A Tool-Supported Method for Fallacies Detection in Process-Based Argumentation

Abstract: Process-based arguments aim at demonstrating that a process, compliant with a standard, has been followed during the development of a safety-critical system. Compliance with these processes is mandatory for certification purposes, so the generation of process-based arguments is essential, but also a very costly and time-consuming task. In addition, inappropriate reasoning in the argumentation such as insufficient evidence (i.e. a fallacious argumentation), may result in a loss of quality of the system, leading to safety-related failures. Therefore, avoiding or detecting fallacies in process-based arguments is crucial. However, the process of reviewing such arguments is currently done manually and is based on the expert’s knowledge, so it is a very laborious and error-prone task.In this thesis, an approach to automatically generate fallacy-free process-based arguments is proposed and implemented. This solution is composed of two parts; (i) detecting omission of key evidence fallacies on the modelled processes, and (ii) transforming them into process-based safety arguments. The former checks automatically if the process model, compliant with the Software & Systems Process Engineering Metamodel (SPEM) 2.0, contains the sufficient information for not committing an omission of key evidence fallacy. If fallacies are detected, the functionality provides the proper recommendation to resolve them. Once the safety engineers/process engineers modify the process model following the provided recommendations, the second part of the solution can be applied. This one generates automatically the process-based argument, compliant with the Structured Assurance Case Metamodel (SACM), and displays it –rendered via Goal Structuring Notation (GSN)– into the OpenCert assurance case editor within the AMASS platform. The applicability of the solution is validated in the context of the ECSS-E-ST-40C standard.