Improving the Java PathFinder tool for generating test data by optimizing constraints
Abstract: 72
| 
PDF: 43 
##plugins.themes.academic_pro.article.main##
Author
Abstract
Test data generation is one of the most important and crucial phases in software testing. Structural test data generation techniques are based on source code to create test data, which can uncover programmer\'s faults.A test data generation technique using symbolic execution is implemented in the Java PathFinder tool to generate test data for Java programs. However, Java PathFinder has a performance limitation: execution time is quite big. In this paper, we propose applying an optimization algorithm for constraints - representing execution paths in programs - in order to reduce the execution time but ensure the coverage effectiveness. The experiment on different Java programs shows a promising result of the proposed solution.
References
-
[1] Cristian Cadar and Koushik Sen, “Symbolic execution for software testing: three decades later”, Commununications of the ACM 56, February. 2013, pp. 82-90.
[2] Cristian Cadar, Patrice Godefroid, Sarfraz Khurshid, Corina Pasareanu, Koushik Sen, Nikolai Tillmann, Willem Visser, Symbolic Execution for Software Testing in Practice – Preliminary Assessment, Proceedings of the 33rd International Conference on Software Engineering, 2011.
[3] W. Visser, K. Havelund, G. Brat, S.-J. Park, and F. Lerda, “Model Checking Programs”, Automated Software Engineering Journal, 10(2), April. 2003.
[4] J. C. King, Symbolic execution and program testing, Communication ACM, 19(7), 1976, pp. 385–394.
[5] D. Coward, Symbolic execution and testing, Inf. Softw. Technol., 33(1), 1991, pp. 53–64.
[6] Corina S. Pǎsǎreanu, Peter C. Mehlitz, David H. Bushnell, Karen Gundy-Burlet, Michael Lowry, Suzette Person, and Mark Pape, Combining unit-level symbolic execution and system-level concrete execution for testing nasa software, In Proceedings of the 2008 International Symposium on Software testing and analysis (ISSTA '08), ACM, New York, NY, USA, 2008, pp.
[7] -26.
[8] Ikpeme Erete and Alessandro Orso, Optimizing Constraint Solving to Better Support Symbolic Execution, Proceedings of the 2012 IEEE Fourth International Conference on Software Testing, Verification and Validation, 2012.
[9] http://www.choco-solver.org.
[10] Ngô Pô Na, Xây dựng công cụ sinh dữ liệu thử tự động cho chương trình Java, Luận văn Thạc sỹ, Đại học Đà Nẵng, 2017.
Read more
##plugins.themes.academic_pro.article.sidebar##
Published
May 31, 2017
Download
How to Cite
Le Thi My Hanh*; Tran Hoang Dung, Nguyen Thanh Binh. “Improving the Java PathFinder Tool for Generating Test Data by Optimizing Constraints”. The University of Danang - Journal of Science and Technology, vol. 5, no. 114.1, May 2017, pp. 104-7, https://jst-ud.vn/jst-ud/article/view/3096.
