Ranking crowd knowledge to assist software development

Abstract

StackOverflow.com (SO) is a Question and Answer service oriented to support collaboration among developers in order to help them solving their issues related to software development. In SO, developers post questions related to a programming topic and other members of the site can provide answers to help them. The information available on this type of service is also known as "crowd knowledge" and currently is one important trend in supporting activities related to software development and maintenance. We present an approach that makes use of "crowd knowledge" available in SO to recommend information that can assist developers in their activities. This strategy recommends a ranked list of pairs of questions/answers from SO based on a query (list of terms). The ranking criteria is based on two main aspects: the textual similarity of the pairs with respect to the query (the developer's problem) and the quality of the pairs. Moreover, we developed a classifier to consider only "how-to" posts. We conducted an experiment considering programming problems on three different topics (Swing, Boost and LINQ) widely used by the software development community to evaluate the proposed recommendation strategy. The results have shown that for 77.14% of the assessed activities, at least one recommended pair proved to be useful concerning the target programming problem. Moreover, for all activities, at least one recommended pair had a source code snippet considered reproducible or almost reproducible.