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<p>In today’s fast-paced software development environment, organizational survival depends not only on rapid delivery but also on the ability to adapt quickly to evolving requirements. Modern methodologies such as rolling wave planning, evolutionary development, and continuous improvement emphasize early delivery and flexible responses to change. This dynamic nature necessitates effective evaluation of requirement change (RC) requests. However, the absence of a detailed change impact analysis often leads to suboptimal decisions, raising concerns about project success in terms of cost, time, and quality.RC requests can influence various dimensions, including functional requirements (FUR), non-functional requirements (NFR), and project constraints (PRC) (Abran A, Castelo D, Mitwasi GM, Vogelezang F, Aguiar M, Fagg P, Soneira P, Woodward C, Ben-Cnaan P, Lesterhuis A, and Symons C (2015) Glossary of terms for non-functional requirements and project requirements used in software project performance measurement, benchmarking and estimating). As the software project progresses, functional requirements evolve and become increasingly detailed, resulting in varying levels of granularity across the development lifecycle. Early-phase requirements tend to be vague or incomplete, while later stages bring greater clarity. This evolving nature frequently leads to “scope creep,” contributing to delays, cost overruns, and reduced software quality.To address this, we propose a multi-level measures-driven change impact analysis approach for prioritizing RC requests. This approach relies on quantitative assessments conducted at different levels of granularity—namely, the functional level, control structure level, and process level—to guide informed and accurate decision-making. In particular, we leverage COSMIC functional size measurement (The COSMIC Functional Size Measurement Method COSMIC (2020). The Version 5.0, Announcement of Version5.0 of the COSMIC Measurement Manual—March31, 2020) alongside structural size measurement methods (Sellami et al. in Inf Softw Technol 59:222–232, 2015) to evaluate the impact of RC requests on development progress.Our methodology enables both macro-level (functional) and micro-level (structural) impact assessments, helping decision-makers—project managers, analysts, and developers—take appropriate actions. While strategic decisions are supported by process-level metrics, operational decisions benefit from detailed functional and structural measurements. This framework provides a structured, data-driven foundation for managing change across the software lifecycle.</p>

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A multi-level measures-driven change impact analysis approach for prioritizing software requirement changes

  • 期刊论文

  • 发表日期：

    2025年9月11日

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  • Hela Hakim,
  • Asma Sellami,
  • Hanêne Ben-Abdallah

摘要

In today’s fast-paced software development environment, organizational survival depends not only on rapid delivery but also on the ability to adapt quickly to evolving requirements. Modern methodologies such as rolling wave planning, evolutionary development, and continuous improvement emphasize early delivery and flexible responses to change. This dynamic nature necessitates effective evaluation of requirement change (RC) requests. However, the absence of a detailed change impact analysis often leads to suboptimal decisions, raising concerns about project success in terms of cost, time, and quality.RC requests can influence various dimensions, including functional requirements (FUR), non-functional requirements (NFR), and project constraints (PRC) (Abran A, Castelo D, Mitwasi GM, Vogelezang F, Aguiar M, Fagg P, Soneira P, Woodward C, Ben-Cnaan P, Lesterhuis A, and Symons C (2015) Glossary of terms for non-functional requirements and project requirements used in software project performance measurement, benchmarking and estimating). As the software project progresses, functional requirements evolve and become increasingly detailed, resulting in varying levels of granularity across the development lifecycle. Early-phase requirements tend to be vague or incomplete, while later stages bring greater clarity. This evolving nature frequently leads to “scope creep,” contributing to delays, cost overruns, and reduced software quality.To address this, we propose a multi-level measures-driven change impact analysis approach for prioritizing RC requests. This approach relies on quantitative assessments conducted at different levels of granularity—namely, the functional level, control structure level, and process level—to guide informed and accurate decision-making. In particular, we leverage COSMIC functional size measurement (The COSMIC Functional Size Measurement Method COSMIC (2020). The Version 5.0, Announcement of Version5.0 of the COSMIC Measurement Manual—March31, 2020) alongside structural size measurement methods (Sellami et al. in Inf Softw Technol 59:222–232, 2015) to evaluate the impact of RC requests on development progress.Our methodology enables both macro-level (functional) and micro-level (structural) impact assessments, helping decision-makers—project managers, analysts, and developers—take appropriate actions. While strategic decisions are supported by process-level metrics, operational decisions benefit from detailed functional and structural measurements. This framework provides a structured, data-driven foundation for managing change across the software lifecycle.