 8 9 10 11 12 Gender F M F M F M F M F M F M City Y Y N N Y Y N N Y Y N N Age A A A A B B B B C C C C 1 2 3 4 5 6 7 8 9 10 11 12 W X X X X X X Y X Z X X X X X X X X X X
    • Example
      • Simplify the Table
        • rules 2, 4, 6, 7, 10, 12 have the same action pattern
        • rules 2, 6 and 10 have two of the three condition values (gender and city dweller) identical and all three of the values of the non- identical value (age) are covered, so they can be condensed into a single column 2
        • The rules 4 and 12 have identical action pattern, but they cannot be combined because the indifferent attribute &quot;Age&quot; does not have all its values covered in these two columns. Age group B is missing
      Conditions Gen der F M F M F F M F F M City Y Y N N Y N N Y N N Age A - A A B B B C C C Actions W X X X X X X Y X Z X X X X X X X X 1 2 3 4 5 6 7 8 9 10
    • Conclusions
      • Advantages of Black Box Testing
          • more effective on larger units of code than glass box testing
          • tester needs no knowledge of implementation, including specific programming languages
          • tester and programmer are independent of each other
          • tests are done from a user's point of view
          • will help to expose any ambiguities or inconsistencies in the specifications
          • test cases can be designed as soon as the specifications are complete
    • Conclusions
      • Disadvantages of Black Box Testing
          • only a small number of possible inputs can actually be tested, to test every possible input stream would take nearly forever
          • without clear and concise specifications, test cases are hard to design
          • there may be unnecessary repetition of test inputs if the tester is not informed of test cases the programmer has already tried
          • may leave many program paths untested
          • cannot be directed toward specific segments of code which may be very complex (and therefore more error prone)
          • most testing related research has been directed toward glass box testing