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Semantic patterns extraction of code smells: Retrieving the solutions of bugs

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Standard

Semantic patterns extraction of code smells : Retrieving the solutions of bugs. / Zhang, Boyang.

SSSME-2019: Joint Proceedings of the Inforte Summer School on Software Maintenance and Evolution. CEUR-WS, 2019. p. 71-77 (CEUR Workshop Proceedings; Vol. 2520).

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Harvard

Zhang, B 2019, Semantic patterns extraction of code smells: Retrieving the solutions of bugs. in SSSME-2019: Joint Proceedings of the Inforte Summer School on Software Maintenance and Evolution. CEUR Workshop Proceedings, vol. 2520, CEUR-WS, pp. 71-77, Joint of the Summer School on Software Maintenance and Evolution, Tampere, Finland, 2/09/19.

APA

Zhang, B. (2019). Semantic patterns extraction of code smells: Retrieving the solutions of bugs. In SSSME-2019: Joint Proceedings of the Inforte Summer School on Software Maintenance and Evolution (pp. 71-77). (CEUR Workshop Proceedings; Vol. 2520). CEUR-WS.

Vancouver

Zhang B. Semantic patterns extraction of code smells: Retrieving the solutions of bugs. In SSSME-2019: Joint Proceedings of the Inforte Summer School on Software Maintenance and Evolution. CEUR-WS. 2019. p. 71-77. (CEUR Workshop Proceedings).

Author

Zhang, Boyang. / Semantic patterns extraction of code smells : Retrieving the solutions of bugs. SSSME-2019: Joint Proceedings of the Inforte Summer School on Software Maintenance and Evolution. CEUR-WS, 2019. pp. 71-77 (CEUR Workshop Proceedings).

Bibtex - Download

@inproceedings{d0903db196a648d4a14f3d71268f172c,
title = "Semantic patterns extraction of code smells: Retrieving the solutions of bugs",
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.",
keywords = "Code smells, NLP, Phrase structure rules, Semantic patterns",
author = "Boyang Zhang",
note = "jufoid=53269",
year = "2019",
language = "English",
series = "CEUR Workshop Proceedings",
publisher = "CEUR-WS",
pages = "71--77",
booktitle = "SSSME-2019",

}

RIS (suitable for import to EndNote) - Download

TY - GEN

T1 - Semantic patterns extraction of code smells

T2 - Retrieving the solutions of bugs

AU - Zhang, Boyang

N1 - jufoid=53269

PY - 2019

Y1 - 2019

N2 - 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.

AB - 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.

KW - Code smells

KW - NLP

KW - Phrase structure rules

KW - Semantic patterns

M3 - Conference contribution

T3 - CEUR Workshop Proceedings

SP - 71

EP - 77

BT - SSSME-2019

PB - CEUR-WS

ER -