Sewordsim: Software-specific word similarity database

Measuring the similarity of words is important in accurately representing and comparing documents, and thus improves the results of many natural language processing (NLP) tasks. The NLP community has proposed various measurements based on WordNet, a lexical database that contains rela-tionships between many pairs of words. Recently, a number of techniques have been proposed to address software engi-neering issues such as code search and fault localization that require understanding natural language documents, and a measure of word similarity could improve their results. How-ever, WordNet only contains information about words senses in general-purpose conversation, which often differ from word senses in a software-engineering context, and the software-specific word similarity resources that have been developed rely on data sources containing only a limited range of words and word uses. In recent work, we have proposed a word similarity re-source based on information collected automatically from StackOverflow. We have found that the results of this re-source are given scores on a 3-point Likert scale that are over 50 % higher than the results of a resource based on WordNet. In this demo paper, we review our data collection method-ology and propose a Java API to make the resulting word similarity resource useful in practice. The SEWordSim database and related information can be found a