A Scalable Approach to Detecting Safety Requirements Inconsistencies for Railway Systems

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Abstract
Dealing with the ever-growing complexity of railway systems requires scalable approaches for detecting inconsistent safety requirements in practice. Despite significant efforts to automate the requirements consistency detection, current inconsistency analysis techniques of railway safety requirements still suffer from scalability issues. This paper proposes a two-layer approach for detecting inconsistencies in time-related safety requirements of railway systems, integrating two distinct formal methods from a pragmatic perspective. At the SafeNL layer, we employ an SMT-based approach to extract conflict patterns and use them to filter out inconsistent requirements descriptions, thus avoiding the more expensive general use of the SMT-based approach. At the CCSL layer, temporal dependencies in requirements are transformed into causal relations, which are then detected for circular inconsistencies using a graph search technique. Our evaluations demonstrate the utility and scalability of our approach.
Funding Information
  • National Natural Science Foundation of China (62192731, 62272166, 62192730)

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