short-paper

Detecting and managing code smells: research and practice

Author:

Tushar SharmaAuthors Info & Claims

ICSE '18: Proceedings of the 40th International Conference on Software Engineering: Companion Proceeedings

Pages 546 - 547

https://doi.org/10.1145/3183440.3183460

Published: 27 May 2018 Publication History

Abstract

Code smells indicate the presence of quality problems that make the software hard to maintain and evolve. A software development team can keep their software maintainable by identifying smells and refactor them. In the first part of the session, we present a comprehensive overview of the literature concerning smells covering various dimensions of the metaphor including defining characteristics, classification, types, as well as causes and impacts of smells. In the second part, we delve into the details of smell detection methods prevailed currently both in research prototypes and industrial tools. The final part present actionable and pragmatic strategies for practitioners to avoid, detect, and eradicate smells from their codebase.

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Tushar Sharma, Marios Fragkoulis, Stamatia Rizou, Magiel Bruntink, and Diomidis Spinellis. 2018. Smelly Relations: Measuring and Understanding Database Schema Quality. In Proceedings of 40th International Conference on Software Engineering (ICSE '18).

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Cited By

Taleb RHallé SKhoury R(2024)Uncertainty in runtime verificationComputer Science Review10.1016/j.cosrev.2023.10059450:COnline publication date: 4-Mar-2024
https://dl.acm.org/doi/10.1016/j.cosrev.2023.100594
Anquetil NEtien AAndreo GDucasse S(2019)Decomposing God Classes at Siemens2019 IEEE International Conference on Software Maintenance and Evolution (ICSME)10.1109/ICSME.2019.00027(169-180)Online publication date: Sep-2019
https://doi.org/10.1109/ICSME.2019.00027
Jesudoss AManeesha SLakshmi naga durga T(2019)Identification of Code Smell Using Machine Learning2019 International Conference on Intelligent Computing and Control Systems (ICCS)10.1109/ICCS45141.2019.9065317(54-58)Online publication date: May-2019
https://doi.org/10.1109/ICCS45141.2019.9065317

Index Terms

Detecting and managing code smells: research and practice
1. Software and its engineering
  1. Software creation and management
    1. Software post-development issues
      1. Maintaining software
  2. Software notations and tools
    1. Software maintenance tools

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Published In

cover image ACM Conferences

ICSE '18: Proceedings of the 40th International Conference on Software Engineering: Companion Proceeedings

May 2018

231 pages

ISBN:9781450356633

DOI:10.1145/3183440

Conference Chair:
Michel Chaudron
Chalmers University of Technology, University of Gothenburg, Sweden
,
General Chair:
Ivica Crnkovic
Chalmers University of Technology, University of Gothenburg, Sweden
,
Program Chairs:
Marsha Chechik
University of Toronto, Canada
,
Mark Harman
Facebook and University College London, United Kingdom

Copyright © 2018 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 ACM 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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SIGSOFT: ACM Special Interest Group on Software Engineering
IEEE-CS: Computer Society

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 May 2018

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Marie Sklodowska-Curie Innovative Training Networks

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ICSE '18

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SIGSOFT
IEEE-CS

ICSE '18: 40th International Conference on Software Engineering

May 27 - June 3, 2018

Gothenburg, Sweden

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Overall Acceptance Rate 276 of 1,856 submissions, 15%

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Cited By

Taleb RHallé SKhoury R(2024)Uncertainty in runtime verificationComputer Science Review10.1016/j.cosrev.2023.10059450:COnline publication date: 4-Mar-2024
https://dl.acm.org/doi/10.1016/j.cosrev.2023.100594
Anquetil NEtien AAndreo GDucasse S(2019)Decomposing God Classes at Siemens2019 IEEE International Conference on Software Maintenance and Evolution (ICSME)10.1109/ICSME.2019.00027(169-180)Online publication date: Sep-2019
https://doi.org/10.1109/ICSME.2019.00027
Jesudoss AManeesha SLakshmi naga durga T(2019)Identification of Code Smell Using Machine Learning2019 International Conference on Intelligent Computing and Control Systems (ICCS)10.1109/ICCS45141.2019.9065317(54-58)Online publication date: May-2019
https://doi.org/10.1109/ICCS45141.2019.9065317

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