Title :
Data mining library reuse patterns in user-selected applications
Author_Institution :
Dept. of Comput. Sci. & Eng., Washington Univ., Seattle, WA, USA
Abstract :
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, CodeWeb, by demonstrating characteristic ways in which applications reuse components in the ET++ application framework
Keywords :
data mining; program debugging; software libraries; software reusability; software tools; CodeWeb tool; ET++ application framework; application building; application classes; application debugging; association rule browsing; association rule discovery; association rule querying; data mining; library class; library reuse patterns; user-selected applications; Application software; Association rules; Books; Computer science; Data engineering; Data mining; Debugging; Electrical capacitance tomography; Software libraries; Sparks;
Conference_Titel :
Automated Software Engineering, 1999. 14th IEEE International Conference on.
Conference_Location :
Cocoa Beach, FL
Print_ISBN :
0-7695-0415-9
DOI :
10.1109/ASE.1999.802089