PathART: path-sensitive adaptive random testing

Authors:
Shan-Shan Hou;Chun Zhang;Dan Hao;Lu Zhang
Affiliations:
Key Laboratory of High Confidence Software Technologies (Peking University), MoE and Peking University, Beijing, China;Key Laboratory of High Confidence Software Technologies (Peking University), MoE and Peking University, Beijing, China;Key Laboratory of High Confidence Software Technologies (Peking University), MoE and Peking University, Beijing, China;Key Laboratory of High Confidence Software Technologies (Peking University), MoE and Peking University, Beijing, China
Venue:
Proceedings of the 5th Asia-Pacific Symposium on Internetware
Year:
2013

Citing 11
Cited 0

Symbolic execution and program testing

Communications of the ACM
A new method for constructing pair-wise covering designs for software testing

Information Processing Letters
Test input generation with java PathFinder

ISSTA '04 Proceedings of the 2004 ACM SIGSOFT international symposium on Software testing and analysis
Adaptive Random Testing Through Dynamic Partitioning

QSIC '04 Proceedings of the Quality Software, Fourth International Conference
Adaptive Random Testing by Localization

APSEC '04 Proceedings of the 11th Asia-Pacific Software Engineering Conference
An Approach to Test Data Generation for Killing Multiple Mutants

ICSM '06 Proceedings of the 22nd IEEE International Conference on Software Maintenance
Feedback-Directed Random Test Generation

ICSE '07 Proceedings of the 29th international conference on Software Engineering
ARTOO: adaptive random testing for object-oriented software

Proceedings of the 30th international conference on Software engineering
Test-data generation guided by static defect detection

Journal of Computer Science and Technology
Test generation via Dynamic Symbolic Execution for mutation testing

ICSM '10 Proceedings of the 2010 IEEE International Conference on Software Maintenance
Effective Message-Sequence Generation for Testing BPEL Programs

IEEE Transactions on Services Computing

Quantified Score

Hi-index	0.00

Visualization

Abstract

As test data widely spreading on the input domain may not thoroughly test the program's logic, in this paper, we propose an approach to generating test data widely spreading on a program's execution paths. In particular, we analyze execution paths of the program, distill constraints for executing the paths, calculate the path distance between test data according to their satisfaction for paths' constraints, and then generate test data far away from each other based on their path distance. The experimental results show that our approach significantly reduces the number of test data generated before the first fault is found.