The DOI matches its Crossref record; 34 of the 34 references it cites were found in a registry or an index.
Dynamically discovering likely program invariants to support program evolution
Abstract
Explicitly stated program invariants can help programmers by identifying program properties that must be preserved when modifying code. In practice, however, these invariants are usually implicit. An alternative to expecting programmers to fully annotate code with invariants is to automatically infer likely invariants from the program itself. This research focuses on dynamic techniques for discovering invariants from execution traces. This article reports three results. First, it describes techniques for dynamically discovering invariants, along with an implementation, named Daikon, that embodies these techniques. Second, it reports on the application of Daikon to two sets of target programs. In programs from Gries's work (1981) on program derivation, the system rediscovered predefined invariants. In a C program lacking explicit invariants, the system discovered invariants that assisted a software evolution task. These experiments demonstrate that, at least for small programs, invariant inference is both accurate and useful. Third, it analyzes scalability issues, such as invariant detection runtime and accuracy, as functions of test suites and program points instrumented.
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Cites
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Wong, W. E., Gao, R., Li, Y., Abreu, R., & Wotawa, F. (2016) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2016.2521368 · Cited by 1,110
The oracle problem in software testing: A survey
Barr, E. T., Harman, M., McMinn, P., Shahbaz, M., & Yoo, S. (2015) · IEEE Transactions on Software Engineering · doi:10.1109/tse.2014.2372785 · Cited by 1,104
Evolutionary testing of classes
Tonella, P. (2004) · Proceedings of the 2004 ACM SIGSOFT international symposium on Software testing and analysis · doi:10.1145/1007512.1007528 · Cited by 410
SOBER: statistical model-based bug localization
Liu, C., Yan, X., Fei, L., Han, J., & Midkiff, S. P. (2005) · Proceedings of the 10th European software engineering conference held jointly with 13th ACM SIGSOFT international symposium on Foundations of software engineering · doi:10.1145/1081706.1081753 · Cited by 357
A Survey on Automated Log Analysis for Reliability Engineering
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Metadata
- Authors
- Ernst, M. D., Cockrell, J., Griswold, W. G., & Notkin, D.
- Venue
- IEEE Transactions on Software Engineering
- Published
- 2001-02
- Volume
- 27
- Issue
- 2
- Pages
- 99-123
- ISSN
- 0098-5589 (ISSN-L)
- 1939-3520
- 2326-3881
- OpenAlex
- W3106729728
- Cited by
- 1,050
- References
- 34
- FWCI
- 141.75
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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