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short-paper

Revisiting context-based code smells prioritization: on supporting referred context

Authors:

Natthawute Sae-Lim,

Shinpei Hayashi,

Motoshi SaekiAuthors Info & Claims

XP '17: Proceedings of the XP2017 Scientific Workshops

Article No.: 3, Pages 1 - 5

https://doi.org/10.1145/3120459.3120463

Published: 22 May 2017 Publication History

Abstract

Because numerous code smells are revealed by code smell detectors, many attempts have been undertaken to mitigate related problems by prioritizing and filtering code smells. We earlier proposed a technique to prioritize code smells by leveraging the context of the developers, i.e., the modules that the developers plan to implement. Our empirical studies revealed that the results of code smells prioritized using our technique are useful to support developers' implementation on the modules they intend to change. Nonetheless, in software change processes, developers often navigate through many modules and refer to them before making actual changes. Such modules are important when considering the developers' context. Therefore, it is essential to ascertain whether our technique can also support developers on modules to which they are going to refer to make changes. We conducted an empirical study of an open source project adopting tools for recording developers' interaction history. Our results demonstrate that the code smells prioritized using our approach can also be used to support developers for modules to which developers are going to refer, irrespective of the need for modification.

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Cited By

Ponce FSoldani JTaramasco CAstudillo HBrogi A(2024)Triaging Microservice Security Smells, with TriSSProceedings of the 28th International Conference on Evaluation and Assessment in Software Engineering10.1145/3661167.3661282(698-706)Online publication date: 18-Jun-2024
https://dl.acm.org/doi/10.1145/3661167.3661282
Huang ZYu HFan GShao ZZhou ZLi M(2024)On the effectiveness of developer features in code smell prioritization: A replication studyJournal of Systems and Software10.1016/j.jss.2024.111968210(111968)Online publication date: Apr-2024
https://doi.org/10.1016/j.jss.2024.111968
Liu LLin GZhu LYang ZSong PWang XHu W(2024)Revisiting Code Smell Severity Prioritization using learning to rank techniquesExpert Systems with Applications10.1016/j.eswa.2024.123483249(123483)Online publication date: Sep-2024
https://doi.org/10.1016/j.eswa.2024.123483
Show More Cited By

Index Terms

Revisiting context-based code smells prioritization: on supporting referred context
1. Software and its engineering
  1. Software creation and management
    1. Software post-development issues
      1. Maintaining software

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Published In

cover image ACM Other conferences

XP '17: Proceedings of the XP2017 Scientific Workshops

May 2017

124 pages

ISBN:9781450352642

DOI:10.1145/3120459

Conference Chair:
Roberto Tonelli
University of Cagliari Italy

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 May 2017

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Short-paper

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Japan Society for the Promotion of Science

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XP '17 Workshops

XP '17 Workshops: Proceedings of the Scientific Workshops of XP2017

May 22 - 26, 2017

Cologne, Germany

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Overall Acceptance Rate 11 of 15 submissions, 73%

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Citations

Cited By

Ponce FSoldani JTaramasco CAstudillo HBrogi A(2024)Triaging Microservice Security Smells, with TriSSProceedings of the 28th International Conference on Evaluation and Assessment in Software Engineering10.1145/3661167.3661282(698-706)Online publication date: 18-Jun-2024
https://dl.acm.org/doi/10.1145/3661167.3661282
Huang ZYu HFan GShao ZZhou ZLi M(2024)On the effectiveness of developer features in code smell prioritization: A replication studyJournal of Systems and Software10.1016/j.jss.2024.111968210(111968)Online publication date: Apr-2024
https://doi.org/10.1016/j.jss.2024.111968
Liu LLin GZhu LYang ZSong PWang XHu W(2024)Revisiting Code Smell Severity Prioritization using learning to rank techniquesExpert Systems with Applications10.1016/j.eswa.2024.123483249(123483)Online publication date: Sep-2024
https://doi.org/10.1016/j.eswa.2024.123483
Huang ZYu HFan GShao ZLi MLiang Y(2024)Aligning XAI explanations with software developers’ expectations: A case study with code smell prioritizationExpert Systems with Applications10.1016/j.eswa.2023.121640238(121640)Online publication date: Mar-2024
https://doi.org/10.1016/j.eswa.2023.121640
Ponce FMalnati ANegro RFontana FAstudillo HBrogi ASoldani J(2024)SST: A Tool to Support the Triage of Security Smells in Microservice ApplicationsSN Computer Science10.1007/s42979-024-03372-55:8Online publication date: 4-Nov-2024
https://dl.acm.org/doi/10.1007/s42979-024-03372-5
Ponce FSoldani JAstudillo HBrogi A(2024)Towards Teamwise Informed Decisions On Microservice Security SmellsSoftware Architecture10.1007/978-3-031-70797-1_23(350-358)Online publication date: 1-Sep-2024
https://dl.acm.org/doi/10.1007/978-3-031-70797-1_23
Verma RKumar KVerma H(2023)Code smell prioritization in object‐oriented software systemsJournal of Software: Evolution and Process10.1002/smr.253635:12Online publication date: 29-Jan-2023
https://dl.acm.org/doi/10.1002/smr.2536
Alkharabsheh KAlawadi SIgnaim KZanoon NCrespo YManso ETaboada J(2022)Prioritization of god class design smell: A multi-criteria based approachJournal of King Saud University - Computer and Information Sciences10.1016/j.jksuci.2022.09.01134:10(9332-9342)Online publication date: Nov-2022
https://doi.org/10.1016/j.jksuci.2022.09.011
Huang ZShao ZFan GGao JZhou ZYang KYang X(2021)Predicting Community Smells’ Occurrence on Individual Developers by Sentiments2021 IEEE/ACM 29th International Conference on Program Comprehension (ICPC)10.1109/ICPC52881.2021.00030(230-241)Online publication date: May-2021
https://doi.org/10.1109/ICPC52881.2021.00030
SAE-LIM NHAYASHI SSAEKI M(2018)An Investigative Study on How Developers Filter and Prioritize Code SmellsIEICE Transactions on Information and Systems10.1587/transinf.2017KBP0006E101.D:7(1733-1742)Online publication date: 1-Jul-2018
https://doi.org/10.1587/transinf.2017KBP0006
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