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| Content Provider | ACM Digital Library |
|---|---|
| Author | Korel, Bogdan |
| Abstract | Test data generation in program testing is the process of identifying a set of test data that satisfies a selected testing criterion, such as, statement coverage or branch coverage. The existing methods of test data generation are limited to unit testing and may not efficiently generate test data for programs with procedures. In this paper we present an approach for automated test data generation for programs with procedures. This approach builds on the current theory of execution-oriented test data generation. In this approach, test data are derived based on the actual execution of the program under test. For many programs, the execution of the selected statement may require prior execution of some other statements that may be part of some procedures. The existing methods use only control flow information of a program during the search process and may not efficiently generate test data for these types of programs because they are not able to identify statements that affect execution of the selected statement. Our approach uses data dependence analysis to guide the process of test data generation. Data dependence analysis automatically identifies statements (or procedures) that affect the execution of the selected statement and this information is used to guide the search process. The initial experiments have shown that this approach may improve the chances of finding test data. |
| Starting Page | 209 |
| Ending Page | 215 |
| Page Count | 7 |
| File Format | |
| ISBN | 0897917871 |
| DOI | 10.1145/229000.226319 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 1996-05-01 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Content Type | Text |
| Resource Type | Article |
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