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An exploratory study to investigate the impact of conceptualization in god class detection

Published: 14 April 2013 Publication History
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  • Abstract

    Context: The concept of code smells is widespread in Software Engineering. However, in spite of the many discussions and claims about them, there are few empirical studies to support or contest these ideas. In particular, the study of the human perception of what is a code smell and how to deal with it has been mostly neglected. Objective: To build empirical support to understand the effect of god classes, one of the most known code smells. In particular, this paper focuses on how conceptualization affects identification of god classes, i.e., how different people perceive the god class concept. Method: A controlled experiment that extends and builds upon another empirical study about how humans detect god classes [19]. Our study: i) deepens and details some of the research questions of the previous study, ii) introduces a new research question and, iii) when possible, compares the results of both studies. Result: Our findings show that participants have different personal criteria and preferences in choosing drivers to identify god classes. The agreement between participants is not high, which is in accordance with previous studies. Conclusion: This study contributes to expand the empirical data about the human perception of code smells. It also presents a new way to evaluate effort and distraction in experiments through the use of automatic logging of participant actions.

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    Cited By

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    • (2023)Selection of human evaluators for design smell detection using dragonfly optimization algorithm: An empirical studyInformation and Software Technology10.1016/j.infsof.2022.107120155(107120)Online publication date: Mar-2023
    • (2022)Developers’ perception matters: machine learning to detect developer-sensitive smellsEmpirical Software Engineering10.1007/s10664-022-10234-227:7Online publication date: 12-Oct-2022
    • (2022)Building empirical knowledge on the relationship between code smells and design patterns: An exploratory studyJournal of Software: Evolution and Process10.1002/smr.248734:9Online publication date: 21-Jul-2022
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    cover image ACM Other conferences
    EASE '13: Proceedings of the 17th International Conference on Evaluation and Assessment in Software Engineering
    April 2013
    268 pages
    ISBN:9781450318488
    DOI:10.1145/2460999
    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]

    Sponsors

    • Centro de Informatica - UFPE: Centro de Informatica - UFPE
    • SBC: Brazilian Computer Society
    • CNPq: Conselho Nacional de Desenvolvimento Cientifico e Tecn
    • CAPES: Brazilian Higher Education Funding Council

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 14 April 2013

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    Author Tags

    1. code smell
    2. controlled experiment
    3. god class

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    EASE '13
    Sponsor:
    • Centro de Informatica - UFPE
    • SBC
    • CNPq
    • CAPES

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    EASE '13 Paper Acceptance Rate 31 of 94 submissions, 33%;
    Overall Acceptance Rate 71 of 232 submissions, 31%

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    • (2023)Selection of human evaluators for design smell detection using dragonfly optimization algorithm: An empirical studyInformation and Software Technology10.1016/j.infsof.2022.107120155(107120)Online publication date: Mar-2023
    • (2022)Developers’ perception matters: machine learning to detect developer-sensitive smellsEmpirical Software Engineering10.1007/s10664-022-10234-227:7Online publication date: 12-Oct-2022
    • (2022)Building empirical knowledge on the relationship between code smells and design patterns: An exploratory studyJournal of Software: Evolution and Process10.1002/smr.248734:9Online publication date: 21-Jul-2022
    • (2021)Exploratory study of the impact of project domain and size category on the detection of the God class design smellSoftware Quality Journal10.1007/s11219-021-09550-5Online publication date: 31-Mar-2021
    • (2020)Applying coupling and cohesion concepts in object-oriented software: a controlled experimentProceedings of the XIX Brazilian Symposium on Software Quality10.1145/3439961.3439969(1-10)Online publication date: 1-Dec-2020
    • (2018)CodexComputer Standards & Interfaces10.1016/j.csi.2018.02.00359:C(35-44)Online publication date: 1-Aug-2018
    • (2017)Investigating factors that affect the human perception on god class detection: an analysis based on a family of four controlled experimentsJournal of Software Engineering Research and Development10.1186/s40411-017-0042-05:1Online publication date: 28-Nov-2017
    • (2017)A Comparative Study of Model-Driven Approaches For Scoping and Planning ExperimentsProceedings of the 21st International Conference on Evaluation and Assessment in Software Engineering10.1145/3084226.3084258(78-87)Online publication date: 15-Jun-2017
    • (2017)Smells are sensitive to developers!Proceedings of the 25th International Conference on Program Comprehension10.1109/ICPC.2017.32(110-120)Online publication date: 20-May-2017
    • (2017)A Systematic Literature Review: Code Bad Smells in Java Source CodeComputational Science and Its Applications – ICCSA 201710.1007/978-3-319-62404-4_49(665-682)Online publication date: 15-Jul-2017
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