An Analysis of Problem-Solving Patterns in Open Source Software

Abstract

Open Source Software (OSS) has become an important environment where developers can create, exchange, and improve reusable software assets by collaborating with other developers. Although developers may find useful software assets to reuse from OSS for their projects, they usually experience difficulties in solving problems that occur while integrating the assets to their own software. We investigated data from major open source environments such as Sourceforge. net and GitHub, and learned that there is a common pattern of solving reuse-related problems in OSS. To analyze the pattern in detail, we have developed an ontological model to formally represent the symptoms and causes of the reuse-related problems, and the correlations between them. Based on this model, we collected data from Sourceforge. net, and built a knowledge base for the most common problem type. We extracted the core types of symptoms and causes for the problem type and calculated the number of correlations between the types of symptoms and causes. We found that there exist correlations between the symptoms and causes that are extracted from the discussion threads for the problem type, and about 60% of them are statistically significant. We also conducted a study to understand the effective timing of recommending solutions to the developers by analyzing the recall rates of finding the causes of the problems in a timeline. We figured that most of the important causes of a problem are discussed at the beginning of the forum discussion. This leads us to the conclusion that recommending the causes of a problem early by using our knowledge framework may help developers spend less amount of time to solve the problem (around 50% less time than solving the problem without using our framework).