Graduate Project

 

Feedback-Based Random Test Generator for TSTL Public Deposited

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https://ir.library.oregonstate.edu/concern/graduate_projects/bk128c53k

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  • Software testing is the process of evaluating the accuracy and performance of software, and automated software testing allows programmers to develop software more efficiently by decreasing testing costs. We compared two advanced random test generators, a Feedback-Directed Random Test Generator (FDR) and a Feedback-Controlled Random Test Generator (FCR), for an automated software testing tool in Python 2.x, the Template Scripting Testing Language (TSTL). An FDR generates test inputs incrementally. Feedback from previous trials is used to generate new inputs. As each test input is executed, the software properties are assessed to determine if there is any value. Because of this process of gradually generating new tests, the FDR avoids redundant and illegal test inputs commonly produced by traditional random test generators. An FCR employs a different feedback technique. It controls the feedback to produce varied test inputs using multiple input containers. In our experiments, we compared the performance of our test generators with TSTL’s generator in terms of coverage, time-efficiency, and error-detection capability.
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  • description.provenance : Approved for entry into archive by Steven Van Tuyl(steve.vantuyl@oregonstate.edu) on 2017-03-30T16:12:15Z (GMT) No. of bitstreams: 2license_rdf: 1536 bytes, checksum: df76b173e7954a20718100d078b240a8 (MD5)project_paper.pdf: 523496 bytes, checksum: 7369f807d0e7c1a061fbf7b2a25b240b (MD5)
  • description.provenance : Made available in DSpace on 2017-03-30T16:12:15Z (GMT). No. of bitstreams: 2license_rdf: 1536 bytes, checksum: df76b173e7954a20718100d078b240a8 (MD5)project_paper.pdf: 523496 bytes, checksum: 7369f807d0e7c1a061fbf7b2a25b240b (MD5)
  • description.provenance : Submitted by Kazuki Kaneoka (kaneokak@oregonstate.edu) on 2017-03-23T20:14:39ZNo. of bitstreams: 2license_rdf: 1536 bytes, checksum: df76b173e7954a20718100d078b240a8 (MD5)project_paper.pdf: 523496 bytes, checksum: 7369f807d0e7c1a061fbf7b2a25b240b (MD5)

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