Model-Driven requirements engineering process aided by ontologies and natural controlled languages

Researches in Requirements Engineering have been growing in the latest few years. Researchers are concerned with a set of open issues such as: communication between several user profiles involved in software engineering; scope definition; volatility and traceability issues. To cope with these issues a set of works are concentrated in (i) defining processes to collect client s specifications in order to solve scope issues; (ii) defining models to represent requirements to address communication and traceability issues; and (iii) working on mechanisms and processes to be applied to requirements modeling in order to facilitate requirements evolution and maintenance, addressing volatility and traceability issues. We propose an iterative Model-Driven process to solve these issues, based on a double layered CIM to communicate requirements related knowledge to a wider amount of stakeholders. We also present a tool to help requirements engineer through the RE process. Finally we present a case study to illustrate the process and tool s benefits and usage

Estendendo CRefine para o suporte de táticas de refinamento

The use of increasingly complex software applications is demanding greater investment in the development of such systems to ensure applications with better quality. Therefore, new techniques are being used in Software Engineering, thus making the development process more effective. Among these new approaches, we highlight Formal Methods, which use formal languages that are strongly based on mathematics and have a well-defined semantics and syntax. One of these languages is Circus, which can be used to model concurrent systems. It was developed from the union of concepts from two other specification languages: Z, which specifies systems with complex data, and CSP, which is normally used to model concurrent systems. Circus has an associated refinement calculus, which can be used to develop software in a precise and stepwise fashion. Each step is justified by the application of a refinement law (possibly with the discharge of proof obligations). Sometimes, the same laws can be applied in the same manner in different developments or even in different parts of a single development. A strategy to optimize this calculus is to formalise these application as a refinement tactic, which can then be used as a single transformation rule. CRefine was developed to support the Circus refinement calculus. However, before the work presented here, it did not provide support for refinement tactics. The aim of this work is to provide tool support for refinement tactics. For that, we develop a new module in CRefine, which automates the process of defining and applying refinement tactics that are formalised in the tactic language ArcAngelC. Finally, we validate the extension by applying the new module in a case study, which used the refinement tactics in a refinement strategy for verification of SPARK Ada implementations of control systems. In this work, we apply our module in the first two phases of this strategy