Fine grained indexing of software repositories to support impact analysis
Proceedings of the 2006 international workshop on Mining software repositories
Where is bug resolution knowledge stored?
Proceedings of the 2006 international workshop on Mining software repositories
Detection of Duplicate Defect Reports Using Natural Language Processing
ICSE '07 Proceedings of the 29th international conference on Software Engineering
An empirical study on the evolution of design patterns
Proceedings of the the 6th joint meeting of the European software engineering conference and the ACM SIGSOFT symposium on The foundations of software engineering
Journal of Software Maintenance and Evolution: Research and Practice
Improving the readability of defect reports
Proceedings of the 2008 international workshop on Recommendation systems for software engineering
Comparison of Process Quality Characteristics Based on Change Request Data
IWSM/Metrikon/Mensura '08 Proceedings of the International Conferences on Software Process and Product Measurement
Using information retrieval based coupling measures for impact analysis
Empirical Software Engineering
Empirical Software Engineering
Dependence clusters in source code
ACM Transactions on Programming Languages and Systems (TOPLAS)
Empirical Evaluation of Strategies to Detect Logical Change Dependencies
SOFSEM '10 Proceedings of the 36th Conference on Current Trends in Theory and Practice of Computer Science
An eclectic approach for change impact analysis
Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering - Volume 2
Applications of data mining in software engineering
International Journal of Data Analysis Techniques and Strategies
Impact analysis by means of unstructured knowledge in the context of bug repositories
Proceedings of the 2010 ACM-IEEE International Symposium on Empirical Software Engineering and Measurement
Impact analysis of SCRs using single and multi-label machine learning classification
Proceedings of the 2010 ACM-IEEE International Symposium on Empirical Software Engineering and Measurement
Recovering traceability links between source code and fixed bugs via patch analysis
Proceedings of the 6th International Workshop on Traceability in Emerging Forms of Software Engineering
A taxonomy for software change impact analysis
Proceedings of the 12th International Workshop on Principles of Software Evolution and the 7th annual ERCIM Workshop on Software Evolution
A static technique for fault localization using character n-gram based information retrieval model
Proceedings of the 5th India Software Engineering Conference
Clustering methodologies for software engineering
Advances in Software Engineering
Communicating continuous integration servers for increasing effectiveness of automated testing
Proceedings of the 27th IEEE/ACM International Conference on Automated Software Engineering
Connectivity of co-changed method groups: a case study on open source systems
CASCON '12 Proceedings of the 2012 Conference of the Center for Advanced Studies on Collaborative Research
The bug report duplication problem: an exploratory study
Software Quality Control
Information and Software Technology
Concept location using program dependencies and information retrieval (DepIR)
Information and Software Technology
Data stream mining for predicting software build outcomes using source code metrics
Information and Software Technology
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Impact analysis is the identification of the work products affected by a proposed change request, either a bug fix or a new feature request. In many open-source projects, such as KDE, Gnome, Mozilla, Openoffice, change requests, and related data, are stored in a bug tracking system such as Bugzilla [1]. These data, together with the data stored in a versioning system, such as CVS [2], are a valuable source of information on which useful analyses can be performed. In this paper we propose a method to derive the set of source files impacted by a proposed change request. The method exploits information retrieval algorithms to link the change request description and the set of historical source file revisions impacted by similar past change requests. The method is evaluated by applying it on four open-source projects.