Semantic patterns extraction of code smells: Retrieving the solutions of bugs
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review
Details
| Original language | English |
|---|---|
| Title of host publication | SSSME-2019 |
| Subtitle of host publication | Joint Proceedings of the Inforte Summer School on Software Maintenance and Evolution |
| Publisher | CEUR-WS |
| Pages | 71-77 |
| Number of pages | 7 |
| Publication status | Published - 2019 |
| Publication type | A4 Article in a conference publication |
| Event | Joint of the Summer School on Software Maintenance and Evolution - Tampere, Finland Duration: 2 Sep 2019 → 4 Sep 2019 |
Publication series
| Name | CEUR Workshop Proceedings |
|---|---|
| Volume | 2520 |
| ISSN (Print) | 1613-0073 |
Conference
| Conference | Joint of the Summer School on Software Maintenance and Evolution |
|---|---|
| Country | Finland |
| City | Tampere |
| Period | 2/09/19 → 4/09/19 |
Abstract
The understanding of code smells have exerted profound influence in the quality and the performance of programming codes. There are various type of code smells require various solutions. In order to interpret the solutions available in code smells, this research uses NLP (natural language programming) techniques to comprehend contents of messages from Technical Debt Dataset. Based on phrase structure rules, semantic patterns were extracted from the Dataset to build connection between trigger words and dependency tree. Verb Phrases are considered as the actions taken by programmers encountering code smells.
ASJC Scopus subject areas
Keywords
- Code smells, NLP, Phrase structure rules, Semantic patterns