Directed random testing

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.

Bibliographic Details
Main Author: Pacheco, Carlos, Ph.D. Massachusetts Institute of Technology
Other Authors: Daniel N. Jackson.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2010
Subjects:
Online Access:http://hdl.handle.net/1721.1/53297
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author Pacheco, Carlos, Ph.D. Massachusetts Institute of Technology
author2 Daniel N. Jackson.
author_facet Daniel N. Jackson.
Pacheco, Carlos, Ph.D. Massachusetts Institute of Technology
author_sort Pacheco, Carlos, Ph.D. Massachusetts Institute of Technology
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description Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.
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spelling mit-1721.1/532972019-04-10T10:33:37Z Directed random testing Pacheco, Carlos, Ph.D. Massachusetts Institute of Technology Daniel N. Jackson. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009. Cataloged from PDF version of thesis. Includes bibliographical references (p. 155-162). Random testing can quickly generate many tests, is easy to implement, scales to large software applications, and reveals software errors. But it tends to generate many tests that are illegal or that exercise the same parts of the code as other tests, thus limiting its effectiveness. Directed random testing is a new approach to test generation that overcomes these limitations, by combining a bottom-up generation of tests with runtime guidance. A directed random test generator takes a collection of operations under test and generates new tests incrementally, by randomly selecting operations to apply and finding arguments from among previously-constructed tests. As soon as it generates a new test, the generator executes it, and the result determines whether the test is redundant, illegal, error-revealing, or useful for generating more tests. The technique outputs failing tests pointing to potential errors that should be corrected, and passing tests that can be used for regression testing. The thesis also contributes auxiliary techniques that post-process the generated tests, including a simplification technique that transforms a, failing test into a smaller one that better isolates the cause of failure, and a branch-directed test generation technique that aims to increase the code coverage achieved by the set of generated tests. Applied to 14 widely-used libraries (including the Java JDK and the core .NET framework libraries), directed random testing quickly reveals many serious, previously unknown errors in the libraries. And compared with other test generation tools (model checking, symbolic execution, and traditional random testing), it reveals more errors and achieves higher code coverage. (cont.) In an industrial case study, a test team at Microsoft using the technique discovered in fifteen hours of human effort as many errors as they typically discover in a person-year of effort using other testing methods. by Carlos Pacheco. Ph.D. 2010-03-25T15:27:51Z 2010-03-25T15:27:51Z 2009 2009 Thesis http://hdl.handle.net/1721.1/53297 549253406 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 165 p. application/pdf Massachusetts Institute of Technology
spellingShingle Electrical Engineering and Computer Science.
Pacheco, Carlos, Ph.D. Massachusetts Institute of Technology
Directed random testing
title Directed random testing
title_full Directed random testing
title_fullStr Directed random testing
title_full_unstemmed Directed random testing
title_short Directed random testing
title_sort directed random testing
topic Electrical Engineering and Computer Science.
url http://hdl.handle.net/1721.1/53297
work_keys_str_mv AT pachecocarlosphdmassachusettsinstituteoftechnology directedrandomtesting