Data mining library reuse patterns using generalized association rules
Proceedings of the 22nd international conference on Software engineering
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IEEE Transactions on Software Engineering
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In this paper, we show how data mining can be used to discover library reuse patterns in user-selected applications. This can be helpful in building and debugging applications that use a particular library by observing how other developers have used that library in their applications.Specifically, we consider the problem of discovering association rules that identify library components that are often reused in combination by application components. For example, such a rule might tell us that application classes that inherit from a particular library class often override certain member functions.By querying and/or browsing such association rules, a developer can discover patterns for reusing library components. We illustrate the approach using our tool, Code-Web, by demonstrating characteristic ways in which applications reuse components in the ET++ application framework.