Paper Info
Title
The Effectiveness of Automated Static Analysis Tools for Fault Detection and Refactoring Prediction
Abstract
Many automated static analysis (ASA) tools have been developed in recent years for detecting software anomalies. The aim of these tools is to help developers to eliminate software defects at early stages and produce more reliable software at a lower cost. Determining the effectiveness of ASA tools requires empirical evaluation. This study evaluates coding concerns reported by three ASA tools on two open source software (OSS) projects with respect to two types of modifications performed in the studied software CVS repositories: corrections of faults that caused failures, and refactoring modifications. The results show that fewer than 3% of the detected faults correspond to the coding concerns reported by the ASA tools. ASA tools were more effective in identifying refactoring modifications and corresponded to about 71% of them. More than 96% of the coding concerns were false positives that do not relate to any fault or refactoring modification.
Year
DOI
Venue
2009
10.1109/ICST.2009.21
ICST
Keywords
Field
DocType
open source software,automated static analysis,asa tool,refactoring modification,early stage,refactoring prediction,fault detection,coding concern,software cvs repository,software anomaly,reliable software,automated static analysis tools,software defect,computer science,encoding,false positive,software testing,data mining,probability density function,static analysis tools,anomaly detection,documentation,static analysis,inspection,java,public domain software,testing
Static program analysis,Anomaly detection,Fault detection and isolation,Computer science,Static analysis,Real-time computing,Coding (social sciences),Software,Code refactoring,Reliability engineering,False positive paradox
Conference
Citations 
PageRank 
References 
10
0.50
10
Authors
3
Name
Order
Citations
PageRank
Fadi Wedyan1474.17
Dalal Alrmuny2120.86
James M. Bieman31237121.36