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Computational Analysis of Code Collaboration Pattern and Semantic Role


Affiliations
1 Software Engineering, University of Houston-Clear Lake, Houston, United States
2 Computer Science, Algoma University, Sault Ste. Marie, Canada
3 Mathematics and Engineering, San Jacinto College, Houston, United States
 

Software functionalities and behavior are accomplished by the cooperation of code artifacts. The understanding of this type of source code collaboration provides an important aid to the maintenance and evolution of legacy systems. However, the original collaboration design information is dispersed at the implementation level. The extraction of code artifacts' collaborations and the roles is therefore an important support in legacy software comprehension and design recovery. In this paper, we present a novel approach to efficiently recover and analyze code collaborations and semantic roles based on dynamic program analysis technique. We also demonstrate the software tools that we have developed to support our approach and illustrate the viability of our approach in a case study.

Keywords

Data Mining, Code Collaboration Pattern, Semantic Role, Design Recovery, Dynamic Program Analysis, Software Visualization, Reverse Engineering.
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  • Computational Analysis of Code Collaboration Pattern and Semantic Role

Abstract Views: 311  |  PDF Views: 141

Authors

Lei Wu
Software Engineering, University of Houston-Clear Lake, Houston, United States
Sharon White
Software Engineering, University of Houston-Clear Lake, Houston, United States
Yi Feng
Computer Science, Algoma University, Sault Ste. Marie, Canada
James Helm
Software Engineering, University of Houston-Clear Lake, Houston, United States
Nathanial Wiggins
Mathematics and Engineering, San Jacinto College, Houston, United States

Abstract


Software functionalities and behavior are accomplished by the cooperation of code artifacts. The understanding of this type of source code collaboration provides an important aid to the maintenance and evolution of legacy systems. However, the original collaboration design information is dispersed at the implementation level. The extraction of code artifacts' collaborations and the roles is therefore an important support in legacy software comprehension and design recovery. In this paper, we present a novel approach to efficiently recover and analyze code collaborations and semantic roles based on dynamic program analysis technique. We also demonstrate the software tools that we have developed to support our approach and illustrate the viability of our approach in a case study.

Keywords


Data Mining, Code Collaboration Pattern, Semantic Role, Design Recovery, Dynamic Program Analysis, Software Visualization, Reverse Engineering.