Semantics Through Pictures: towards a diagrammatic semantics for object-oriented modelling notations

An object-oriented (OO) model has a static component, the set of allowable snapshots or system states, and a dynamic component, the set of filmstrips or sequences of snapshots. Diagrammatic notations, such as those in UML, each places constraints on the static and/or dynamic models. A formal semantics of OO modeling notations can be constructed by providing a formal description of (i) sets of snapshots and filmstrips, (ii) constraints on those sets, and (iii) the derivation of those constraints from diagrammatic notations. In addition, since constraints are contributed by many diagrams for the same model, a way of doing this compositionally is desirable. One approach to the semantics is to use first-order logic for (i) and (ii), and theory inclusion with renaming, as in Larch, to characterize composition. A common approach to (iii) is to bootstrap: provide a semantics for a kernel of the notation and then use the kernel to give a semantics to the other notations. This only works if a kernel which is sufficiently expressive can be identified, and this is not the case for UML. However, we have developed a diagrammatic notation, dubbed constraint diagrams, which seems capable of expressing most if not all static and dynamic constraints, and it is proposed that this be used to give a diagrammatic semantics to OO models

Constraint Diagrams: Visualizing Assertions in OO Modelling

Describes a notation, constraint diagrams, which allows pre/post conditions and invariants to be expressed visually, rather than in the notation of mathematical logic. The notation is explored through a small case study (a library system). Some conclusions are drawn about the use of the notation in modelling, and its possible impact on tools and semantics. This report has been split into two and considerable revised and updated: Kent (1997b), Kent (1997c)

Generating natural language specifications from UML class diagrams

Early phases of software development are known to be problematic, difficult to manage and errors occurring during these phases are expensive to correct. Many systems have been developed to aid the transition from informal Natural Language requirements to semistructured or formal specifications. Furthermore, consistency checking is seen by many software engineers as the solution to reduce the number of errors occurring during the software development life cycle and allow early verification and validation of software systems. However, this is confined to the models developed during analysis and design and fails to include the early Natural Language requirements. This excludes proper user involvement and creates a gap between the original requirements and the updated and modified models and implementations of the system. To improve this process, we propose a system that generates Natural Language specifications from UML class diagrams. We first investigate the variation of the input language used in naming the components of a class diagram based on the study of a large number of examples from the literature and then develop rules for removing ambiguities in the subset of Natural Language used within UML. We use WordNet,a linguistic ontology, to disambiguate the lexical structures of the UML string names and generate semantically sound sentences. Our system is developed in Java and is tested on an independent though academic case study

Towards Practical Graph-Based Verification for an Object-Oriented Concurrency Model

To harness the power of multi-core and distributed platforms, and to make the development of concurrent software more accessible to software engineers, different object-oriented concurrency models such as SCOOP have been proposed. Despite the practical importance of analysing SCOOP programs, there are currently no general verification approaches that operate directly on program code without additional annotations. One reason for this is the multitude of partially conflicting semantic formalisations for SCOOP (either in theory or by-implementation). Here, we propose a simple graph transformation system (GTS) based run-time semantics for SCOOP that grasps the most common features of all known semantics of the language. This run-time model is implemented in the state-of-the-art GTS tool GROOVE, which allows us to simulate, analyse, and verify a subset of SCOOP programs with respect to deadlocks and other behavioural properties. Besides proposing the first approach to verify SCOOP programs by automatic translation to GTS, we also highlight our experiences of applying GTS (and especially GROOVE) for specifying semantics in the form of a run-time model, which should be transferable to GTS models for other concurrent languages and libraries.Comment: In Proceedings GaM 2015, arXiv:1504.0244

An architecture and methodology for the design and development of Technical Information Systems

In order to meet demands in the context of Technical Information Systems (TIS) pertaining to reliability, extensibility, maintainability, etc., we have developed an architectural framework with accompanying methodological guidelines for designing such systems. With the framework, we aim at complex multiapplication information systems using a repository to share data among applications. The framework proposes to keep a strict separation between Man-Machine-Interface and Model data, and provides design and implementation support to do this effectively.\ud The framework and methodological guidelines have been developed in the context of the ESPRIT project IMPRESS. The project also provided for ldquotesting groundsrdquo in the form of a TIS for the Spanish Electricity company Iberdrola.\ud This work has been conducted within the ESPRIT project IMPRESS (Integrated, Multi-Paradigm, Reliable and Extensible Storage System), ESPRIT No. 635

Analysis and design of multiagent systems using MAS-CommonKADS

This article proposes an agent-oriented methodology called MAS-CommonKADS and develops a case study. This methodology extends the knowledge engineering methodology CommonKADSwith techniquesfrom objectoriented and protocol engineering methodologies. The methodology consists of the development of seven models: Agent Model, that describes the characteristics of each agent; Task Model, that describes the tasks that the agents carry out; Expertise Model, that describes the knowledge needed by the agents to achieve their goals; Organisation Model, that describes the structural relationships between agents (software agents and/or human agents); Coordination Model, that describes the dynamic relationships between software agents; Communication Model, that describes the dynamic relationships between human agents and their respective personal assistant software agents; and Design Model, that refines the previous models and determines the most suitable agent architecture for each agent, and the requirements of the agent network