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dc.contributor.advisorMichael D. Ernst.en_US
dc.contributor.authorGlasser, David Samuelen_US
dc.contributor.otherMassachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2009-06-30T16:54:43Z
dc.date.available2009-06-30T16:54:43Z
dc.date.copyright2007en_US
dc.date.issued2007en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/45982
dc.descriptionThesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.en_US
dc.descriptionIncludes bibliographical references (p. 95-98).en_US
dc.description.abstractAutomated unit tests are essential for the construction of reliable software, but writing them can be tedious. If the goal of test generation is to create a lasting unit test suite (and not just to optimize execution of system tests), it is essential that generated tests can be understood by the developers that will be running them, so that they can tell the difference between real and spurious failures. amock is a system which automatically generates human-readable JUnit regression tests that use mock objects to simulate the behavior of individual objects dynamically observed during a system test execution.en_US
dc.description.statementofresponsibilityby David Samuel Glasser.en_US
dc.format.extent98 p.en_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.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.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectElectrical Engineering and Computer Science.en_US
dc.titleTest factoring with amock: generating readable unit tests from system testsen_US
dc.typeThesisen_US
dc.description.degreeM.Eng.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.identifier.oclc335013675en_US


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