short-paper

Merging smell detectors: evidence on the agreement of multiple tools

Authors:

Apostolos Ichtsis,

Nikolaos Mittas,

Apostolos Ampatzoglou,

Alexander ChatzigeorgiouAuthors Info & Claims

TechDebt '22: Proceedings of the International Conference on Technical Debt

Pages 61 - 65

https://doi.org/10.1145/3524843.3528089

Published: 16 August 2022 Publication History

Abstract

Technical Debt estimation relies heavily on the use of static analysis tools looking for violations of pre-defined rules. Largely, Technical Debt principal is attributed to the presence of low-level code smells, unavoidably tying the effort for fixing the problems with mere coding inefficiencies. At the same time, despite their simple definition, the detection of most code smells is non-trivial and subjective, rendering the assessment of Technical Debt principal dubious. To this end, we have revisited the literature on code smell detection approaches backed by tools and developed an Eclipse plugin that incorporates six code smell detection approaches. The combined application of various smell detectors can increase the certainty of identifying actual code smells that matter to the development team. We also conduct a case study to investigate the agreement among the employed code smell detectors. To our surprise the level of agreement is quite low even for relatively simple code smells, threating the validity of existing TD analysis tools and calling for increased attention to the precise specification of code and design level issues.

Source code: https://github.com/apostolisich/SmellDetectorMerger

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Cited By

Huang ZYu HFan GShao ZZhou ZLi M(2024)On the effectiveness of developer features in code smell prioritizationJournal of Systems and Software10.1016/j.jss.2024.111968210:COnline publication date: 25-Jun-2024
https://dl.acm.org/doi/10.1016/j.jss.2024.111968
Huang ZYu HFan GShao ZLi MLiang Y(2024)Aligning XAI explanations with software developers’ expectationsExpert Systems with Applications: An International Journal10.1016/j.eswa.2023.121640238:PAOnline publication date: 27-Feb-2024
https://dl.acm.org/doi/10.1016/j.eswa.2023.121640
Santana AFigueiredo EAlves Pereira JGarcia A(2024)An exploratory evaluation of code smell agglomerationsSoftware Quality Journal10.1007/s11219-024-09680-632:4(1375-1412)Online publication date: 11-Jul-2024
https://doi.org/10.1007/s11219-024-09680-6
Show More Cited By

Index Terms

Merging smell detectors: evidence on the agreement of multiple tools
1. Social and professional topics
  1. Professional topics
    1. Management of computing and information systems
      1. System management
        Quality assurance
2. 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

TechDebt '22: Proceedings of the International Conference on Technical Debt

May 2022

89 pages

ISBN:9781450393041

DOI:10.1145/3524843

General Chair:
Neil Ernst
University of Victoria, Canada
,
Program Chairs:
Valentina Lenarduzzi
University of Oulu, Finland
,
Tushar Sharma
Dalhousie University, Canada

Copyright © 2022 ACM.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 August 2022

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Horizon Europe

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TechDebt '22

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SIGSOFT

TechDebt '22: International Conference on Technical Debt

May 16 - 18, 2022

Pennsylvania, Pittsburgh

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Overall Acceptance Rate 14 of 31 submissions, 45%

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Cited By

Huang ZYu HFan GShao ZZhou ZLi M(2024)On the effectiveness of developer features in code smell prioritizationJournal of Systems and Software10.1016/j.jss.2024.111968210:COnline publication date: 25-Jun-2024
https://dl.acm.org/doi/10.1016/j.jss.2024.111968
Huang ZYu HFan GShao ZLi MLiang Y(2024)Aligning XAI explanations with software developers’ expectationsExpert Systems with Applications: An International Journal10.1016/j.eswa.2023.121640238:PAOnline publication date: 27-Feb-2024
https://dl.acm.org/doi/10.1016/j.eswa.2023.121640
Santana AFigueiredo EAlves Pereira JGarcia A(2024)An exploratory evaluation of code smell agglomerationsSoftware Quality Journal10.1007/s11219-024-09680-632:4(1375-1412)Online publication date: 11-Jul-2024
https://doi.org/10.1007/s11219-024-09680-6
Nikolaidis NMittas NAmpatzoglou AFeitosa DChatzigeorgiou A(2023)A metrics-based approach for selecting among various refactoring candidatesEmpirical Software Engineering10.1007/s10664-023-10412-w29:1Online publication date: 16-Dec-2023
https://dl.acm.org/doi/10.1007/s10664-023-10412-w

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