We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 December 2024
Reseach Article

Test Data Generation using Artificial Life

by Harsh Bhasin, Shewani, Deepika Goyal
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 67 - Number 12
Year of Publication: 2013
Authors: Harsh Bhasin, Shewani, Deepika Goyal
10.5120/11450-7045

Harsh Bhasin, Shewani, Deepika Goyal . Test Data Generation using Artificial Life. International Journal of Computer Applications. 67, 12 ( April 2013), 34-39. DOI=10.5120/11450-7045

@article{ 10.5120/11450-7045,
author = { Harsh Bhasin, Shewani, Deepika Goyal },
title = { Test Data Generation using Artificial Life },
journal = { International Journal of Computer Applications },
issue_date = { April 2013 },
volume = { 67 },
number = { 12 },
month = { April },
year = { 2013 },
issn = { 0975-8887 },
pages = { 34-39 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume67/number12/11450-7045/ },
doi = { 10.5120/11450-7045 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:24:40.670612+05:30
%A Harsh Bhasin
%A Shewani
%A Deepika Goyal
%T Test Data Generation using Artificial Life
%J International Journal of Computer Applications
%@ 0975-8887
%V 67
%N 12
%P 34-39
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Test Data Generation is an intricate process which requires intensive manual labor and thus a lot of project time. There is an immediate need of finding out an effective technique for automating the process as manual Test Data Generation escalates the project cost. The paper proposes the use of Artificial Life in generating and minimizing the Test Cases. The work has been applied on some programs and the initial results are encouraging. The technique makes sure that all the modules are tested in accordance with their functional specifications by the Artificial Life Test Suite Generator (ALTSG). The initial results even points to an indication of the technique being better than its counterparts.

References
  1. Bertolino, A. , Marchetti, E. : A brief essay on software testing. In: Thayer, R. H. , Christensen, M. J. (eds. ) Software Engineering, 3rd edn. Development process, vol. 1, pp. 393–411. Wiley-IEEE Computer Society Press (2005)
  2. J. Edvardsson. A survey on automatic test data generation. In Proceedings of the Second Conference on Computer Science and Engineering in Linkoping, pages 21-28. ECSEL, October 1999.
  3. Neelam Gupta , Aditya P. Mathur , Mary Lou Soffa, Automated test data generation using an iterative relaxation method, Proceedings of the 6th ACM SIGSOFT international symposium on Foundations of software engineering, p. 231-244, November 01-05, 1998, Lake Buena Vista, Florida, United States
  4. Roger Ferguston, B. Korel, The chaining approach for software test data generation, ACM Transactions on Software Engineering and Methodology (TOSEM) Volume 5.
  5. Ali M. Alakeel. 2010. A Framework for Concurrent Assertion – Based Automated Test Data Generation. Universityof Tabuk. Saudi Arabia.
  6. C. G. Langton (1984). "Self-reproduction in cellular automata". Physica D 10: 135–144.
  7. Von Neumann, John; Burks, Arthur W. (1966). "Theory of Self-Reproducing Automata. " (Scanned book online). www. walenz. org. Archived from the original on 2008-01-05. Retrieved 2008-02-29.
  8. Wiener, N. 1948. Cybernetics, or Control and Communication in the Animal and the Machine. Wiley.
  9. B. A. Kitchenham et. Al. Systematic literature reviews in software engineering - A tertiary study, Information & Software Technology - INFSOF , vol. 52, no. 8, pp. 792-805, 2010.
Index Terms

Computer Science
Information Sciences

Keywords

Artificial Life Test Data Generator Program Analyzer Path Selector