DocumentCode :
1955728
Title :
Notice of Retraction
Generation of efficient test data using path selection strategy with elitist GA in regression testing
Author :
Kumar, A. ; Tiwari, S. ; Mishra, K.K. ; Misra, A.K.
Author_Institution :
Comput. Sci. & Eng. Dept., MNNIT, Allahabad, India
Volume :
9
fYear :
2010
fDate :
9-11 July 2010
Firstpage :
389
Lastpage :
393
Abstract :
Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

Regression testing is an expensive and frequently executed maintenance process used to revalidate modified software. Various problems are associated with regression testing such as regression test selection problem, coverage identification problem, test case execution problem, test case maintenance problem etc. In test selection problem, appropriate and effective test data is to be selected from the input domain of test data. One more problem may arise, when tester has to select the modified paths from the set of modified path for test case execution i.e. path selection problem. To overcome these problems, this paper presents a combined approach by which the stated problems are resolved in effective manner. By this approach, tester can identify the appropriate paths for test case execution and also generate efficient test data using elitist version of GA. The proposed approach enables tester to execute the test cases in order to increase their effectiveness to find faults taking minimum efforts. This approach is used in regression testing to choose an appropriate subset of test cases by using elitist GA, among a previously run test suite for a software system, based on the information about the modifications made to the system for enhancement.
Keywords :
genetic algorithms; program testing; software fault tolerance; software maintenance; elitist GA; fault; path selection problem; regression testing; software maintenance; software system; software testing; system enhancement; system modification; test case execution; test data; test selection; Complexity theory; Elitist GA; Path Selection Problem; Regression Testing; Test Case Selection Problem;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Information Technology (ICCSIT), 2010 3rd IEEE International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-5537-9
Type :
conf
DOI :
10.1109/ICCSIT.2010.5564915
Filename :
5564915
Link To Document :
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