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  1. Proceedings of the 5th International Workshop on Emerging Trends in Software Metrics (WETSoM 2014)
  2. Clustering of defects in Java software systems
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What can changes tell about software processes?
Why are industrial agile teams using metrics and how do they use them?
Design test process in component-based software engineering: an analysis of requirements scalability
A new metric for predicting software change using gene expression programming
A replicated study on correlating agile team velocity measured in function and story points
In-depth measurement and analysis on densification power law of software execution
Using fine-grained code change metrics to simulate software evolution
"May the fork be with you": novel metrics to analyze collaboration on GitHub
Clustering of defects in Java software systems
Structural evolution of software: a social network perspective
Towards a catalog format for software metrics
A security metric based on security arguments

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Clustering of defects in Java software systems

Content Provider ACM Digital Library
Author Monni, Cristina OrrĂ¹, Matteo Concas, Giulio Tonelli, Roberto
Abstract In this paper we present a case study about the clustering of maintenance activities applied on large software systems, from the complex networks perspective. We analyze several releases of two large Open Source Java software systems, using data extracted from Software Configuration Management systems and from Issue Tracking systems (ITS). We find that Java files affected by maintenance activity are likely to be connected with each other, forming interconnected clusters inside the software network associated to the software system. This means that Java files interested by the maintenance activities requested on ITS are likely to be connected each other through dependencies at the source code level. The information carried by the clusters of Java files may be used to improve strategies for large maintenance operations. Since the tendency to form clusters can vary across different systems, such analysis can also be a useful indicator of the impact of defects on source code files in different software systems. .
Starting Page 59
Ending Page 65
Page Count 7
File Format PDF
ISBN 9781450328548
DOI 10.1145/2593868.2593879
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2014-06-03
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Bugs Software networks Clustering
Content Type Text
Resource Type Article
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