A study of applying sequential-pattern mining to software version histories

• Main Authors: Kai-shiang Fan, 范凱翔
• Other Authors: Shi-jen Lin
• Format: Others
• Language: zh-TW
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/23036138690909505826

碩士 === 國立中央大學 === 資訊管理研究所 === 97 === The evolution of the modern software is continual. Although detailed information of the evolution of the software version is stored in the version control system (VCS), the understanding of more and more complex software structure is still finite. On the other hand, lines of code in the software project are usually hundreds of thousands, which makes the software maintenance a difficult problem. The researches of applying data mining techniques to VCS are usually based on association rules, which usually pass over the ordering information. As a result, by taking the time dimension of the software data from the Concurrent Version System (CVS) into consideration, this study uses the sequential-pattern mining technique to analyze and find out the potential sequence pattern. We expect the “entities” to be changed more precisely than those in previous researches and re-evaluate the sequence pattern for the users by means of a classification rule in order to provide the reference of the software maintenance in the future.