In safety critical domains, system test cases are often derived from functional requirements in natural language (NL) and traceability between requirements and their corresponding test cases is usually mandatory. The definition of test cases is therefore time-consuming and error prone, especially so given the quickly rising complexity of embedded systems in many critical domains. Though considerable research has been devoted to automatic generation of system test cases from NL requirements, most of the proposed approaches require significant manual intervention or additional, complex behavioral modelling. This significantly hinders their applicability in practice.In this paper, we propose Use Case Modelling for System Tests Generation (UMTG), an approach that automatically generates executable system test cases from use case specifications and a domain model, the latter including a class diagram and constraints. Our rationale and motivation are that, in many environments, including that of our industry partner in the reported case study, both use case specifications and domain modelling are common and accepted practice, whereas behavioural modelling is considered a difficult and expensive exercise if it is to be complete and precise. In order to extract behavioral information from use cases and enable test automation, UMTG employs Natural Language Processing (NLP), a restricted form of use case specifications, and constraint solving.

Requirements traceability is the ability to relate requirements back to stakeholders and forward to corresponding design artifacts, code, and test cases. Although considerable research has been devoted to relating requirements in both forward and backward directions, less attention has been paid to relating requirements with other requirements. Relations between requirements influence a number of activities during software development such as consistency checking and change management. In most approaches and tools, there is a lack of precise definition of requirements relations. In this respect, deficient results may be produced. In this paper, we aim at formal definitions of the relation types in order to enable reasoning about requirements relations. We give a requirements metamodel with commonly used relation types. The semantics of the relations is provided with a formalization in first-order logic. We use the formalization for consistency checking of relations and for inferring new relations. A tool has been built to support both reasoning activities. We illustrate our approach in an example which shows that the formal semantics of relation types enables new relations to be inferred and contradicting relations in requirements documents to be determined.

Semantic Web evolution brought a new vision into agent research. The interpretation of this second generation web will be realized by autonomous computational entities, called agents, to handle the semantic content on behalf of their human users. Surely, Semantic Web environment has specific architectural entities and a different semantic which must be considered to model a Multi-agent System (MAS) within this environment. Hence, in this study, we introduce a MAS development process which supports the Semantic Web environment. Our approach is based on Model Driven Development (MDD) which aims to change the focus of software development from code to models. We first define an architecture for Semantic Web enabled MASs and then provide a MAS metamodel which consists of the first class meta-entities derived from this architecture. We also define a model transformation process for MDD of such MASs. We present a complete transformation process in which the source and the target metamodels, entity mappings between models and the implementation of the transformation for two different real MAS frameworks by using a well-known model transformation language are all included. In addition to the model-to-model transformation, the implementation of the model-tocode transformation is given as the last step of the system development process. The evaluation of the proposed development process by considering its use within the scope of a real commercial software project is also discussed.

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In many domains such as automotive and avionics, the size and complexity of software systems is quickly increasing. At the same time, many stakeholders tend to be involved in the development of such systems, which typically must also be configured for multiple customers with varying needs. Product Line Engineering (PLE) is therefore an inevitable practice for such systems. Furthermore, because in many areas requirements must be explicit and traceability to them is required by standards, use cases and domain models are common practice for requirements elicitation and analysis. In this paper, based on the above observations, we aim at supporting PLE in the context of use casecentric development. Therefore, we propose, apply, and assess a use case-driven configuration approach which interactively receives configuration decisions from the analysts to generate Product Specific (PS) use case and domain models. Our approach provides the following: (1) a use case-centric product line modeling method (PUM), (2) automated, interactive configuration support based on PUM, and (3) an automatic generation of PS use case and domain models from Product Line (PL) models and configuration decisions. The approach is supported by a tool relying on Natural Language Processing (NLP), and integrated with an industrial requirements management tool, i.e., IBM Doors. We successfully applied and evaluated our approach to an industrial case study in the automotive domain, thus showing evidence that the approach is practical and beneficial to capture variability at the appropriate level of granularity and to configure PS use case and domain models in industrial settings.