Got Issues? Do New Features and Code Improvements Affect Defects?
Authors:
- Daryl PosnettDPDaryl Posnett
- Abram HindleAHAbram Hindle
- Prem DevanbuPDPrem Devanbu
- 1 October 2011
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- No. 10951350,p. 211-215
Abstract
There is a perception that when new features are added to a system that those added and modified parts of the source-code are more fault prone. Many have argued that new code and new features are defect prone due to immaturity, lack of testing, as well unstable requirements. Unfortunately most previous work does not investigate the link between a concrete requirement or new feature and the defects it causes, in particular the feature, the changed code and the subsequent defects are rarely investigated. In this paper we investigate the relationship between improvements, new features and defects recorded within an issue tracker. A manual case study is performed to validate the accuracy of these issue types. We combine defect issues and new feature issues with the code from version-control systems that introduces these features, we then explore the relationship of new features with the fault-proneness of their implementations. We describe properties and produce models of the relationship between new features and fault proneness, based on the analysis of issue trackers and version-control systems. We find, surprisingly, that neither improvements nor new features have any significant effect on later defect counts, when controlling for size and total number of changes.Keywords
This publication has 7 references indexed in Scilit:
- Does distributed development affect software quality? An empirical case study of Windows Vista2009
- Predicting defects in SAP Java code: An experience report2009
- Using Software Dependencies and Churn Metrics to Predict Field Failures: An Empirical Case Study2007
- EQ-Mine: Predicting Short-Term Defects for Software Evolution2007
- Where the bugs areACM SIGSOFT Software Engineering Notes, 2004
- Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple TestingJournal of the Royal Statistical Society Series B: Statistical Methodology, 1995
- Likelihood Ratio Tests for Model Selection and Non-Nested HypothesesEconometrica, 1989