Using Model Combinatorial Methods to Analyze Program Size Variation in Open-Source Software

• Main Authors: Huang, Shih-Min, 黃詩閔
• Other Authors: Huang, Chin-Yu
• Format: Others
• Language: en_US
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/95439192542340764810

碩士 === 國立清華大學 === 資訊系統與應用研究所 === 101 === As one of the most important internal attributes of software systems, the estimation of software size is crucial to project success. Typically, software size can be described by the length, functionality, or complexity of the file, but in practice many people still use lines of code (LOC) as a measure of software size since LOC is widely used and can be easily measured upon project completion. In this paper, we used a linear combination model with modified Bayesian inference weight decision approach (MBIWDA) to analyze the size distribution and software size-change rate of Open-Source Software (OSS). Furthermore, we investigated the factors that influenced the software size-change rate using the quantile regression (QR) model. Experiments were conducted using real data of several OSS projects, and evaluation results showed that the linear combination model with the MBIWDA had a outstanding capability of fitting the distribution of the software size-change rate. Finally, the analysis of QR demonstrated that faults with higher severity had an impact on LOC changes in the early stage. These findings offer an alternative view and reveal different issues of software sizing.