Software Testing Outsourcing Companies: Code Coverage-Based Methods
The code coverage based methods are really beneficial because they ensure that a chosen test set will preserve a required degree of coverage for <P> elements with respect to a criterion of structural coverage C used to create the initial set of tests. This does not mean that if the program’s attribute defined by C is covered by the original plurality of tests, it will be also covered with the selected set; in fact, the only guarantee is that % of the code coverage will be preserved. Code coverage based techniques reduce the spread over the coverage, requiring selection of tests which activate a hard-to-reach code, and withdrawal of tests that only duplicate coverage. Since in practice the code coverage criteria are typically used to select a single test for each element to be covered, approaches based on the code coverage can be regarded as specific kinds of minimization methods.
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Some of the techniques based on code coverage are data flow coverage techniques. These methods are more effective that minimization methods and nearly as effective as the safe methods. At the same time, they may require at least the same time for analysis as the most efficient safe methods and therefore may be more expensive than safe methods and be much more expensive than other minimization methods. They tend to include excessive tests in a set of regression tests to cover the definition-use chains depending on changes, which in some cases leads to a large number of selected tests. This fact has been proved experimentally.
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Data flaw based techniques may be useful for other tasks of regression testing apart from the selection of tests, for example, for finding < P> elements, insufficiently tested < T > elements.
Method with100 % coverage of the amended code is similar to the minimization method. Thus, for example, the table below shows 4 ways to select two tests in accordance with this criterion. It is not enough to run a single test. The results of comparing coverage-oriented selective regression-testing methods are given in Table 1:
|Completeness||From 0% до 100%||100%||< 100%||< 100%|
|Size of test set||Customized||Large||Small||Depends on the method parameters|
|Execution time of method||Very little time||Time consuming||Time consuming||Time consuming|
|Benefits of regression testing methods||Absence of tools to support regression testing||High quality requirements||Low cost of missing a defect||Set of original tests is developed based on the coverage criterion|
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