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Prioritizing test cases for regression testing
Author(s) -
Sebastian Elbaum,
Alexey Malishevsky,
Gregg Rothermel
Publication year - 2000
Publication title -
digital commons - university of nebraska lincoln (university of nebraska–lincoln)
Language(s) - English
Resource type - Conference proceedings
ISBN - 1-58113-266-2
DOI - 10.1145/347324.348910
Subject(s) - regression testing , prioritization , granularity , computer science , reliability engineering , fault detection and isolation , schedule , fault (geology) , process (computing) , test case , test (biology) , measure (data warehouse) , data mining , software , machine learning , regression analysis , artificial intelligence , software system , engineering , software construction , paleontology , management science , seismology , actuator , biology , programming language , geology , operating system
Test case prioritization techniques schedule test cases in an order that increases their effectiveness in meeting some performance goal. One performance goal, rate of fault detection, is a measure of how quickly faults are detected within the testing process; an improved rate of fault detection can provide faster feedback on the system under test, and let software engineers begin locating and correcting faults earlier than might otherwise be possible. In previous work, we reported the results of studies that showed that prioritization techniques can significantly improve rate of fault detection. Those studies, however, raised several additional questions: (1) can prioritization techniques be effective when aimed at specific modified versions; (2) what tradeoffs exist between fine granularity and coarse granularity prioritization techniques; (3) can the incorporation of measures of fault proneness into prioritization techniques improve their effectiveness? This paper reports the results of new experiments addressing these questions.

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