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Natural language processing (NLP) applied on issue trackers
Ellmann M.  NL4SE 2018 (Proceedings of the 4th ACM SIGSOFT International Workshop on NLP for Software Engineering, Lake Buena Vista, FL, Nov 4, 2018)38-41.2018.Type:Proceedings
Date Reviewed: Feb 28 2019

An attempt at an analytical account, this paper lists approaches related to the discovery of duplicates in software development issue descriptions.

The paper discusses the structure of issues that are posted in issue tracking systems for software development, and then provides a survey of different approaches that have been adopted to solve the problem of issue duplication by looking at the language used to describe the issue. The survey is split into sections on “Characteristic Analysis of Duplicates,” “Syntactic Analysis of Duplicates,” “Semantic Analysis of Duplicates,” and “Classification and Prediction of Duplicates.” In each of these sections, the author lists a number of papers that have contributed to the approach in question without analyzing them or commenting on their strengths and weaknesses.

Not very well written, with many typographical errors, this paper reads like an organized catalog of papers, with brief summaries about the approaches they adopt to discover duplicates in issue tracking systems.

Reviewer:  Mariana Damova Review #: CR146451 (1905-0188)
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