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General Information
    • ISSN: 2301-3559
    • Frequency: Quarterly
    • DOI: 10.18178/LNSE
    • Editor-in-Chief: Prof. Jemal Antidze
    • Executive Editor: Ms. Nina Lee
    • Abstracting/ Indexing: EI (INSPEC, IET), Electronic Journals Library,  Ulrich's Periodicals Directory, International Computer Science Digital Library (ICSDL), ProQuest and Google Scholar.
    • E-mail: lnse@ejournal.net
Prof. Jemal Antidze
I. Vekua Scientific Institute of Applied Mathematics
Tbilisi State University, Georgia
I'm happy to take on the position of editor in chief of LNSE. We encourage authors to submit papers concerning any branch of Software Engineering.

LNSE 2015 Vol.3(2): 152-156 IS4SN: 2301-3559
DOI: 10.7763/LNSE.2015.V3.181

Automated Software Test Data Generation Using Improved Search Procedure

Shubham Agarwal and Abhimanyu Bhatter
Abstract—Automated software test data generation is a complex and one of the most challenging task. Generation of test data manually is tedious and error-prone. The base algorithm, which has been improved in this paper involves redundant and un-necessary execution cycles. In this paper, we have proposed an efficient search procedure that reduces the time complexity of test data generation significantly. Our experiments conducted on varying sizes of source code showing ratio of execution time of automated test data generation using Basic Search Procedure and our Improved Search Procedure conclude that, with the increase of source code size, test data generation takes place in lesser time using our improved search procedure.

Index Terms—Automated test data generation, basic search procedure, risk factor, white box testing, time complexity.

The authors are with the Birla Institute of Technology and Science, Pilani, India (e-mail: agarwalshubham2007@gmail.com, abhimanyubhatter@gmail.com).


Cite: Shubham Agarwal and Abhimanyu Bhatter, "Automated Software Test Data Generation Using Improved Search Procedure," Lecture Notes on Software Engineering vol. 3, no. 2, pp. 152-156, 2015.

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