Towards a Holistic Definition of Requirements Debt

When not appropriately managed, technical debt is considered to have negative effects to the long term success of software projects. However, how the debt metaphor applies to requirements engineering in general, and to requirements engineering activities in particular, is not well understood. Grounded in the existing literature, we present a holistic definition of requirements debt which includes debt incurred during the identification, formalization, and implementation of requirements. We outline future assessment to validate and further refine our proposed definition. This conceptualization is a first step towards a requirements debt monitoring framework to support stakeholders decisions, such as when to incur and eventually pay back requirements debt, and at what costs.

[1]  Rodrigo O. Spínola,et al.  Towards an Ontology of Terms on Technical Debt , 2014, 2014 Sixth International Workshop on Managing Technical Debt.

[2]  Jan Bosch,et al.  An Empirically Developed Method to Aid Decisions on Architectural Technical Debt Refactoring: AnaConDebt , 2016, 2016 IEEE/ACM 38th International Conference on Software Engineering Companion (ICSE-C).

[3]  Apostolos Ampatzoglou,et al.  The financial aspect of managing technical debt: A systematic literature review , 2015, Inf. Softw. Technol..

[4]  Joost Visser,et al.  An empirical model of technical debt and interest , 2011, MTD '11.

[5]  Hideaki Hata,et al.  Identifying Design and Requirement Self-Admitted Technical Debt Using N-gram IDF , 2018, 2018 9th International Workshop on Empirical Software Engineering in Practice (IWESEP).

[6]  Daniela Cruzes,et al.  Are all code smells harmful? A study of God Classes and Brain Classes in the evolution of three open source systems , 2010, 2010 IEEE International Conference on Software Maintenance.

[7]  Roel Wieringa,et al.  Naming the pain in requirements engineering , 2016, Empirical Software Engineering.

[8]  Peng Liang,et al.  A systematic mapping study on technical debt and its management , 2015, J. Syst. Softw..

[9]  Audris Mockus,et al.  Quantifying the Effect of Code Smells on Maintenance Effort , 2013, IEEE Transactions on Software Engineering.

[10]  Davide Taibi,et al.  How developers perceive smells in source code: A replicated study , 2017, Inf. Softw. Technol..

[11]  Yuanfang Cai,et al.  Comparing four approaches for technical debt identification , 2014, Software Quality Journal.

[12]  Maleknaz Nayebi,et al.  App store mining is not enough for app improvement , 2018, Empirical Software Engineering.

[13]  Zahra Shakeri Hossein Abad,et al.  Using real options to manage Technical Debt in Requirements Engineering , 2015, 2015 IEEE 23rd International Requirements Engineering Conference (RE).

[14]  Muhammad Ovais Ahmad,et al.  Comparing Requirements Decomposition Within the Scrum, Scrum with Kanban, XP, and Banana Development Processes , 2017, XP.

[15]  Stefan Wagner,et al.  Rapid quality assurance with Requirements Smells , 2016, J. Syst. Softw..

[16]  Davide Taibi,et al.  The Technical Debt Dataset , 2019, PROMISE.

[17]  Jan Bosch,et al.  Investigating Architectural Technical Debt accumulation and refactoring over time: A multiple-case study , 2015, Inf. Softw. Technol..

[18]  Neil A. Ernst,et al.  Measure it? Manage it? Ignore it? software practitioners and technical debt , 2015, ESEC/SIGSOFT FSE.

[19]  Sajjad Mahmood,et al.  A survey on UML model smells detection techniques for software refactoring , 2019, J. Softw. Evol. Process..

[20]  Robert L. Nord,et al.  In Search of a Metric for Managing Architectural Technical Debt , 2012, 2012 Joint Working IEEE/IFIP Conference on Software Architecture and European Conference on Software Architecture.

[21]  Robert L. Nord,et al.  Managing technical debt in software-reliant systems , 2010, FoSER '10.

[22]  Terese Besker,et al.  Technical Debt Prioritization: State of the Art. A Systematic Literature Review , 2019, ArXiv.

[23]  Klaus Schmid.  On the limits of the technical debt metaphor some guidance on going beyond , 2013, 2013 4th International Workshop on Managing Technical Debt (MTD).

[24]  Carolyn B. Seaman,et al.  Measuring and Monitoring Technical Debt , 2011, Adv. Comput..

[25]  Maleknaz Nayebi,et al.  Toward Data-Driven Requirements Engineering , 2016, IEEE Software.

[26]  Richard T. Vidgen,et al.  An exploration of technical debt , 2013, J. Syst. Softw..

[27]  Neil A. Ernst.  On the role of requirements in understanding and managing technical debt , 2012, 2012 Third International Workshop on Managing Technical Debt (MTD).

[28]  Davide Taibi,et al.  MVP Explained: A Systematic Mapping Study on the Definitions of Minimal Viable Product , 2016, 2016 42th Euromicro Conference on Software Engineering and Advanced Applications (SEAA).

[29]  Gabriele Taentzer,et al.  UML Model Smells and Model Refactorings in Early Software Development Phases , 2010 .

[30]  Carolyn B. Seaman,et al.  A portfolio approach to technical debt management , 2011, MTD '11.

[31]  Kelly Blincoe,et al.  Embracing Technical Debt, from a Startup Company Perspective , 2018, 2018 IEEE International Conference on Software Maintenance and Evolution (ICSME).

[32]  Gabriele Bavota,et al.  On the diffuseness and the impact on maintainability of code smells: a large scale empirical investigation , 2017, Empirical Software Engineering.

[33]  Yi Sun,et al.  Some Code Smells Have a Significant but Small Effect on Faults , 2014, TSEM.

[34]  Ward Cunningham,et al.  The WyCash portfolio management system , 1992, OOPSLA '92.