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Title:
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Theories in Practice: Easy-to-Write Specifications that Catch Bugs |
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Author:
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Saff, David; Boshernitsan, Marat; Ernst, Michael D. |
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Other Contributors:
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Program Analysis |
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Advisor:
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Michael Ernst |
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Issue Date:
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2008-01-14 |
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Abstract:
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Automated testing during development helps ensure that software works according to the test suite. Traditional test suites verify a few well-picked scenarios or example inputs. However, such example-based testing does not uncover errors in legal inputs that the test writer overlooked. We propose theory-based testing as an adjunct to example-based testing. A theory generalizes a (possibly infinite) set of example-based tests. A theory is an assertion that should be true for any data, and it can be exercised by human-chosen data or by automatic data generation. A theory is expressed in an ordinary programming language, it is easy for developers to use (often even easier than example-based testing), and it serves as a lightweight form of specification. Six case studies demonstrate the utility of theories that generalize existing tests to prevent bugs, clarify intentions, and reveal design problems. |
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URI:
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http://hdl.handle.net/1721.1/40090
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Other Identifiers:
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MIT-CSAIL-TR-2008-002 |
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Related To
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Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory
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Keywords:
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JUnit, testing, partial specification |
