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Data Mining Techniques for Building Fault-Proneness Models in Telecom Java Software

Overview This paper describes a study performed in an industrial setting that attempts to build predictive models to identify parts of a Java system with a high probability of fault. Developers usually have limited resources for their testing and inspections and would like to be able to devote extra resources to faulty system parts. The main focus of this paper is two-fold: use and compare many data mining and machine learning techniques to build fault-proneness models based mostly on source code measures and change/fault history data, and demonstrate that the usual classification evaluation criteria based on confusion matrices may not be fully appropriate to compare and evaluate models.

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Publisher
Simula Research Laboratory
File Format
PDF
Date Published
Oct 7, 2008
Format
White Papers
Topics
Application Development, Java, Data Mining - Analysis

Simula Research Laboratory White Papers

A Preliminary Checklist for Software Cost Management

A Preliminary Checklist for Software Cost Management

This paper presents a process framework and a preliminary checklist for software cost management. While most textbooks a

Publisher: Simula Research Laboratory  |  Tags: management, software