Title
Towards A Software Diagnosis Method Based On Rough Set Reasoning
Abstract
Software diagnosis for finding faults based on the test results is one of the most time-consuming and labor-intensive activities in large scale software development. Revealing the potential knowledge hidden in the test results or program constructs to assist this activity is a rational solution. In this paper, we propose two kinds of debugging applications based on rough set reasoning. One is to select key input parameters which will affect program's behaviors to facilitate diagnosis. The other is to extract association rules between program input and its behaviors. The inputs of the above two rough reasoning applications arc, all the test results of functional testing. Our work is the first attempt to utilize functional testing information to help software debugging. The feasibility and effectiveness of our approach is validated by some examples and experiments. In addition, some on-going research issues are also addressed
Year
DOI
Venue
2008
10.1109/CIT.2008.4594763
2008 IEEE 8TH INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION TECHNOLOGY, VOLS 1 AND 2
Keywords
Field
DocType
application software,testing,cognition,software development,rough set,classification algorithms,software testing,software engineering,finance,programming,functional testing,association rule,rough set theory,computer science,association rules,data mining,debugging
Data mining,Computer science,Software diagnosis,Functional testing,Rough set,Software,Application software,Software construction,Software development,Debugging
Conference
Volume
Issue
Citations 
null
null
4
PageRank 
References 
Authors
0.57
10
3
Name
Order
Citations
PageRank
Chengying Mao116225.01
Xiaohua Hu22819314.15
Yansheng Lu355553.68