Efficient fault-prone software modules selection based on complexity metrics

Author

Yigang Wang ; Xiaodong Zhu ; Yanbin Ye ; Fei Ye

Author_Institution

Maintenance Eng. Inst., Mech. Eng. Coll., Shijiazhuang, China

Volume

2

fYear

2009

fDate

8-9 Aug. 2009

Firstpage

103

Lastpage

106

Abstract

In order to improve the software reliability early, this paper proposes an efficient algorithm to select fault-prone software module. Based on software module´s complexity metrics, the algorithm uses modified cascaded-correlation algorithm as neural network classifier to select the fault-prone software module. Finally, by analyzing the algorithm´s application in the project MAP, the paper shows the advantage of the algorithm.

Keywords

neural nets; pattern classification; software fault tolerance; software maintenance; software metrics; cascaded-correlation algorithm; complexity metrics; fault-prone software module selection; maintainability allocation-and-prediction; neural network classifier; project MAP; software reliability; Algorithm design and analysis; Artificial intelligence; Communication system control; Engineering management; Maintenance engineering; Mechanical engineering; Neural networks; Software algorithms; Software maintenance; Software reliability; cascade-correlation; complexity metrics; cross-validation; fault-prone; neural network;

fLanguage

English

Publisher

ieee

Conference_Titel

Computing, Communication, Control, and Management, 2009. CCCM 2009. ISECS International Colloquium on

Conference_Location

Sanya

Print_ISBN

978-1-4244-4247-8

Type

conf

DOI

10.1109/CCCM.2009.5267972

Filename

5267972