Automated construction of a software-specific word similarity database

Yuan Tian 1 David Lo 1 Julia Lawall 2, 3
2 Whisper - Well Honed Infrastructure Software for Programming Environments and Runtimes
LIP6 - Laboratoire d'Informatique de Paris 6, Inria de Paris
3 Regal - Large-Scale Distributed Systems and Applications
LIP6 - Laboratoire d'Informatique de Paris 6, Inria Paris-Rocquencourt
Abstract : Many automated software engineering approaches, including code search, bug report categorization, and duplicatebug report detection, measure similarities between two documents by analyzing natural language contents. Often different words are used to express the same meaning and thus measuring similarities using exact matching of words is insufficient. To solve this problem, past studies have shown the need to measure the similarities between pairs of words. To meet this need, the natural language processing community has built WordNet which is a manually constructed lexical database that records semantic relations among words and can be used to measure how similar two words are. However, WordNet is a general purpose resource, and often does not contain software-specific words. Also, the meanings of words in WordNet are often different than when they are used in software engineering context. Thus, there is a need for a software-specific WordNet-like resource that can measure similarities of words.In this work, we propose an automated approach that builds a software-specific WordNet like resource, named WordSim-SE-DB, by leveraging the textual contents of posts in StackOverflow. Our approach measures the similarity of words by computing the similarities of the weighted co-occurrences of these words with three types of words in the textual corpus. We have evaluated our approach on a set of software-specific words and compared our approach with an existing WordNet-based technique (WordNet-res) to return top-k most similar words.Human judges are used to evaluate the effectiveness of the two techniques. We find that WordNet-res returns no result for 55% of the queries. For the remaining queries, WordNet-res returns significantly poorer results.
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Contributor : Julia Lawall <>
Submitted on : Friday, November 21, 2014 - 5:48:04 PM
Last modification on : Thursday, March 21, 2019 - 2:39:44 PM



Yuan Tian, David Lo, Julia Lawall. Automated construction of a software-specific word similarity database. 2014 Software Evolution Week - IEEE Conference on Software Maintenance, Reengineering, and Reverse Engineering, CSMR-WCRE, Feb 2014, Antwerp, Belgium. pp.44-53, ⟨10.1109/CSMR-WCRE.2014.6747213⟩. ⟨hal-01086077⟩



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