Expertise browser: a quantitative approach to identifying expertise
Proceedings of the 24th International Conference on Software Engineering
Mining Version Histories to Guide Software Changes
Proceedings of the 26th International Conference on Software Engineering
Use of relative code churn measures to predict system defect density
Proceedings of the 27th international conference on Software engineering
Facilitating software evolution research with kenyon
Proceedings of the 10th European software engineering conference held jointly with 13th ACM SIGSOFT international symposium on Foundations of software engineering
ICSM '05 Proceedings of the 21st IEEE International Conference on Software Maintenance
Proceedings of the 28th international conference on Software engineering
Toward a Software Maintenance Methodology using Semantic Web Techniques
SOFTWARE-EVOLVABILITY '06 Proceedings of the Second International IEEE Workshop on Software Evolvability
Questions programmers ask during software evolution tasks
Proceedings of the 14th ACM SIGSOFT international symposium on Foundations of software engineering
Predicting Faults from Cached History
ICSE '07 Proceedings of the 29th international conference on Software Engineering
Mining Software Repositories with iSPAROL and a Software Evolution Ontology
MSR '07 Proceedings of the Fourth International Workshop on Mining Software Repositories
Answering conceptual queries with Ferret
Proceedings of the 30th international conference on Software engineering
Change Analysis with Evolizer and ChangeDistiller
IEEE Software
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We propose a distributed and collaborative software analysis platform to enable seamless interoperability of software analysis tools across platform, geographical and organizational boundaries. In particular, we devise software analysis tools as services that can be accessed and composed over the Internet. These distributed services shall be widely accessible through a software analysis broker where organizations and research groups can register and share their tools. To enable (semi)-automatic use and composition of these tools, they will be classified and mapped into a software analysis taxonomy and adhere to specific meta-models and ontologies for their category of analysis. We claim that moving software analysis "outside the lab and into the Web" is highly beneficial from many point of views. Simple, common analyses can be effortlessly combined together into much meaningful, complex and novel ones. Analyses can be run everywhere and anytime without the need to install several tools and to cope with many output formats. Empirical studies can be easily replicated. At last, we claim that this will greatly help in the maturing of the field and boost its role in supporting software development practices