Large-scale, AST-based API-usage analysis of open-source Java projects

Authors:
Ralf Lämmel;Ekaterina Pek;Jürgen Starek
Affiliations:
Universität Koblenz-Landau, Germany;Universität Koblenz-Landau, Germany;Universität Koblenz-Landau, Germany
Venue:
Proceedings of the 2011 ACM Symposium on Applied Computing
Year:
2011

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Abstract

Research on API migration and language conversion can be informed by empirical data about API usage. For instance, such data may help with designing and defending mapping rules for API migration in terms of relevance and applicability. We describe an approach to large-scale API-usage analysis of open-source Java projects, which we also instantiate for the Source-Forge open-source repository in a certain way. Our approach covers checkout, building, tagging with metadata, fact extraction, analysis, and synthesis with a large degree of automation. Fact extraction relies on resolved (type-checked) ASTs. We describe a few examples of API-usage analysis; they are motivated by API migration. These examples are concerned with analysing API footprint (such as the numbers of distinct APIs used in a project), API coverage (such as the percentage of methods of an API used in a corpus), and framework-like vs. class-library-like usage.