A general framework for positioning, evaluating and selecting the new generation of development tools.

This paper focuses on the evaluation and positioning of a new generation of development tools containing subtools (report generators, browsers, debuggers, GUI-builders, ...) and programming languages that are designed to work together and have a common graphical user interface and are therefore called environments. Several trends in IT have led to a pluriform range of developments tools that can be classified in numerous categories. Examples are: object-oriented tools, GUI-tools, upper- and lower CASE-tools, client/server tools and 4GL environments. This classification does not sufficiently cover the tools subject in this paper for the simple reason that only one criterion is used to distinguish them. Modern visual development environments often fit in several categories because to a certain extent, several criteria can be applied to evaluate them. In this study, we will offer a broad classification scheme with which tools can be positioned and which can be refined through further research.

Early Quantitative Assessment of Non-Functional Requirements

Non-functional requirements (NFRs) of software systems are a well known source of uncertainty in effort estimation. Yet, quantitatively approaching NFR early in a project is hard. This paper makes a step towards reducing the impact of uncertainty due to NRF. It offers a solution that incorporates NFRs into the functional size quantification process. The merits of our solution are twofold: first, it lets us quantitatively assess the NFR modeling process early in the project, and second, it lets us generate test cases for NFR verification purposes. We chose the NFR framework as a vehicle to integrate NFRs into the requirements modeling process and to apply quantitative assessment procedures. Our solution proposal also rests on the functional size measurement method, COSMIC-FFP, adopted in 2003 as the ISO/IEC 19761 standard. We extend its use for NFR testing purposes, which is an essential step for improving NFR development and testing effort estimates, and consequently for managing the scope of NFRs. We discuss the advantages of our approach and the open questions related to its design as well

Do internal software quality tools measure validated metrics?

Internal software quality determines the maintainability of the software product and influences the quality in use. There is a plethora of metrics which purport to measure the internal quality of software, and these metrics are offered by static software analysis tools. To date, a number of reports have assessed the validity of these metrics. No data are available, however, on whether metrics offered by the tools are somehow validated in scientific studies. The current study covers this gap by providing data on which tools and how many validated metrics are provided. The results show that a range of metrics that the tools provided do not seem to be validated in the literature and that only a small percentage of metrics are validated in the provided tools

Highlighting model elements to improve OCL comprehension

Models, metamodels, and model transformations play a central role in Model-Driven Development (MDD). Object Constraint Language (OCL) was initially proposed as part of the Unified Modeling Language (UML) standard to add the precision and validation capabilities lacking in its diagrams, and to express well-formedness rules in its metamodel. OCL has several other applications, such as defining design metrics, code-generation templates, or validation rules for model transformations, required in MDD. Learning OCL as part of a UML course at the university would seem natural but is still the exception rather than the rule. We believe that this is mainly due to a widespread perception that OCL is hard to learn, as gleaned from claims made in the literature. Based on data gathered over the past school years from numerous undergraduate students of di↵erent Software Engineering courses, we analyzed how learning design by contract clauses with UML+OCL compares with several other Software Engineering Body Of Knowledge (SWEBOK) topics. The outcome of the learning process was collected in a rigorous setup, supported by an e-learning platform. We performed inferential statistics on that data to support our conclusions and identify the relevant explanatory variables for students’ success/failure. The obtained findings lead us to extend an existing OCL tool with two novel features: one is aimed at OCL apprentices and goes straight to the heart of the matter by allowing to visualize how OCL expressions traverse UML class diagrams; the other is intended for researchers and allows to compute OCL complexity metrics, making it possible to replicate a research study like the one we are presenting.Modelos, metamodelos e transformações de modelo desempenham um papel central em MDD. OCL foi inicialmente proposta como parte da UML para adicionar os recursos de precisão e validação que faltavam nestes diagramas, e também para expressar regras de boa formação no metamodelo. OCL possui outras aplicações, tais como definir métricas de desenho, modelos de geração de código ou regras de validação para transformações de modelo, exigidas em MDD. Aprender OCL como parte de um curso de UML na universidade parecia portanto natural, não sendo no entanto o que se verifica. Acreditamos que isso se deva a uma percepção generalizada de que OCL é difícil de aprender, tendo em conta afirmações feitas na literatura. Com base em dados recolhidos em anos letivos anteriores de vários alunos de licenciatura de diferentes cursos de Engenharia de Software, analisámos como a aprendizagem por cláusulas contratuais de UML + OCL se compara a outros tópicos do SWEBOK. O resultado do processo de aprendizagem foi recolhido de forma rigorosa, apoiado por uma plataforma de e-learning. Realizámos estatísticas inferenciais sobre os dados para apoiar as nossas conclusões, de forma a identificar as variáveis explicativas relevantes para o sucesso / fracasso dos alunos. As conclusões obtidas levaram-nos a estender uma ferramenta OCL com duas novas funcionalidades: a primeira é voltada para os estudantes de OCL e permite visualizar como as expressões percorrem um diagrama de classes UML; a segunda é voltada para investigadores e permite calcular métricas de complexidade OCL, habilitando a réplica de um estudo semelhante ao apresentado

Proceedings of the ECCS 2005 satellite workshop: embracing complexity in design - Paris 17 November 2005

Embracing complexity in design is one of the critical issues and challenges of the 21st century. As the realization grows that design activities and artefacts display properties associated with complex adaptive systems, so grows the need to use complexity concepts and methods to understand these properties and inform the design of better artifacts. It is a great challenge because complexity science represents an epistemological and methodological swift that promises a holistic approach in the understanding and operational support of design. But design is also a major contributor in complexity research. Design science is concerned with problems that are fundamental in the sciences in general and complexity sciences in particular. For instance, design has been perceived and studied as a ubiquitous activity inherent in every human activity, as the art of generating hypotheses, as a type of experiment, or as a creative co-evolutionary process. Design science and its established approaches and practices can be a great source for advancement and innovation in complexity science. These proceedings are the result of a workshop organized as part of the activities of a UK government AHRB/EPSRC funded research cluster called Embracing Complexity in Design (www.complexityanddesign.net) and the European Conference in Complex Systems (complexsystems.lri.fr). Embracing complexity in design is one of the critical issues and challenges of the 21st century. As the realization grows that design activities and artefacts display properties associated with complex adaptive systems, so grows the need to use complexity concepts and methods to understand these properties and inform the design of better artifacts. It is a great challenge because complexity science represents an epistemological and methodological swift that promises a holistic approach in the understanding and operational support of design. But design is also a major contributor in complexity research. Design science is concerned with problems that are fundamental in the sciences in general and complexity sciences in particular. For instance, design has been perceived and studied as a ubiquitous activity inherent in every human activity, as the art of generating hypotheses, as a type of experiment, or as a creative co-evolutionary process. Design science and its established approaches and practices can be a great source for advancement and innovation in complexity science. These proceedings are the result of a workshop organized as part of the activities of a UK government AHRB/EPSRC funded research cluster called Embracing Complexity in Design (www.complexityanddesign.net) and the European Conference in Complex Systems (complexsystems.lri.fr)