Bug Prediction Metrics Based Decision Support For Preventive Software Maintenance

被引：1

作者：

Maskeri, Girish ^{[1
]}

Karnam, Deepthi ^{[1
]}

Viswanathan, SreeAurovindh ^{[1
]}

Padmanabhuni, Srinivas ^{[1
]}

机构：

[1] Infosys Ltd, Infosys Labs, Bangalore, Karnataka, India

来源：

2012 19TH ASIA-PACIFIC SOFTWARE ENGINEERING CONFERENCE (APSEC), VOL 1 | 2012年

关键词：

Bug Prevention; Software Maintenance; Mining Software Repositories; QUALITY; COMPLEXITY; FAULTS;

D O I：

10.1109/APSEC.2012.43

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

There exist a number of large legacy systems that still undergo continuous maintenance and enhancement. Due to the sheer size and complexity of the software systems and limited resources, managers are confronted with crucial decisions regarding allocation and training of new engineers, intelligent allocation of testing personnel, assessment of release readiness of the software and so on. While the area of bug prediction by mining software repositories holds promise, and is a worthwhile endeavor, the current state of the art techniques are not accurate enough in predicting bugs and hence are of limited usefulness to managers. So instead of predicting files as buggy or not we take a different viewpoint and focus on providing decision support for managers. In this paper we present a set of metrics to guide the managers in taking these decisions. These metrics are evaluated using 4 open source systems and 2 proprietary systems.

引用

页码：260 / 269

页数：10

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