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Article

Domain matters: bringing further evidence of the relationships among anti-patterns, application domains, and quality-related metrics in Java mobile apps

Authors:

Mario Linares-Vásquez,

Collin McMillan,

Aminata Sabané,

Denys Poshyvanyk,

Yann-Gaël GuéhéneucAuthors Info & Claims

ICPC 2014: Proceedings of the 22nd International Conference on Program Comprehension

Pages 232 - 243

https://doi.org/10.1145/2597008.2597144

Published: 02 June 2014 Publication History

Abstract

Some previous work began studying the relationship between application domains and quality, in particular through the prevalence of code and design smells (e.g., anti-patterns). Indeed, it is generally believed that the presence of these smells degrades quality but also that their prevalence varies across domains. Though anecdotal experiences and empirical evidence gathered from developers and researchers support this belief, there is still a need to further deepen our understanding of the relationship between application domains and quality. Consequently, we present a large-scale study that investigated the systematic relationships between the presence of smells and quality-related metrics computed over the bytecode of 1,343 Java Mobile Edition applications in 13 different application domains. Although, we did not find evidence of a correlation between smells and quality- related metrics, we found (1) that larger differences exist between metric values of classes exhibiting smells and classes without smells and (2) that some smells are commonly present in all the domains while others are most prevalent in certain domains

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Cited By

Pontillo VPalomba FFerrucci F(2024)Test Code Flakiness in Mobile Apps: The Developer’s PerspectiveInformation and Software Technology10.1016/j.infsof.2023.107394168(107394)Online publication date: Apr-2024
https://doi.org/10.1016/j.infsof.2023.107394
Abidi MRahman MOpenja MKhomh F(2024)Design smells in multi-language systems and bug-proneness: a survival analysisEmpirical Software Engineering10.1007/s10664-024-10476-229:5Online publication date: 3-Jul-2024
https://doi.org/10.1007/s10664-024-10476-2
Zhong YShi MHe JFang CChen Z(2023)Security‐based code smell definition, detection, and impact quantification in AndroidSoftware: Practice and Experience10.1002/spe.325753:11(2296-2321)Online publication date: 9-Sep-2023
https://doi.org/10.1002/spe.3257
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Index Terms

Domain matters: bringing further evidence of the relationships among anti-patterns, application domains, and quality-related metrics in Java mobile apps
1. Social and professional topics
  1. Professional topics
    1. Management of computing and information systems
      1. Software management
        Software maintenance
2. Software and its engineering
  1. Software creation and management
    1. Software post-development issues

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Published In

cover image ACM Conferences

ICPC 2014: Proceedings of the 22nd International Conference on Program Comprehension

June 2014

325 pages

ISBN:9781450328791

DOI:10.1145/2597008

General Chair:
Chanchal K. Roy
University of Saskatchewan, Canada
,
Program Chairs:
Andrew Begel
Microsoft Research, USA
,
Leon Moonen
Simula Research Laboratory, Norway

Copyright © 2014 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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Published: 02 June 2014

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June 2 - 3, 2014

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Cited By

Pontillo VPalomba FFerrucci F(2024)Test Code Flakiness in Mobile Apps: The Developer’s PerspectiveInformation and Software Technology10.1016/j.infsof.2023.107394168(107394)Online publication date: Apr-2024
https://doi.org/10.1016/j.infsof.2023.107394
Abidi MRahman MOpenja MKhomh F(2024)Design smells in multi-language systems and bug-proneness: a survival analysisEmpirical Software Engineering10.1007/s10664-024-10476-229:5Online publication date: 3-Jul-2024
https://doi.org/10.1007/s10664-024-10476-2
Zhong YShi MHe JFang CChen Z(2023)Security‐based code smell definition, detection, and impact quantification in AndroidSoftware: Practice and Experience10.1002/spe.325753:11(2296-2321)Online publication date: 9-Sep-2023
https://doi.org/10.1002/spe.3257
Gupta RSingh S(2022)Using Machine Learning for Inter-smell Detection: A Feasibility StudyArtificial Intelligence and Data Science10.1007/978-3-031-21385-4_25(291-305)Online publication date: 14-Dec-2022
https://doi.org/10.1007/978-3-031-21385-4_25
Sztwiertnia SGrübel MChouchane ASokolowski DNarasimhan KMezini MWang SXie XMa L(2021)Impact of programming languages on machine learning bugsProceedings of the 1st ACM International Workshop on AI and Software Testing/Analysis10.1145/3464968.3468408(9-12)Online publication date: 12-Jul-2021
https://dl.acm.org/doi/10.1145/3464968.3468408
Abidi MRahman MOpenja MKhomh F(2021)Are Multi-Language Design Smells Fault-Prone? An Empirical StudyACM Transactions on Software Engineering and Methodology10.1145/343269030:3(1-56)Online publication date: 11-Feb-2021
https://dl.acm.org/doi/10.1145/3432690
Sobrinho EDe Lucia AMaia M(2021)A Systematic Literature Review on Bad Smells–5 W's: Which, When, What, Who, WhereIEEE Transactions on Software Engineering10.1109/TSE.2018.288097747:1(17-66)Online publication date: 1-Jan-2021
https://doi.org/10.1109/TSE.2018.2880977
Yu JMao CYe X(2021)A Novel Tree-based Neural Network for Android Code Smells Detection2021 IEEE 21st International Conference on Software Quality, Reliability and Security (QRS)10.1109/QRS54544.2021.00083(738-748)Online publication date: Dec-2021
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Alkharabsheh KCrespo YFernández-Delgado MViqueira JTaboada J(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
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Alshemaimri BElmasri RAlsahfi TAlmotairi M(2021)A survey of problematic database code fragments in software systemsEngineering Reports10.1002/eng2.124413:10Online publication date: 11-Jul-2021
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