By by Mats Grindal.
ISBN-10: 9185715743
ISBN-13: 9789185715749
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Extra resources for Handling combinatorial explosion in software testing
Sample text
1 categorizes the five studies with respect to the employed research strategy and whether the chosen approach is quantitative or qualitative. The different parts of study S5 have different research methodologies and are thus indicated separately in the table. 1: Overview of research methodologies used in the studies. The following paragraphs discuss key methodological issues with respect to each of the conducted studies. Further details can be found in the corresponding papers. Study S1 Prior, informal observations of aspects of testing maturity aspects in several organizations indicate generally low testing maturity.
All three of the test generation tasks are difficult to automate. Identification of actual test case inputs can be automated but it requires that the function mapping IPM parameter values to actual inputs be formalized. Automation of the identification of the expected results may possibly be the most difficult task to automate. The reason is that the specification needs to be semantically exact and machine readable, that is, expressed in some formal language. Finally, automatic documentation of test cases requires code generation, which also requires semantically exact specifications.
Concept correctly used C2. No overlap of IPM Parameter Values C3. 3: Number of solutions (of 19) that satisfy different properties. boundary value analysis. Except for the three properties “semantic information indicated” (A2), “conflicts indicated” (A3), and “all aspects covered” (B2), the number of solutions satisfying the other properties vary around 15. The low results in inclusion of semantic and conflict information in the subjects’ solutions can be explained by the fact that the tutorial did not stress how test cases are generated by combination strategies.
Handling combinatorial explosion in software testing by by Mats Grindal.
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