Mining Open Source Component Behavior for Reuse Evaluation

Authors:
Ji Wu;Chun Wang;Xiao-Xia Jia;Chao Liu
Affiliations:
School of Computer Science and Engineering, BeiHang University, Beijing, China 100083;School of Computer Science and Engineering, BeiHang University, Beijing, China 100083;School of Computer Science and Engineering, BeiHang University, Beijing, China 100083;School of Computer Science and Engineering, BeiHang University, Beijing, China 100083
Venue:
ICSR '08 Proceedings of the 10th international conference on Software Reuse: High Confidence Software Reuse in Large Systems
Year:
2008

Citing 5
Cited 0

Certification of Software Components

IEEE Transactions on Software Engineering
COTS Evaluation and Selection

ICSM '98 Proceedings of the International Conference on Software Maintenance
Mission-Critical Development with Open Source Software: Lessons Learned

IEEE Software
Information System for Evaluations of COTS

SERA '05 Proceedings of the Third ACIS Int'l Conference on Software Engineering Research, Management and Applications
Java Object Behavior Modeling and Visualization

ICSEA '06 Proceedings of the International Conference on Software Engineering Advances

Quantified Score

Hi-index	0.00

Visualization

Abstract

Reusing Open Source Component (OSC) has become more and more popular in developing in-house applications. Before integrating an OSC into project, the component has to be evaluated according to the project. This paper proposes the usage and dependency model to help understand OSC from the interactions with its usage context. The usage and dependency model extends the traditional usage model with the context dependency and backward dependency, which are widely observed in open source project. Based on the usage model, this paper proposes three metrics to measure the interaction complexity. To construct the usage and dependency model, the invocation matrix and the mining algorithm are proposed. The framework component in open source project Junit 4.4 is selected to validate this research.