DocumentCode :
2560669
Title :
A genetic algorithm for the time-aware regression testing reduction problem
Author :
You, Liang ; Lu, Yansheng
Author_Institution :
Coll. of Comput. Sci. & Technol., Huazhong Univ. of Sci. & Technol., Wuhan, China
fYear :
2012
fDate :
29-31 May 2012
Firstpage :
596
Lastpage :
599
Abstract :
After the programmer fixes the bugs and enhances the functionality of the software project, regression testing reruns the regression testing suite to ensure that the new version software projects can run smoothly and correctly. Because the regression testing is the most expensive phase of the software testing, regression testing reduction eliminates the redundant test cases in the regression testing suite and saves the cost of the regression testing. This paper formally defines the time-aware regression testing reduction problem. It also proposes a novel genetic algorithm for the time-aware regression testing reduction problem. It defines the representation and fitness function of the genetic algorithm, it also describes the parent selection, crossover and mutation operator of the genetic algorithm. The novel algorithm not only removes redundant test cases in the regression testing suite but also minimizes the total running time of the remaining test cases. Finally, the paper evaluates the genetic algorithm using eight example programs. The experimental result illustrates the efficiency of the proposed genetic algorithm for the time-aware regression testing reduction problem.
Keywords :
algorithm theory; genetic algorithms; regression analysis; software management; fitness function; genetic algorithm; mutation operator; parent selection; programmer fix; redundant test case; regression testing suite; time-aware regression testing reduction problem; version software project; Algorithm design and analysis; Genetic algorithms; Greedy algorithms; Heuristic algorithms; Maintenance engineering; Software; Testing; genetic algorithm; regression testing; regression testing minimization; regression testing reduction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation (ICNC), 2012 Eighth International Conference on
Conference_Location :
Chongqing
ISSN :
2157-9555
Print_ISBN :
978-1-4577-2130-4
Type :
conf
DOI :
10.1109/ICNC.2012.6234754
Filename :
6234754
Link To Document :
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