Prioritization of test case scenarios derived from activity diagram using genetic algorithm

Author

Sabharwal, Sangeeta ; Sibal, Ritu ; Sharma, Chayanika

Author_Institution

Dept. of Comput. Sci. & IT, Netaji Subhas Inst. of Technol., Delhi, India

fYear

2010

fDate

17-19 Sept. 2010

Firstpage

481

Lastpage

485

Abstract

Software testing involves identifying the test cases which discovers the errors in the program. However, the exhaustive testing is rarely impossible and very time consuming. In this paper, the software testing efficiency is optimized by identifying the critical path clusters. The test case scenarios are derived from the activity diagram and the testing efficiency is optimized by applying the genetic algorithm on the test data. The information flow metric is adopted in this work for calculating the information flow complexity associated with each node of activity diagram.

Keywords

genetic algorithms; program testing; activity diagram; critical path cluster; genetic algorithm; information flow complexity; information flow metric; program error; software testing; test case scenario; Biological cells; Evolutionary computation; Gallium; Software; Software testing; Unified modeling language; CFG; activity diagram; genetic algorithm; software testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer and Communication Technology (ICCCT), 2010 International Conference on

Conference_Location

Allahabad, Uttar Pradesh

Print_ISBN

978-1-4244-9033-2

Type

conf

DOI

10.1109/ICCCT.2010.5640479

Filename

5640479