A PRISMA-driven systematic mapping study on system assurance weakeners

Context: An assurance case is a structured hierarchy of claims aiming at demonstrating that a given mission-critical system supports specific requirements (e.g., safety, security, privacy). The presence of assurance weakeners (i.e., assurance deficits, logical fallacies) in assurance cases reflects insufficient evidence, knowledge, or gaps in reasoning. These weakeners can undermine confidence in assurance arguments, potentially hindering the verification of mission-critical system capabilities. Objectives: As a stepping stone for future research on assurance weakeners, we aim to initiate the first comprehensive systematic mapping study on this subject. Methods: We followed the well-established PRISMA 2020 and SEGRESS guidelines to conduct our systematic mapping study. We searched for primary studies in five digital libraries and focused on the 2012-2023 publication year range. Our selection criteria focused on studies addressing assurance weakeners at the modeling level, resulting in the inclusion of 39 primary studies in our systematic review. Results: Our systematic mapping study reports a taxonomy (map) that provides a uniform categorization of assurance weakeners and approaches proposed to manage them at the modeling level. Conclusion: Our study findings suggest that the SACM (Structured Assurance Case Metamodel) -- a standard specified by the OMG (Object Management Group) -- may be the best specification to capture structured arguments and reason about their potential assurance weakeners

Trusta: Reasoning about Assurance Cases with Formal Methods and Large Language Models

Assurance cases can be used to argue for the safety of products in safety engineering. In safety-critical areas, the construction of assurance cases is indispensable. Trustworthiness Derivation Trees (TDTs) enhance assurance cases by incorporating formal methods, rendering it possible for automatic reasoning about assurance cases. We present Trustworthiness Derivation Tree Analyzer (Trusta), a desktop application designed to automatically construct and verify TDTs. The tool has a built-in Prolog interpreter in its backend, and is supported by the constraint solvers Z3 and MONA. Therefore, it can solve constraints about logical formulas involving arithmetic, sets, Horn clauses etc. Trusta also utilizes large language models to make the creation and evaluation of assurance cases more convenient. It allows for interactive human examination and modification. We evaluated top language models like ChatGPT-3.5, ChatGPT-4, and PaLM 2 for generating assurance cases. Our tests showed a 50%-80% similarity between machine-generated and human-created cases. In addition, Trusta can extract formal constraints from text in natural languages, facilitating an easier interpretation and validation process. This extraction is subject to human review and correction, blending the best of automated efficiency with human insight. To our knowledge, this marks the first integration of large language models in automatic creating and reasoning about assurance cases, bringing a novel approach to a traditional challenge. Through several industrial case studies, Trusta has proven to quickly find some subtle issues that are typically missed in manual inspection, demonstrating its practical value in enhancing the assurance case development process.Comment: 38 page

Formal Assurance Arguments: A Solution In Search of a Problem?

An assurance case comprises evidence and argument showing how that evidence supports assurance claims (e.g., about safety or security). It is unsurprising that some computer scientists have proposed formalizing assurance arguments: most associate formality with rigor. But while engineers can sometimes prove that source code refines a formal specification, it is not clear that formalization will improve assurance arguments or that this benefit is worth its cost. For example, formalization might reduce the benefits of argumentation by limiting the audience to people who can read formal logic. In this paper, we present (1) a systematic survey of the literature surrounding formal assurance arguments, (2) an analysis of errors that formalism can help to eliminate, (3) a discussion of existing evidence, and (4) suggestions for experimental work to definitively answer the question

Automating the Generation of Heterogeneous Aviation Safety Cases

A safety case is a structured argument, supported by a body of evidence, which provides a convincing and valid justification that a system is acceptably safe for a given application in a given operating environment. This report describes the development of a fragment of a preliminary safety case for the Swift Unmanned Aircraft System. The construction of the safety case fragment consists of two parts: a manually constructed system-level case, and an automatically constructed lower-level case, generated from formal proof of safety-relevant correctness properties. We provide a detailed discussion of the safety considerations for the target system, emphasizing the heterogeneity of sources of safety-relevant information, and use a hazard analysis to derive safety requirements, including formal requirements. We evaluate the safety case using three classes of metrics for measuring degrees of coverage, automation, and understandability. We then present our preliminary conclusions and make suggestions for future work

Addressing Complexity and Intelligence in Systems Dependability Evaluation

Engineering and computing systems are increasingly complex, intelligent, and open adaptive. When it comes to the dependability evaluation of such systems, there are certain challenges posed by the characteristics of “complexity” and “intelligence”. The first aspect of complexity is the dependability modelling of large systems with many interconnected components and dynamic behaviours such as Priority, Sequencing and Repairs. To address this, the thesis proposes a novel hierarchical solution to dynamic fault tree analysis using Semi-Markov Processes. A second aspect of complexity is the environmental conditions that may impact dependability and their modelling. For instance, weather and logistics can influence maintenance actions and hence dependability of an offshore wind farm. The thesis proposes a semi-Markov-based maintenance model called “Butterfly Maintenance Model (BMM)” to model this complexity and accommodate it in dependability evaluation. A third aspect of complexity is the open nature of system of systems like swarms of drones which makes complete design-time dependability analysis infeasible. To address this aspect, the thesis proposes a dynamic dependability evaluation method using Fault Trees and Markov-Models at runtime.The challenge of “intelligence” arises because Machine Learning (ML) components do not exhibit programmed behaviour; their behaviour is learned from data. However, in traditional dependability analysis, systems are assumed to be programmed or designed. When a system has learned from data, then a distributional shift of operational data from training data may cause ML to behave incorrectly, e.g., misclassify objects. To address this, a new approach called SafeML is developed that uses statistical distance measures for monitoring the performance of ML against such distributional shifts. The thesis develops the proposed models, and evaluates them on case studies, highlighting improvements to the state-of-the-art, limitations and future work

Regulatory Compliance in Multi-Tier Supplier Networks

Over the years, avionics systems have increased in complexity to the point where 1st tier suppliers to an aircraft OEM find it financially beneficial to outsource designs of subsystems to 2nd tier and at times to 3rd tier suppliers. Combined with challenging schedule and budgetary pressures, the environment in which safety-critical systems are being developed introduces new hurdles for regulatory agencies and industry. This new environment of both complex systems and tiered development has raised concerns in the ability of the designers to ensure safety considerations are fully addressed throughout the tier levels. This has also raised questions about the sufficiency of current regulatory guidance to ensure: proper flow down of safety awareness, avionics application understanding at the lower tiers, OEM and 1st tier oversight practices, and capabilities of lower tier suppliers. Therefore, NASA established a research project to address Regulatory Compliance in a Multi-tier Supplier Network. This research was divided into three major study efforts: 1. Describe Modern Multi-tier Avionics Development 2. Identify Current Issues in Achieving Safety and Regulatory Compliance 3. Short-term/Long-term Recommendations Toward Higher Assurance Confidence This report presents our findings of the risks, weaknesses, and our recommendations. It also includes a collection of industry-identified risks, an assessment of guideline weaknesses related to multi-tier development of complex avionics systems, and a postulation of potential modifications to guidelines to close the identified risks and weaknesses