Data stream mining for predicting software build outcomes using source code metrics

TL;DR

This paper explores how data stream mining techniques applied to source code metrics from software repositories can predict software build outcomes, aiming to improve development process insights.

Contribution

It introduces a novel approach combining data stream mining with source code metrics for predicting software build success or failure.

Findings

Effective prediction of build outcomes using source code metrics

Enhanced understanding of development process through repository mining

Potential for real-time build outcome prediction

Abstract

Software development projects involve the use of a wide range of tools to produce a software artifact. Software repositories such as source control systems have become a focus for emergent research because they are a source of rich information regarding software development projects. The mining of such repositories is becoming increasingly common with a view to gaining a deeper understanding of the development process.