Survey on Safety Evidence Change Impact Analysis in Practice: Detailed Description and Analysis

Critical systems must comply with safety standards in many application domains. This involves gathering safety evidence in the form of artefacts such as safety analyses, system specifications, and testing results. These artefacts can evolve during a system’s lifecycle, and impact analysis might be necessary to guarantee that system safety and compliance are not jeopardised. Although extensive research has been conducted on impact analysis and on safety evidence management, the knowledge about how safety evidence change impact analysis is addressed in practice is limited. This technical report presents a survey targeted at filling this gap by analysing the circumstances under which safety evidence change impact analysis is addressed, the tool support used, and the challenges faced. We obtained 97 valid responses representing 16 application domains, 28 countries, and 47 safety standards. The results suggest that most projects deal with safety evidence change impact analysis during system development and mainly from system specifications, the level of automation in the process is low, and insufficient tool support is the most frequent challenge. Other notable findings are that safety case evolution should probably be better managed, no commercial impact analysis tool has been reported as used for all artefact types, and experience and automation do not seem to greatly help in avoiding challenges

Changes, Evolution and Bugs - Recommendation Systems for Issue Management

Changes in evolving software systems are often managed using an issue repository. This repository may contribute to information overload in an organization, but it may also help navigating the software system. Software developers spend much effort on issue triage, a task in which the mere number of issue reports becomes a significant challenge. One specific difficulty is to determine whether a newly submitted issue report is a duplicate of an issue previously reported, if it contains complementary information related to a known issue, or if the issue report addresses something that has not been observed before. However, the large number of issue reports may also be used to help a developer to navigate the software development project to find related software artifacts, required both to understand the issue itself, and to analyze the impact of a possible issue resolution. This chapter presents recommendation systems that use information in issue repositories to support these two challenges, by supporting either duplicate detection of issue reports or navigation of artifacts in evolving software systems