Aged to Perfection? Analyzing the Impact of Years of Experience on Code Quality
Abstract
The association between developer experience and code quality is a significant debate within the software engineering community. To explore this relationship, we quantitatively evaluated 401 GitHub software repositories in JavaScript, PHP, and Python, maintained by 98 developers with Workana profiles – a freelancing platform. For quality assessment, we rely on SonarQube, a widely adopted tool in both industry and academia. We analyzed several dimensions, such as the programming languages and severity (high, medium, and low) of maintainability and reliability issues. We observed that developers with the highest level of experience presented code with fewer issues. However, developers with intermediate level of experience presented more code quality issues than their novice and experienced counterparts, revealing a more complex and nuanced relationship between level of experience and code quality. Despite that, our analysis did not indicate significant statistical differences between the density of the issue at varying levels of experience, suggesting that other factors may also contribute to code quality outcomes. This study contributes to an open question with implications for software engineering recruitment and code quality assurance.We provide a new dataset of developers and their projects based on recent data. All extracted data and accompanying scripts are available, aiming to enable further replications of our study.
Keywords:
Code quality, developer experience, repository mining
References
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Raymond PL Buse and Westley R Weimer. 2009. Learning a metric for code readability. IEEE Transactions on software engineering 36, 4 (2009), 546–558.
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Jacob Cohen. 1988. Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Routledge, New York, NY, USA.
Francisco Gomes de Oliveira Neto, Richard Torkar, Robert Feldt, Lucas Gren, Carlo A Furia, and Ziwei Huang. 2019. Evolution of statistical analysis in empirical software engineering research: Current state and steps forward. Journal of Systems and Software 156 (2019), 246–267.
Massimiliano Di Penta, Luigi Cerulo, and Lerina Aversano. 2009. The life and death of statically detected vulnerabilities: An empirical study. Information and Software Technology 51, 10 (2009), 1469–1484.
O. Dieste et al. 2017. Empirical evaluation of the effects of experience on code quality and programmer productivity: an exploratory study. Empirical Software Engineering 22, 5, 2457–2542.
Nikolina Dragicevic, Matantsev Maxim, and Artem Kruglov. 2023. A Study of Effective Strategies for Personal Development and Success for Software Engineers. In 2023 IEEE 14th International Conference on Software Engineering and Service Science (ICSESS). IEEE, 101–104.
K Anders Ericsson, Robert R Hoffman, Aaron Kozbelt, and A Mark Williams. 2018. The Cambridge handbook of expertise and expert performance. Cambridge University Press.
Jefferson G. Lopes, Johnatan Alves, and Eduardo Figueiredo. 2022. EXTRACTPRO: A Data Mining Tool for Developer Profile Generation based on Source Code Analysis. In Proceedings of the XXXVI Brazilian Symposium on Software Engineering. 112–117.
E. Giger, M. Pinzger, and H. C. Gall. 2011. Comparing fine-grained source code changes and code churn for bug prediction. In Proceedings of Data Archiving and Networked Services (DANS).
Nicolas E Gold and Jens Krinke. 2022. Ethics in the mining of software repositories. Empirical Software Engineering 27, 1 (2022), 17.
Nora Honken. 2013. Dreyfus five-stage model of adult skills acquisition applied to engineering lifelong learning. In 2013 ASEE Annual Conference & Exposition. 23–443.
.. Khyber, Sikandar Ali, Fazli Wahid, S. Baseer, A. Alkhayyat, and Akram Al-Radaei. 2024. Smell-Aware Bug Classification. IEEE Access 12 (2024), 14061–14082. DOI: 10.1109/ACCESS.2023.3335175
S. Ozcan Kini and A. Tosun. 2018. Periodic Developer Metrics in Software Defect Prediction. In IEEE Xplore.
Barbara Kitchenham and Stuart Charters. 2007. Guidelines for Performing Systematic Literature Reviews in Software Engineering. Technical Report EBSE 2007-001. EBSE Technical Report. [link]
William H. Kruskal and W. Allen Wallis. 1952. Use of Ranks in One-Criterion Variance Analysis. J. Amer. Statist. Assoc. 47, 260 (Dec. 1952), 583–621.
Paul Luo Li, Amy J Ko, and Jiamin Zhu. 2015. What makes a great software engineer?. In 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering, Vol. 1. IEEE, 700–710.
Jefferson GM Lopes, Johnatan Oliveira, and Eduardo Figueiredo. 2024. Evaluating the Impact of Developer Experience on Code Quality: A Systematic Literature Review. In Congresso Ibero-Americano em Engenharia de Software (CIbSE). SBC, 166–180.
Ivano Malavolta, Roberto Verdecchia, Bojan Filipovic, Magiel Bruntink, and Patricia Lago. 2018. How maintainability issues of android apps evolve. In 2018 IEEE international conference on software maintenance and evolution (ICSME). IEEE, 334–344.
James Miller. 2004. Statistical significance testing—-a panacea for software technology experiments? Journal of Systems and Software 73, 2 (2004), 183–192.
O. Dieste et al. 2018. Empirical Evaluation of the Effects of Experience on Code Quality and Programmer Productivity: An Exploratory Study. In Proceedings of the 2018 International Conference on Software and System Process. 111–112.
Johnatan Oliveira, Maurício Souza, Matheus Flauzino, Rafael Durelli, and Eduardo Figueiredo. 2022. Can source code analysis indicate programming skills? a survey with developers. In International Conference on the Quality of Information and Communications Technology. Springer, 156–171.
Susanna Paloniemi. 2006. Experience, competence and workplace learning. Journal of Workplace Learning 18 (10 2006), 439–450. DOI: 10.1108/13665620610693006
Pandas. 2019. Python Data Analysis Library — pandas: Python Data Analysis Library. [link]. Accessed: Nov. 1, 2024.
Shravan Pargaonkar. 2023. Cultivating Software Excellence: The Intersection of Code Quality and Dynamic Analysis in Contemporary Software Development within the Field of Software Quality Engineering. International Journal of Science and Research (IJSR) (2023). DOI: 10.21275/sr23829092346
V. Piantadosi, S. Scalabrino, A. Serebrenik, N. Novielli, and R. Oliveto. 2023. Do attention and memory explain the performance of software developers? Empirical Software Engineering 28, 5 (Aug. 2023).
Alifia Puspaningrum, Muhammad Anis Al Hilmi, . Darsih, Muhamad Mustamiin, and Maulana Ilham Ginanjar. 2022. Vulnerable Source Code Detection Using Sonarcloud Code Analysis. In Proceedings of the 5th International Conference on Applied Science and Technology on Engineering Science. SCITEPRESS - Science and Technology Publications, 683–687. DOI: 10.5220/0011862600003575
Yilin Qiu, Weiqiang Zhang, Weiqin Zou, Jia Liu, and Qin Liu. 2015. An empirical study of developer quality. In 2015 IEEE International Conference on Software Quality, Reliability and Security-Companion. IEEE, 202–209.
Foyzur Rahman and Premkumar Devanbu. 2011. Ownership, experience and defects: a fine-grained study of authorship. In Proceedings of the 33rd International Conference on Software Engineering. 491–500.
Baishakhi Ray, Daryl Posnett, Vladimir Filkov, and Premkumar Devanbu. 2014. A large scale study of programming languages and code quality in github. In Proceedings of the 22nd ACM SIGSOFT international symposium on foundations of software engineering. 155–165.
María José Salamea and Carles Farré. 2019. Influence of developer factors on code quality: A data study. In 2019 IEEE 19th International Conference on Software Quality, Reliability and Security Companion (QRS-C). IEEE, 120–125.
Amanda Santana, Eduardo Figueiredo, and Juliana Alves Pereira. 2024. Unraveling the Impact of Code Smell Agglomerations on Code Stability. In 2024 IEEE International Conference on Software Maintenance and Evolution (ICSME). IEEE, 461–473.
Geanderson Santos, Amanda Santana, Gustavo Vale, and Eduardo Figueiredo. 2023. Yet another model! a study on model’s similarities for defect and code smells. In International Conference on Fundamental Approaches to Software Engineering. Springer Nature Switzerland Cham, 282–305.
Sigrid Schefer-Wenzl and I. Miladinovic. 2019. Developing Complex Problem-Solving Skills: An Engineering Perspective. Int. J. Adv. Corp. Learn. 12 (2019), 82–88. DOI: 10.3991/ijac.v12i3.11067
D. Shyamal, P. Asanka, and D. Wickramaarachchi. 2023. A Comprehensive Approach to Evaluating Software Code Quality Through a Flexible Quality Model. 2023 International Research Conference on Smart Computing and Systems Engineering (SCSE) 6 (2023), 1–8. DOI: 10.1109/SCSE59836.2023.10215004
Daniel J Simons. 2013. Unskilled and optimistic: Overconfident predictions despite calibrated knowledge of relative skill. Psychonomic bulletin & review 20 (2013), 601–607.
SonarSource. 2024. Clean-Code-based analysis | SonarQube Docs. [link]. Accessed: Nov. 1, 2024.
SonarSource. 2024. Metrics | SonarQube Docs. [link]. Accessed: Nov. 1, 2024.
SonarSource. 2024. Software qualities | SonarQube Docs. [link]. Accessed: Nov. 20, 2024.
Adam Tornhill and Markus Borg. 2022. Code red: the business impact of code quality-a quantitative study of 39 proprietary production codebases. In Proceedings of the International Conference on Technical Debt. 11–20.
W.-C. Tsai, N.-W. Chi, T.-C. Huang, and A.-J. Hsu. 2010. The Effects of Applicant Résumé Contents on Recruiters’ Hiring Recommendations: The Mediating Roles of Recruiter Fit Perceptions. Applied Psychology 60, 2 (Oct. 2010), 231–254.
V. Piantadosi et al. 2023. Do Attention and Memory Explain the Performance of Software Developers? Empirical Software Engineering (2023).
Y. Wang, B. Zheng, and H. Huang. 2008. Complying with Coding Standards or Retaining Programming Style: A Quality Outlook at Source Code Level. Journal of Software Engineering and Applications 1, 1 (2008), 88–91.
Claes Wohlin, Per Runeson, Martin Host, Magnus C. Ohlsson, Björn Regnell, and Anders Wesslén. 2012. Experimentation in Software Engineering. Springer, Berlin, Heidelberg. DOI: 10.1007/978-3-642-29044-2
ClaesWohlin, Per Runeson, Martin Hst, Magnus C. Ohlsson, Bjrn Regnell, and Anders Wessln. 2012. Experimentation in Software Engineering. Springer Publishing Company, Incorporated.
WORKANA. 2024. Hire Freelancers and IT Developers | Workana. [link]. Accessed: Nov. 1, 2024.
Z. Karimi et al. 2016. Links Between the Personalities, Styles and Performance in Computer Programming. Journal of Systems and Software 111 (2016), 228–241.
2023. ISO/IEC 25010:2023: Systems and Software Engineering — Systems and Software Quality Requirements and Evaluation (SQuaRE) — System and Software Quality Models. [link] ISO/IEC Standard.
Reem Alfayez, Pooyan Behnamghader, Kamonphop Srisopha, and Barry Boehm. 2018. An exploratory study on the influence of developers in technical debt. In Proceedings of the 2018 international conference on technical debt. 1–10.
Authors. 2025. replication-package-Analyzing-the-Impact-of-Years-of-Experience-on-Code-Quality-main. (1 2025). DOI: 10.6084/m9.figshare.28306316.v1
Michele A Brandão and Mirella M Moro. 2017. Social professional networks: A survey and taxonomy. Computer Communications 100 (2017), 20–31.
Raymond PL Buse and Westley R Weimer. 2009. Learning a metric for code readability. IEEE Transactions on software engineering 36, 4 (2009), 546–558.
Denivan Campos, Luana Martins, and Ivan Machado. 2022. An empirical study on the influence of developers’ experience on software test code quality. In Proceedings of the XXI Brazilian Symposium on Software Quality. 1–10.
Luiz Fernando Capretz and F. Ahmed. 2018. A Call to Promote Soft Skills in Software Engineering. ArXiv abs/1901.01819 (2018). DOI: 10.17140/PCSOJ-4-e011
Jacob Cohen. 1988. Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Routledge, New York, NY, USA.
Francisco Gomes de Oliveira Neto, Richard Torkar, Robert Feldt, Lucas Gren, Carlo A Furia, and Ziwei Huang. 2019. Evolution of statistical analysis in empirical software engineering research: Current state and steps forward. Journal of Systems and Software 156 (2019), 246–267.
Massimiliano Di Penta, Luigi Cerulo, and Lerina Aversano. 2009. The life and death of statically detected vulnerabilities: An empirical study. Information and Software Technology 51, 10 (2009), 1469–1484.
O. Dieste et al. 2017. Empirical evaluation of the effects of experience on code quality and programmer productivity: an exploratory study. Empirical Software Engineering 22, 5, 2457–2542.
Nikolina Dragicevic, Matantsev Maxim, and Artem Kruglov. 2023. A Study of Effective Strategies for Personal Development and Success for Software Engineers. In 2023 IEEE 14th International Conference on Software Engineering and Service Science (ICSESS). IEEE, 101–104.
K Anders Ericsson, Robert R Hoffman, Aaron Kozbelt, and A Mark Williams. 2018. The Cambridge handbook of expertise and expert performance. Cambridge University Press.
Jefferson G. Lopes, Johnatan Alves, and Eduardo Figueiredo. 2022. EXTRACTPRO: A Data Mining Tool for Developer Profile Generation based on Source Code Analysis. In Proceedings of the XXXVI Brazilian Symposium on Software Engineering. 112–117.
E. Giger, M. Pinzger, and H. C. Gall. 2011. Comparing fine-grained source code changes and code churn for bug prediction. In Proceedings of Data Archiving and Networked Services (DANS).
Nicolas E Gold and Jens Krinke. 2022. Ethics in the mining of software repositories. Empirical Software Engineering 27, 1 (2022), 17.
Nora Honken. 2013. Dreyfus five-stage model of adult skills acquisition applied to engineering lifelong learning. In 2013 ASEE Annual Conference & Exposition. 23–443.
.. Khyber, Sikandar Ali, Fazli Wahid, S. Baseer, A. Alkhayyat, and Akram Al-Radaei. 2024. Smell-Aware Bug Classification. IEEE Access 12 (2024), 14061–14082. DOI: 10.1109/ACCESS.2023.3335175
S. Ozcan Kini and A. Tosun. 2018. Periodic Developer Metrics in Software Defect Prediction. In IEEE Xplore.
Barbara Kitchenham and Stuart Charters. 2007. Guidelines for Performing Systematic Literature Reviews in Software Engineering. Technical Report EBSE 2007-001. EBSE Technical Report. [link]
William H. Kruskal and W. Allen Wallis. 1952. Use of Ranks in One-Criterion Variance Analysis. J. Amer. Statist. Assoc. 47, 260 (Dec. 1952), 583–621.
Paul Luo Li, Amy J Ko, and Jiamin Zhu. 2015. What makes a great software engineer?. In 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering, Vol. 1. IEEE, 700–710.
Jefferson GM Lopes, Johnatan Oliveira, and Eduardo Figueiredo. 2024. Evaluating the Impact of Developer Experience on Code Quality: A Systematic Literature Review. In Congresso Ibero-Americano em Engenharia de Software (CIbSE). SBC, 166–180.
Ivano Malavolta, Roberto Verdecchia, Bojan Filipovic, Magiel Bruntink, and Patricia Lago. 2018. How maintainability issues of android apps evolve. In 2018 IEEE international conference on software maintenance and evolution (ICSME). IEEE, 334–344.
James Miller. 2004. Statistical significance testing—-a panacea for software technology experiments? Journal of Systems and Software 73, 2 (2004), 183–192.
O. Dieste et al. 2018. Empirical Evaluation of the Effects of Experience on Code Quality and Programmer Productivity: An Exploratory Study. In Proceedings of the 2018 International Conference on Software and System Process. 111–112.
Johnatan Oliveira, Maurício Souza, Matheus Flauzino, Rafael Durelli, and Eduardo Figueiredo. 2022. Can source code analysis indicate programming skills? a survey with developers. In International Conference on the Quality of Information and Communications Technology. Springer, 156–171.
Susanna Paloniemi. 2006. Experience, competence and workplace learning. Journal of Workplace Learning 18 (10 2006), 439–450. DOI: 10.1108/13665620610693006
Pandas. 2019. Python Data Analysis Library — pandas: Python Data Analysis Library. [link]. Accessed: Nov. 1, 2024.
Shravan Pargaonkar. 2023. Cultivating Software Excellence: The Intersection of Code Quality and Dynamic Analysis in Contemporary Software Development within the Field of Software Quality Engineering. International Journal of Science and Research (IJSR) (2023). DOI: 10.21275/sr23829092346
V. Piantadosi, S. Scalabrino, A. Serebrenik, N. Novielli, and R. Oliveto. 2023. Do attention and memory explain the performance of software developers? Empirical Software Engineering 28, 5 (Aug. 2023).
Alifia Puspaningrum, Muhammad Anis Al Hilmi, . Darsih, Muhamad Mustamiin, and Maulana Ilham Ginanjar. 2022. Vulnerable Source Code Detection Using Sonarcloud Code Analysis. In Proceedings of the 5th International Conference on Applied Science and Technology on Engineering Science. SCITEPRESS - Science and Technology Publications, 683–687. DOI: 10.5220/0011862600003575
Yilin Qiu, Weiqiang Zhang, Weiqin Zou, Jia Liu, and Qin Liu. 2015. An empirical study of developer quality. In 2015 IEEE International Conference on Software Quality, Reliability and Security-Companion. IEEE, 202–209.
Foyzur Rahman and Premkumar Devanbu. 2011. Ownership, experience and defects: a fine-grained study of authorship. In Proceedings of the 33rd International Conference on Software Engineering. 491–500.
Baishakhi Ray, Daryl Posnett, Vladimir Filkov, and Premkumar Devanbu. 2014. A large scale study of programming languages and code quality in github. In Proceedings of the 22nd ACM SIGSOFT international symposium on foundations of software engineering. 155–165.
María José Salamea and Carles Farré. 2019. Influence of developer factors on code quality: A data study. In 2019 IEEE 19th International Conference on Software Quality, Reliability and Security Companion (QRS-C). IEEE, 120–125.
Amanda Santana, Eduardo Figueiredo, and Juliana Alves Pereira. 2024. Unraveling the Impact of Code Smell Agglomerations on Code Stability. In 2024 IEEE International Conference on Software Maintenance and Evolution (ICSME). IEEE, 461–473.
Geanderson Santos, Amanda Santana, Gustavo Vale, and Eduardo Figueiredo. 2023. Yet another model! a study on model’s similarities for defect and code smells. In International Conference on Fundamental Approaches to Software Engineering. Springer Nature Switzerland Cham, 282–305.
Sigrid Schefer-Wenzl and I. Miladinovic. 2019. Developing Complex Problem-Solving Skills: An Engineering Perspective. Int. J. Adv. Corp. Learn. 12 (2019), 82–88. DOI: 10.3991/ijac.v12i3.11067
D. Shyamal, P. Asanka, and D. Wickramaarachchi. 2023. A Comprehensive Approach to Evaluating Software Code Quality Through a Flexible Quality Model. 2023 International Research Conference on Smart Computing and Systems Engineering (SCSE) 6 (2023), 1–8. DOI: 10.1109/SCSE59836.2023.10215004
Daniel J Simons. 2013. Unskilled and optimistic: Overconfident predictions despite calibrated knowledge of relative skill. Psychonomic bulletin & review 20 (2013), 601–607.
SonarSource. 2024. Clean-Code-based analysis | SonarQube Docs. [link]. Accessed: Nov. 1, 2024.
SonarSource. 2024. Metrics | SonarQube Docs. [link]. Accessed: Nov. 1, 2024.
SonarSource. 2024. Software qualities | SonarQube Docs. [link]. Accessed: Nov. 20, 2024.
Adam Tornhill and Markus Borg. 2022. Code red: the business impact of code quality-a quantitative study of 39 proprietary production codebases. In Proceedings of the International Conference on Technical Debt. 11–20.
W.-C. Tsai, N.-W. Chi, T.-C. Huang, and A.-J. Hsu. 2010. The Effects of Applicant Résumé Contents on Recruiters’ Hiring Recommendations: The Mediating Roles of Recruiter Fit Perceptions. Applied Psychology 60, 2 (Oct. 2010), 231–254.
V. Piantadosi et al. 2023. Do Attention and Memory Explain the Performance of Software Developers? Empirical Software Engineering (2023).
Y. Wang, B. Zheng, and H. Huang. 2008. Complying with Coding Standards or Retaining Programming Style: A Quality Outlook at Source Code Level. Journal of Software Engineering and Applications 1, 1 (2008), 88–91.
Claes Wohlin, Per Runeson, Martin Host, Magnus C. Ohlsson, Björn Regnell, and Anders Wesslén. 2012. Experimentation in Software Engineering. Springer, Berlin, Heidelberg. DOI: 10.1007/978-3-642-29044-2
ClaesWohlin, Per Runeson, Martin Hst, Magnus C. Ohlsson, Bjrn Regnell, and Anders Wessln. 2012. Experimentation in Software Engineering. Springer Publishing Company, Incorporated.
WORKANA. 2024. Hire Freelancers and IT Developers | Workana. [link]. Accessed: Nov. 1, 2024.
Z. Karimi et al. 2016. Links Between the Personalities, Styles and Performance in Computer Programming. Journal of Systems and Software 111 (2016), 228–241.
Published
2025-09-22
How to Cite
LOPES, Jefferson G. M.; OLIVEIRA, Johnatan; FIGUEIREDO, Eduardo.
Aged to Perfection? Analyzing the Impact of Years of Experience on Code Quality. In: BRAZILIAN SYMPOSIUM ON SOFTWARE ENGINEERING (SBES), 39. , 2025, Recife/PE.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 82-92.
ISSN 2833-0633.
DOI: https://doi.org/10.5753/sbes.2025.9688.
