Assurance Case Development for Evolving Software Product Lines: A Formal Approach

2025-11-04

AI Summary

Scalability in assurance case (AC) development and maintenance for software product lines (SPLs) remains challenging due to the need to simultaneously accommodate variant diversity, perform evolution impact analysis, and enable certification evidence reuse. Method: This paper proposes a variant-aware formal approach that elevates AC construction to the product-line level. We define a variant-aware AC language and a template-based construction mechanism, enabling unified modeling of safety evidence and supporting property-level scalability and sustainable certification. Integrating variant logic, formal modeling, and model-driven engineering, we develop an automated toolchain for AC generation and maintenance. Contribution/Results: Empirical evaluation on a medical device SPL demonstrates that our approach significantly improves traceability accuracy and evidence reuse efficiency under evolutionary changes, thereby advancing scalable, maintainable, and certifiable SPL assurance.

Technology Category

• Constraint Satisfaction and Optimization: Satisfiability Modulo Theories
• Natural Language Processing: Safety and Robustness
• Machine Learning: Calibration & Uncertainty Quantification

Application Category

• Security and Privacy: Large-scale security measurements
• Semantics and Knowledge: Scalable techniques for the creation, curation, publication, maintenance, and consumption of large, Web-based, structured, reusable, knowledge graphs and ontologies
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications

Abstract

In critical software engineering, structured assurance cases (ACs) are used to demonstrate how key system properties are supported by evidence (e.g., test results, proofs). Creating rigorous ACs is particularly challenging in the context of software product lines (SPLs), i.e, sets of software products with overlapping but distinct features and behaviours. Since SPLs can encompass very large numbers of products, developing a rigorous AC for each product individually is infeasible. Moreover, if the SPL evolves, e.g., by the modification or introduction of features, it can be infeasible to assess the impact of this change. Instead, the development and maintenance of ACs ought to be lifted such that a single AC can be developed for the entire SPL simultaneously, and be analyzed for regression in a variability-aware fashion. In this article, we describe a formal approach to lifted AC development and regression analysis. We formalize a language of variability-aware ACs for SPLs and study the lifting of template-based AC development. We also define a regression analysis to determine the effects of SPL evolutions on variability-aware ACs. We describe a model-based assurance management tool which implements these techniques, and illustrate our contributions by developing an AC for a product line of medical devices.

Problem

• Developing rigorous assurance cases for evolving software product lines
• Managing assurance case regression analysis during feature modifications
• Creating variability-aware assurance cases for entire product families

Innovation

• Formal approach for lifted assurance case development
• Variability-aware ACs for software product lines
• Model-based tool for assurance management implementation