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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Poulding, S. Feldt, R. |
| Copyright Year | 2015 |
| Description | Author affiliation: Software Eng. Res. Lab. (SERL Sweden), Blekinge Inst. of Technol., Karlshamn, Sweden (Poulding, S.; Feldt, R.) |
| Abstract | The efficiency of random testing can be improved by sampling test inputs using a generating program that incorporates knowledge about the types of input most likely to detect faults in the software-under-test (SUT). But when the input of the SUT is a complex data type--such as a domain-specific string, array, record, tree, or graph--creating such a generator may be time- consuming and may require the tester to have substantial prior experience of the domain. In this paper we propose the re-use of generators created for one SUT on other SUTs that take the same complex data type as input. The re-use of a generator in this way would have little overhead, and we hypothesise that the re-used generator will typically be as least as efficient as the most straightforward form of random testing: sampling test inputs from the uniform distribution. We investigate this proposal for two data types using five generators. We assess test efficiency against seven real-world SUTs, and in terms of both structural coverage and the detection of seeded faults. The results support the re-use of generators for complex data types, and suggest that if a library of generators is to be maintained for this purpose, it is possible to extend library generators to accommodate the specific testing requirements of newly-encountered SUTs. |
| Starting Page | 1 |
| Ending Page | 10 |
| File Size | 182146 |
| Page Count | 10 |
| File Format | |
| ISBN | 9781479971251 |
| DOI | 10.1109/ICST.2015.7102605 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-04-13 |
| Publisher Place | Austria |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Generators Libraries Probability distribution Data models Proposals Optimization Testing |
| Content Type | Text |
| Resource Type | Article |
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