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Test case prioritization.

Malishevsky, Alexey Grigorievich.

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Test case prioritization.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Test case prioritization./
作者:	Malishevsky, Alexey Grigorievich.
面頁冊數:	272 p.
附註:	Source: Dissertation Abstracts International, Volume: 64-10, Section: B, page: 5040.
Contained By:	Dissertation Abstracts International64-10B.
標題:	Computer Science. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3107736

Test case prioritization.
Malishevsky, Alexey Grigorievich.

Test case prioritization. - 272 p.

Source: Dissertation Abstracts International, Volume: 64-10, Section: B, page: 5040.

Thesis (Ph.D.)--Oregon State University, 2004.

Regression testing is an expensive software engineering activity intended to provide confidence that modifications to a software system have not introduced faults. Test case prioritization techniques help to reduce regression testing cost by ordering test cases in a way that better achieves testing objectives. In this thesis, we are interested in prioritizing to maximize a test suite's rate of fault detection, measured by a metric, APFD, trying to detect regression faults as early as possible during testing.Subjects--Topical Terms:

626642
Computer Science.

Test case prioritization.
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500 $a Source: Dissertation Abstracts International, Volume: 64-10, Section: B, page: 5040.
500 $a Adviser: Gregg E. Rothermel.
502 $a Thesis (Ph.D.)--Oregon State University, 2004.
520 $a Regression testing is an expensive software engineering activity intended to provide confidence that modifications to a software system have not introduced faults. Test case prioritization techniques help to reduce regression testing cost by ordering test cases in a way that better achieves testing objectives. In this thesis, we are interested in prioritizing to maximize a test suite's rate of fault detection, measured by a metric, APFD, trying to detect regression faults as early as possible during testing.
520 $a In previous work, several prioritization techniques using low-level code coverage information had been developed. These techniques try to maximize APFD over a sequence of software releases, not targeting a particular release. These techniques' effectiveness was empirically evaluated.
520 $a We present a larger set of prioritization techniques that use information at arbitrary granularity levels and incorporate modification information, targeting prioritization at a particular software release. Our empirical studies show significant improvements in the rate of fault detection over randomly ordered test suites.
520 $a Previous work on prioritization assumed uniform test costs and fault severities, which might not be realistic in many practical cases. We present a new cost-cognizant metric, APFDC, and prioritization techniques, together with approaches for measuring and estimating these costs. Our empirical studies evaluate prioritization in a cost-cognizant environment.
520 $a Prioritization techniques have been developed independently with little consideration of their similarities. We present a general prioritization framework that allows us to express existing prioritization techniques by a framework algorithm using parameters and specific functions.
520 $a Previous research assumed that prioritization was always beneficial if it improves the APFD metric. We introduce a prioritization cost-benefit model that more accurately captures relevant cost and benefit factors, and allows practitioners to assess whether it is economical to employ prioritization.
520 $a Prioritization effectiveness varies across programs, versions, and test suites. We empirically investigate several of these factors on substantial software systems and present a classification-tree-based predictor that can help select the most appropriate prioritization technique in advance.
520 $a Together, these results improve our understanding of test case prioritization and of the processes by which it is performed.
590 $a School code: 0172.
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