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Test debts identification in a test factory

Published:28 October 2019Publication History

ABSTRACT

Testing processes are commonly used with the aim of systematizing testing activities within a software development project or in a Test Factory (TF). However, even using a process, the team may fail to perform testing activities, intentionally or not, in order to, for example, make a faster delivery. In this situation, the team may incur a Technical Debt (TD): technical commitment generated during the software development lifecycle that may be beneficial in the short term, but in the long term, may be detrimental to the quality of the project. These TDs should be identified and managed, because if they remain invisible and non-refunded, they may accumulate incrementally and hinder, or even make impossible, maintenance tasks and software evolution. In this context, this work aims to report the experience of identifying technical test debts in a Test Factory. As object of the study, Test Debts were analyzed in five projects with the industry, in 2017, 2018 and 2019. As a result, four Test Debts causes were identified over the three years of our experience in the industry. Also, we present 11 lessons learned that help to identify and prevent Test Debts.

References

  1. Nicolli SR Alves, Thiago S Mendes, Manoel G de Mendonça, Rodrigo O Spínola, Forrest Shull, and Carolyn Seaman. 2016. Identification and management of technical debt: A systematic mapping study. Information and Software Technology 70 (2016), 100--121.Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. R. M. C. Andrade, V. Lelli, R. N. S. Castro, and I. S. Santos. 2017. Fifteen Years of Industry and Academia Partnership: Lessons Learned from a Brazilian Research Group. In 2017 IEEE/ACM 4th International Workshop on Software Engineering Research and Industrial Practice (SER IP). 10--16. https://doi.org/10.1109/SER-IP.2017..2Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Nanette Brown, Yuanfang Cai, Yuepu Guo, Rick Kazman, Miryung Kim, Philippe Kruchten, Erin Lim, Alan MacCormack, Robert Nord, Ipek Ozkaya, et al. 2010. Managing technical debt in software-reliant systems. In Proceedings of the FSE/SDP workshop on Future of software engineering research. ACM, 47--52.Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Ward Cunningham. 1992. The WyCash Portfolio Management System. SIGPLAN OOPS Mess. 4, 2 (Dec. 1992), 29--30. https://doi.org/10.1145/157710.157715Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Rossana M. de Castro Andrade, Ismayle de Sousa Santos, Valéria Lelli, Káthia Marçal de Oliveira, and Ana Regina Cavalcanti da Rocha. 2017. Software Testing Process in a Test Factory - From Ad hoc Activities to an Organizational Standard. In ICEIS.Google ScholarGoogle Scholar
  6. Amanda Oliveira de Sousa, Ismayle de Sousa Santos, Bruno Sabóia Aragão, and Rossana M. de Castro Andrade. 2018. Towards an Automatic Approach to Estimating Test Effort: An Experience Report. In Proceedings of the 17th Brazilian Symposium on Software Quality (SBQS). ACM, New York, NY, USA, 305--314. https://doi.org/10.1145/3275245.3275273Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Yuepu Guo, Carolyn Seaman, and Fabio QB da Silva. 2016. Costs and obstacles encountered in technical debt management--A case study. Journal of Systems and Software 120 (2016), 156--169.Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Zengyang Li, Paris Avgeriou, and Peng Liang. 2015. A systematic mapping study on technical debt and its management. Journal of Systems and Software 101 (2015), 193--220.Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Erin Lim, Nitin Taksande, and Carolyn Seaman. 2012. A Balancing Act: What Software Practitioners Have to Say about Technical Debt. 29 (11 2012), 22--27.Google ScholarGoogle Scholar
  10. Alessandro Orso and Gregg Rothermel. 2014. Software testing: a research travelogue (2000--2014). In Proceedings of the on Future of Software Engineering. ACM, 117--132.Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Nirav Patel, Muthukrishnan Govindrajan, Susmita Maharana, and Shoba Ramdas. 2001. Test Case Point Analysis. Cognizant Technology Solutions, White Paper (2001).Google ScholarGoogle Scholar
  12. Ganesh Samarthyam, Mahesh Muralidharan, and Raghu Kalyan Anna. 2017. Understanding Test Debt. In Trends in Software Testing. Springer, 1--17.Google ScholarGoogle Scholar
  13. Ana Sanz, Javier Garcia, Javier Saldana, and Antonio Amescua. 2009. A proposal of a process model to create a Test Factory. In Software Quality, 2009. WOSQ'09. ICSE Workshop on. IEEE, 65--70.Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. IEEE Computer Society, Pierre Bourque, and Richard E. Fairley. 2014. Guide to the Software Engineering Body of Knowledge (SWEBOK(R)): Version 3.0 (3rd ed.). IEEE Computer Society Press, Los Alamitos, CA, USA.Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Cleydiane Lima de Sousa. 2016. Mapa de apoio à gestão de dívida técnica no processo de teste de software. (2016).Google ScholarGoogle Scholar
  16. Lucas Sales Vieira, Cayk G Lima Barreto, Erick Barros dos Santos, Bruno Sabóia Aragão, Ismayle de Sousa Santos, and Rossana M Castro Andrade. 2018. Automação de Testes em uma Fábrica de Testes: Um Relato de Experiência. In Anais do XIV Simpósio Brasileiro de Sistemas de Informação. SBC, 80--73.Google ScholarGoogle Scholar
  17. K. Wiklund, S. Eldh, D. Sundmark, and K. Lundqvist. 2012. Technical Debt in Test Automation. In 2012 IEEE Fifth International Conference on Software Testing, Verification and Validation. 887--892. https://doi.org/10.1109/ICST.2012.192Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Kristian Wiklund, Sigrid Eldh, Daniel Sundmark, and Kristina Lundqvist. 2017. Impediments for software test automation: A systematic literature review. Software Testing, Verification and Reliability 27, 8 (2017).Google ScholarGoogle Scholar

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    • Published in

      cover image ACM Other conferences
      SBQS '19: Proceedings of the XVIII Brazilian Symposium on Software Quality
      October 2019
      330 pages
      ISBN:9781450372824
      DOI:10.1145/3364641

      Copyright © 2019 ACM

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      Publication History

      • Published: 28 October 2019

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      Acceptance Rates

      SBQS '19 Paper Acceptance Rate35of99submissions,35%Overall Acceptance Rate35of99submissions,35%

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