A Type-inferencing Mechanism for Automatically Detecting Variable Types in System Requirements Specifications

Abstract: A system requirements specification (SyRS) defines a set of functionalities that a system is expected to fulfil. A requirement may be “it is always the case that actualFuelLevel is greater than or equal to 0” for an industrial system. Inconsistencies in a SyRS may require the system to be redesigned or reimplemented, which can drastically increase costs. With the increased size and complexity of SyRS it is important to assess new methods for verifying their correctness with respect to some criteria such as consistency. PROPAS is a tool for automated consistency checking of SyRS developed within the VeriSpec project, a cooperation between Mälardalen University, Scania and Volvo GTT. The tool is based on satisfiability modulo theories (SMT) techniques and operates on SyRS encoded in formal notation, that is timed computation tree logic (TCTL). In this thesis we extend the functionality of the PROPAS tool by implementing a type-inferencing mechanism such that variable types in SyRS can be automatically inferred. For validation, we apply the extended PROPAS tool on a set of industrial requirements. The results show that the type-inferencing mechanism can correctly infer the types of the variables from the set of requirements in most cases, while in the same time not introducing significant computational overhead to the existing solution.