Dolphin: A search engine for OSS based on crowd discussions across communities

Abstract

The global open source software resources have become an Internet-scale repository, which provide abundant resources for software reuse. However, how to locate the desired resource efficiently and accurately from such large amounts is quite a challenge problem. Most of recent works barely focus on the semantic similarity by analyzing the software itself, which often result in inappropriate ranking. In this paper, we propose Dolphin, a global OSS search engine, which leverage the crowd discussions around OSS across communities for optimizing software ranking. Dolphin employs the crowd wisdom as an important factor and combines it with the semantic similarity to optimize search results ranking. We implement an OSS search engine based on the proposed approach, which provides online service continuously. Extensive experiments and user studies suggest the effectiveness of our approach.