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Quantifying Requirements Technical Debt: A Systematic Mapping Study and a Conceptual Model

Judith Perera, Ewan Tempero, Yu‐Cheng Tu, Kelly Blincoe

202311 citationsDOI

Abstract

Requirements Technical Debt (RTD) is a research area where the Technical Debt (TD) metaphor is used to capture the consequences of sub-optimal decisions made concerning Requirements. Understanding the quantification of RTD is key to its management. To facilitate this understanding, we model the quantification of RTD. Our work is grounded in the literature found via a Systematic Mapping Study (SMS) and informed by prior work modeling the quantification of TD for software code-related TD types. This paper reports on the SMS and the development of our model, the RTD Quantification Model (RTDQM). The key observation from our work is that, although RTD is similar in most aspects to TD in software code, it also has its own components. Requirement artifacts have a feedback loop involving the User to precisely capture User Needs. RTD Interest (i.e., additional costs due to sub-optimal decisions concerning Requirements) can incur during both Requirements Engineering and Implementation activities. Furthermore, RTD can incur regardless of the presence of software code-related TD. Similar to benefits accrued by refactoring software code, rectifying RTD can also accrue benefits.

Topics & Concepts

Technical debtComputer scienceSoftware engineeringCode refactoringKey (lock)SoftwareCode (set theory)Conceptual modelRisk analysis (engineering)Systems engineeringSoftware developmentDatabaseEngineeringProgramming languageComputer securitySet (abstract data type)MedicineSoftware Engineering ResearchSoftware Engineering Techniques and PracticesSoftware Reliability and Analysis Research