A PRISMA-Driven Bibliometric Analysis of the Scientific Literature on Assurance Case Patterns

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Main Authors: Odu, Oluwafemi, Belle, Alvine Boaye, Wang, Song, Shahandashti, Kimya Khakzad
Format: Preprint
Published: 2024
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author Odu, Oluwafemi
Belle, Alvine Boaye
Wang, Song
Shahandashti, Kimya Khakzad
author_facet Odu, Oluwafemi
Belle, Alvine Boaye
Wang, Song
Shahandashti, Kimya Khakzad
contents Justifying the correct implementation of the non-functional requirements (e.g., safety, security) of mission-critical systems is crucial to prevent system failure. The later could have severe consequences such as the death of people and financial losses. Assurance cases can be used to prevent system failure, They are structured arguments that allow arguing and relaying various safety-critical systems' requirements extensively as well as checking the compliance of such systems with industrial standards to support their certification. Still, the creation of assurance cases is usually manual, error-prone, and time-consuming. Besides, it may involve numerous alterations as the system evolves. To overcome the bottlenecks in creating assurance cases, existing approaches usually promote the reuse of common structured evidence-based arguments (i.e. patterns) to aid the creation of assurance cases. To gain insights into the advancements of the research on assurance case patterns, we relied on SEGRESS to conduct a bibliometric analysis of 92 primary studies published within the past two decades. This allows capturing the evolutionary trends and patterns characterizing the research in that field. Our findings notably indicate the emergence of new assurance case patterns to support the assurance of ML-enabled systems that are characterized by their evolving requirements (e.g., cybersecurity and ethics).
format Preprint
id arxiv_https___arxiv_org_abs_2407_04961
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A PRISMA-Driven Bibliometric Analysis of the Scientific Literature on Assurance Case Patterns
Odu, Oluwafemi
Belle, Alvine Boaye
Wang, Song
Shahandashti, Kimya Khakzad
Software Engineering
Justifying the correct implementation of the non-functional requirements (e.g., safety, security) of mission-critical systems is crucial to prevent system failure. The later could have severe consequences such as the death of people and financial losses. Assurance cases can be used to prevent system failure, They are structured arguments that allow arguing and relaying various safety-critical systems' requirements extensively as well as checking the compliance of such systems with industrial standards to support their certification. Still, the creation of assurance cases is usually manual, error-prone, and time-consuming. Besides, it may involve numerous alterations as the system evolves. To overcome the bottlenecks in creating assurance cases, existing approaches usually promote the reuse of common structured evidence-based arguments (i.e. patterns) to aid the creation of assurance cases. To gain insights into the advancements of the research on assurance case patterns, we relied on SEGRESS to conduct a bibliometric analysis of 92 primary studies published within the past two decades. This allows capturing the evolutionary trends and patterns characterizing the research in that field. Our findings notably indicate the emergence of new assurance case patterns to support the assurance of ML-enabled systems that are characterized by their evolving requirements (e.g., cybersecurity and ethics).
title A PRISMA-Driven Bibliometric Analysis of the Scientific Literature on Assurance Case Patterns
topic Software Engineering
url https://arxiv.org/abs/2407.04961