Coward-p421 - A Review of Software Testing P David Coward...

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Unformatted text preview: A Review of Software Testing - P David Coward Reprinted: Information and Software Technology; Vol. 30, No. 3 April 1988 Software Engineering: The Development Process, Vol 1, Chapter 7 Presented By: Andrew Diemer Software Engineering II – EEL 6883 Aim of paper No guarantee that software meets functional requirements Introduces software testing techniques Needs Software is to be correct – What does this mean It often means the program matches the specifications. Problem with specification – Specification could be wrong Needs If this happens then the correctness is measured by the software meeting the user requirements Needs Testing – Why test Tests may have not been adequate enough Asses the performance of the tasks Terminology Verification –vs- Validation Verification – Ensures correctness from phase to phase of the software life cycle process – Formal proofs of correctness Terminology Validation – Checks software against requirements Executes software with test data Author uses testing and checking instead of verification and validation Categories of Testing Two categories of testing: – Functional – Non-functional Functional Testing Functional – Addresses to see if the program obtains the correct output It is normally used when testing a modified or new program Functional Testing Regression Testing – Tests following modification – Tests to see if the unchanging functions have indeed changed Non-functional Requirements Style Documentation standards Response times Legal obligations Situation testing Two situations testing can fall under: – Testing which finds faults in the software – Testing which does NOT find faults in the software Situation testing Finding faults – Destructive process more probing Not finding faults – miss inherent faults too gentle Questions How much testing is needed? Confidence in testing? Ignore faults? – Which ones are important? Are there more faults? What is the purpose of this testing? Testing Strategies Functional -vs- Structural Static -vs- Dynamic analysis Strategy starting points Specification – It makes known the required functions – Asses to see if they are provided – Functional testing Strategy starting points Software – Tests the structure of the system – Structural testing – Functions are included into the system but are NOT required – Example: accessing a database that has not been asked by the user Functional testing Identify the functions which the software is expected to perform Creating test data that will check to see if these functions are performed by the software Does NOT matter how the program performs these functions Functional testing Rules may be applied to uncover the functions Functional testing methods of formal documentation that includes descriptions of faults that correlate to each part of the design and the design features themselves Functional testing Isolation of these particular properties of each function should take place Fault class associations Black box approach Testers have an understanding of what the output should be Functional testing Oracle – An expert on what the outcome of a program will be for a particular test When might the oracle approach not work? – Simulation testing Only provides a “range of values” Structural testing Testing is based on the detailed design rather than the functions required by the program Structural testing Two approaches for this testing – First and most common is to execute the program with test cases – Second is symbolic execution Functions of the program are compared to the required functions for congruency Structural testing May require single path or percentage testing Research has been conducted to find out what the minimum amount of testing would be to ensure a degree of reliability Structural testing Measure of reliability – All statements should be executed at least once – All branches should be executed at least once – All linear code sequence and jumps in the program should be executed at least once Structural testing Measure of reliability (cont.) – Best approach would be the exhaustive approach in which every path is tested Structural testing Problems with the exhaustive approach – Extensive number of paths – Multiple combinations constitutes multiple conditions – Infeasible paths Contradictions of predicates at conditional statements Structural testing Path issues – There is a path for a loop not executing, executing once, and executing multiple of times – Control loops determine the number of paths Structural testing Path issues – Known as the “level-i” path or island code – Island code A series of lines of code, following a program termination, which is not the destination of a transfer control from somewhere else in the program Structural testing Path issues – When does island code occur? When failing to delete redundant code after maintenance Static analysis Does NOT involve execution of software with data but involves the use of constraints on the input and output data sets mathematically on software components Examples of static analysis would be program proving and symbolic execution Static analysis Symbolic execution – Use symbolic values for variables instead of numeric or string values Dynamic analysis Relies on program statements which make calls to analysis routines They record the frequency of execution of elements of the program Dynamic analysis Act as a liaison between functional and structural testing Test cases monitored dynamically, then structurally tested to see what idle code is left by previous tests Shows functions the program should perform Classification of Techniques There are three classifications: Static – Structural – – – – Symbolic execution Partition analysis Program proving Anomaly analysis Classification of Techniques Dynamic - Functional – – – – Domain testing Random testing Adaptive perturbation Cause-effect graphing Classification of Techniques Dynamic - Structural – Domain and computational testing – Automatic test data generation – Mutation analysis Classification of Techniques Dynamic - Structural – Domain and computational testing – Automatic test data generation – Mutation analysis Symbolic execution Non traditional approach – traditional is the execution requires that a selection of paths through a program is exercised by a set of test classes Produces a set of expressions, one per output variable Symbolic execution Usually a program executes using input data values with the output resulting in a set of actual values Use of flow-graphs – Each branch contains decision points (directed graph) – Branch predictions are produced Symbolic execution Use of top down approach During the top down traversal, the input variable is given a symbol in place of an actual value A problem is in the iterations As mentioned before, no executing loop, executing once, and then executing multiple times. Partition analysis Uses symbolic execution to find sub domains of the input domain Path conditions are used to find them Input domains that cannot be allocated to a sub domain infer a fault Partition analysis Specifications need to be written at a higher lever Program proving At the beginning and end of the procedure, place a mathematical method assertions Similar to symbolic execution Neither of them execute actual data and both examine source code Program proving Tries to come up with a proof that encompasses all possible iterations Program proving steps: – Construct a program – Examine the program and insert mathematical assertions at the beginning and end of procedures Program proving Program proving steps (cont): – Determine whether the code between each pair of start and end assertions will achieve the end assertion given the start assertion – If the code reaches the end assertion then the block has been proven Program proving DeMillo says that proofs can only be stated as acceptable and not correct His acceptance is determined by a gathering of people who cannot find fault with the proof Program proving The larger the audience, the more confidence in the software Total correctness means loops will terminate Anomaly analysis Two levels of anomalies: – made by the compiler (language syntax) – problems that are not necessarily wrong by the programming language Anomaly analysis Some anomalies are: – – – – – Unexecutable code Array boundaries Initializing variables wrong Unused labels and variables Traversing in and out of loops Anomaly analysis Produce flow-graphs Determine infeasible paths Some use data-flow analysis – Where the input values turn into intermediate, which then turn into output values Anomaly analysis Some data-flow anomalies: – Assigning values to variables which are not used – Using variables that have not been assigned previously to a value – Re-assigning of a variable without making use of a previous variable – Indicates possible faults Domain testing Based upon informal classifications of the requirements Test cases executed and compared against the expected to determine whether faults have been detected Random testing Produces data without reference to code or specification Random number generation is used Main problem is there is no complete coverage guarantee Random testing Key is to examine small subsets If followed it will give you a high branch coverage success rate Adaptive perturbation testing Concerns with assessing the effectiveness of sets of test cases Used to generate further test cases for effectiveness Adaptive perturbation testing Optimization is reached when routines find the best value to replace the discarded value so the number of assertions is maximized Process is replaced until the violated assertions are maximized to the limit Cause-effect graphing Power comes from the input combinations used by logic (AND, OR, NOT, etc) Cause-effect graphing Five steps: – Divide into workable pieces – Identify cause and effect – Represent a graph to link cause and effect semantics Cause-effect graphing Five steps (cont): – Annotate to show impossible combinations and effects – Convert the graph into a limitedentity decision table It helps identify small test cases Domain and computational testing Based upon selecting test cases Assignment statements are used for deciding computational paths Domain and computational testing Paths considered: – Path computation Set of algebraic expressions, one for each output variable, in terms of input variables and constraints – Path condition A joining of constraints of a path Domain and computational testing Paths considered (cont): – Path domain Set of input values that satisfy the path condition – Empty path Infeasible paths and cannot execute A path that follows errors is a computation error Automatic test data generation Courage comes with covering metrics Contradictory paths are infeasible Needs detailed specification to achieve this testing Formal specifications may provide fundamental help Mutation analysis Concerns the quality of sets of test data Uses the program to test the test data This means the original and mutant program are tested using the same test data Mutation analysis The two outputs are compared If the mutant output is different from the original output, then the mutant is of little value If the two outputs are the same, then the problem is there has been a change Mutation analysis The mutant is then said to be live Ratios are then taken (dead/alive) High ratio of live mutants equals poor test data If this happens then more tests need to be run until the ratio goes down Conclusion I thought this paper was thorough This paper gave good examples (compartmentalized) I thought this paper was a little out of date ...
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