UC5 Eval Criteria SCP-2/Mapping 1-4

Reduction of requirement violations from the outset by following a methodical requirements elicitation and specification process

Use Case Id

Description of evaluation

Test case Test case where the V&V method has been used to improve a evaluation criteria. The test case where the V&V process improvement has been achieved

Requirement The validated requirement where a VALU3S V&V method has been used.

Evaluation Scenario The evaluation scenario where the V&V evaluation result has been obtained

V&V method

V&V Tool

Evaluation Criteria for Safety, Cybersecurity, and Privacy (SCP)

VALU3S SCP Criteria

Quantitative results Description and specification of the evaluation criteria used to measure the improvement (D5.6)

The aerospace use case which is focused on an aircraft engine software controller has not yet detected specific safety/security requirement violations (although work is ongoing). However, much time was spent in accurately eliciting and formalising the original set of natural language requirements. There were 14 requirements originally and, after a thorough elicitation process, this number increased to 42 requirements. This demonstrates that significant ambiguities were present in the natural-language requirements that could be identified and captured by formalising the requirements.

Long Description

Requirement violations can be detected by a number of verification activities including formal methods, simulation, testing and run-time monitoring. However, it is important that when violations are detected that the root cause of the conflict is identified and resolved. One way to reduce requirement violations from the outset is to follow a methodical requirements elicitation and specification process that involves formalising and slowly refining the requirements. This involves beginning with a high-level set of requirements that are gradually decomposed into more detailed, specific requirements. Typically, this kind of process would start with abstract natural language requirements and return a larger set of formalised requirements. Here we can measure the following: -Number of natural language requirements:12

-Number of formalised requirements:42

These numbers give an idea of the effort involved in removing ambiguities from natural language requirements and the formalised requirements can be used as direct input to other verification tools/techniques.

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