Abstract
Automated random testing has shown to be an effective approach to finding faults but still faces a major unsolved issue: how to generate test inputs diverse enough to find many faults and find them quickly. Stateful testing, the automated testing technique introduced in this article, generates new test cases that improve an existing test suite. The generated test cases are designed to violate the dynamically inferred contracts (invariants) characterizing the existing test suite. As a consequence, they are in a good position to detect new faults, and also to improve the accuracy of the inferred contracts by discovering those that are unsound. Experiments on 13 data structure classes totalling over 28,000 lines of code demonstrate the effectiveness of stateful testing in improving over the results of long sessions of random testing: stateful testing found 68.4% new faults and improved the accuracy of automatically inferred contracts to over 99%, with just a 7% time overhead.
Original language | English |
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Title of host publication | 2011 26th IEEE/ACM International Conference on Automated Software Engineering, ASE 2011, Proceedings |
Pages | 440-443 |
Number of pages | 4 |
DOIs | |
Publication status | Published - 1 Dec 2011 |
Externally published | Yes |
Event | 2011 26th IEEE/ACM International Conference on Automated Software Engineering, ASE 2011 - Lawrence, KS, United States Duration: 6 Nov 2011 → 10 Nov 2011 |
Conference
Conference | 2011 26th IEEE/ACM International Conference on Automated Software Engineering, ASE 2011 |
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Country/Territory | United States |
City | Lawrence, KS |
Period | 6/11/11 → 10/11/11 |
Keywords
- automation
- dynamic analysis
- random testing
ASJC Scopus subject areas
- Software