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 November 2024
Call for Paper
December Edition
IJCA solicits high quality original research papers for the upcoming December edition of the journal. The last date of research paper submission is 20 November 2024

Submit your paper
Know more
Reseach Article

Path Prioritization using Meta-Heuristic Approach

by Himanshi, Nitin Umesh, Saurabh Srivastava
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 77 - Number 11
Year of Publication: 2013
Authors: Himanshi, Nitin Umesh, Saurabh Srivastava
10.5120/13435-8638

Himanshi, Nitin Umesh, Saurabh Srivastava . Path Prioritization using Meta-Heuristic Approach. International Journal of Computer Applications. 77, 11 ( September 2013), 1-5. DOI=10.5120/13435-8638

@article{ 10.5120/13435-8638,
author = { Himanshi, Nitin Umesh, Saurabh Srivastava },
title = { Path Prioritization using Meta-Heuristic Approach },
journal = { International Journal of Computer Applications },
issue_date = { September 2013 },
volume = { 77 },
number = { 11 },
month = { September },
year = { 2013 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume77/number11/13435-8638/ },
doi = { 10.5120/13435-8638 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:49:58.360749+05:30
%A Himanshi
%A Nitin Umesh
%A Saurabh Srivastava
%T Path Prioritization using Meta-Heuristic Approach
%J International Journal of Computer Applications
%@ 0975-8887
%V 77
%N 11
%P 1-5
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Software testing is one of the most important phase in development life cycle of any software system as testing assures the quality of the software i. e. a software is bug-free can judged using software testing. Although, creating bug-free software is impossible but we can find out most of the bugs and recover them. Software testing can be done in many ways but here we will focus on structural testing. This paper presents an approach which can prioritize the paths among a set of paths such that they can be executed accordingly and comparison between existing methods is done. All results have been produced using a software developed for the purpose.

References
  1. Baby, K. M. (2009). An Approach of Optimal Path Generation using Ant colony optimization. IEEE , 1-6.
  2. Bhuvnesh Sharma, I. G. (2011). Software Coverage : A Testing Approach through Ant Colony Optimization. Swarm, Evolutionary, and Memetic Computing - Second International Conference, SEMCCO 2011 (pp. 618-625). vishakhapatnam: Springer-Verlag Berlin Heidelberg 2011.
  3. Christian Blum, M. B. (2005). Combining Ant Colony Optimization with Dynamic Programming for Solving the k-Cardinality Tree Problem. Computational Intelligence and Bioinspired Systems , 25-30.
  4. Dorigo, M. (1992). Optimization, Learning and Natural Algorithms. italy: the Milano polytechnic.
  5. Ghiduk, A. S. (2010). A New Software Data-Flow Testing Approach via Ant Colony Algorithms. Universal Journal of Computer Science and Engineering Technology , 64-72.
  6. Gogul Balakrishnan, S. S. (2008). SLR: Path-Sensitive Analysis through Infeasible-Path Detection and Syntactic Language Refinement. springer verlag , 1-16.
  7. Greco, F. (2008). travelling salesman problem. croatia: in-teh.
  8. Hunt, t. (2002). Advanced Topics in Computer Science: Testing. wales: swansea univesity.
  9. Mathur, a. (2007). foundation of software testing. new delhi: pearson education.
  10. McCabe, t. J. (1976). A Complexity Measure. IEEE transactions on software engineering , 308-320.
  11. Mousavi. (2012). Path Testing. Eindhoven University of Technology, The Netherlands , 1-7.
  12. Qingfeng, D. (2009). An improved algortihm for basis path testing. IEEE (pp. 175-178). hefei: IEEE.
  13. Rai. (2009). An Ant Colony Optimization Approach to Test Sequence Generation for Control Flow based Software Testing. ICISTM' 09 (pp. 345-356). berlin: springr.
  14. Roggenbach, H. S. (2002). Topics in Computer Science: Testing, Path Testing". wales: swansea university.
  15. Sommerville, i. (2009). software engineering. london: pearson edition.
  16. Srivastava, p. r. (2010). Automated Software Testing Using Metahurestic Technique Based on An Ant Colony Optimization. electronic system design .
  17. Stutzle, t. (2004). ant colony optimzation. london: MIT press.
  18. T. Bharat Kumar, N. H. (2012). An Catholic and Enhanced Study on Basis Path Testing to Avoid Infeasible Paths in CFG. Global Trends in Information Systems and Software Applications , 386-395.
  19. Zhang Zhonglin, M. L. (2010). An Improved Method of Acquiring Basis Path for software testing. ICCSE'10 (pp. 1891-1894). hefei: IEEE.
  20. Zhao, R. (2012). A Path-oriented Automatic Random Testing based on Double Constraint Propagation. IJSEA , 1-11.
Index Terms

Computer Science
Information Sciences

Keywords

Path Prioritization