HyperAST: Enabling Efficient Analysis of Software Histories at Scale-Reference-Cited by-同舟云学术

HyperAST: Enabling Efficient Analysis of Software Histories at Scale

Published:2022-10-10 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering
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Author:

Le Dilavrec Quentin¹^ORCID,Khelladi Djamel Eddine²^ORCID,Blouin Arnaud³^ORCID,Jézéquel Jean-Marc⁴^ORCID

Affiliation:

1. Univ. Rennes, France and IRISA, France

2. CNRS, France and Univ Rennes, France

3. INSA Rennes, France and Univ Rennes, France

4. Univ Rennes, France and IRISA, France

Funder

Agence Nationale de la Recherche

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3551349.3560423

Reference51 articles.

1. Redundancy-free analysis of multi-revision software artifacts

2. A Literature Review of Automatic Traceability Links Recovery for Software Change Impact Analysis

3. TraceME: Traceability Management in Eclipse

4. Space/time trade-offs in hash coding with allowable errors

5. Arnaud Blouin , Valéria Lelli , Benoit Baudry , and Fabien Coulon . 2018. User Interface Design Smell: Automatic Detection and Refactoring of Blob Listeners. Information and Software Technology 102 (May 2018 ), 49–64. Arnaud Blouin, Valéria Lelli, Benoit Baudry, and Fabien Coulon. 2018. User Interface Design Smell: Automatic Detection and Refactoring of Blob Listeners. Information and Software Technology 102 (May 2018), 49–64.

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1. 7 Dimensions of software change patterns;Scientific Reports;2024-03-13

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