Definition of a support infrastructure for replicating and aggregating families of software engineering experiments

Experimental software engineering includes several processes, the most representative being run experiments, run replications and synthesize the results of multiple replications. Of these processes, only the first is relatively well established in software engineering. Problems of information management and communication among researchers are one of the obstacles to progress in the replication and synthesis processes. Software engineering experimentation has expanded considerably over the last few years. This has brought with it the invention of experimental process support proposals. However, few of these proposals provide integral support, including replication and synthesis processes. Most of the proposals focus on experiment execution. This paper proposes an infrastructure providing integral support for the experimental research process, specializing in the replication and synthesis of a family of experiments. The research has been divided into stages or phases, whose transition milestones are marked by the attainment of their goals. Each goal exactly matches an artifact or product. Within each stage, we will adopt cycles of successive approximations (generateand- test cycles), where each approximation includes a diferent viewpoint or input. Each cycle will end with the product approval.

Some Reflections on Engineering Education as a Tool for the next Knowledge Society

The aim of this paper is to offer a broad panorama of some aspects related with Engineering Education in a Knowledge Society.

Modelling spatial decisión support systems focused on the development of a data warehouse: applying software engineering

Nowadays, organizations have plenty of data stored in DB databases, which contain invaluable information. Decision Support Systems DSS provide the support needed to manage this information and planning médium and long-term ?the modus operandi? of these organizations. Despite the growing importance of these systems, most proposals do not include its total evelopment, mostly limiting itself on the development of isolated parts, which often have serious integration problems. Hence, methodologies that include models and processes that consider every factor are necessary. This paper will try to fill this void as it proposes an approach for developing spatial DSS driven by the development of their associated Data Warehouse DW, without forgetting its other components. To the end of framing the proposal different Engineering Software focus (The Software Engineering Process and Model Driven Architecture) are used, and coupling with the DB development methodology, (and both of them adapted to DW peculiarities). Finally, an example illustrates the proposal.

Promotion of professional skills in engineering education: strategies and challenges

Basic engineering skills are not the only key to professional development, particularly as engineering problems are everyday more and more complex and multifaceted, hence requiring the implementation of larger multidisciplinary teams, in many cases working in an international context and in a continuously evolving environment. Therefore other outcomes, sometimes referred to as professional skills, are also necessary for our students, as most universities are already aware. In this study we try to methodically analyze the main strategies for the promotion of professional skills, mainly linked to actuations which directly affect students or teachers (and teaching methodologies) and which take advantage of the environment and available resources. From an initial list of 51 strategies (in essence aimed at promotion of different drivers of change, linked to students, teachers, environment and resources), we focus on the 11 drivers of change considered more important after an initial evaluation. Subsequently, a systematic analysis of the typical problems linked to these main drivers of change, enables us to find and formulate 12 major and usually repeated and unsolved problems. After selecting these typical problems, we put forward 25 different solutions, for short-term actuation, and discuss their effects, while bearing in mind our team’s experience, together with the information from the studies carried out by numerous teaching staff from other universities.

Replications of software engineering experiments

There are many open issues that must be addressed before the replication process can be successfully formalized in empirical software engineering research. We define replication as the deliberate repetition of the same empirical study for the purpose of determining whether the results of the first experiment can be reproduced. This definition would appear at first glance to be good. However, it needs several clarifications that have not yet been forthcoming in software engineering: – What is the exact meaning of the same empirical study? Namely how similar should an experiment be to the baseline study for it to be considered a replication? What is the exact meaning of a result being reproduced? Namely how similar does a result have to be to the result of the baseline study for it to be considered reproduced? These and other methodological questions need to be researched and tailored for empirical software engineering.

Engineering education on geosciences in a changing world

Engineering aims to work with what knowledge is available to achieve society's goals (Coyle, Murphy, and Grimson 2007). The current environmental challenges and the characteristics of the labour market mean that the effectiveness of Engineering activities in Geosciences must be increased through the development of technical knowledge and the inclusion of suitable training aimed at solving real cases (European Commission 2010). Human capital – understood as the talents, skills and capabilities of higher education graduates – is perceived as an essential element for sustainable economic growth and development in the globalised economy (Sianesi and Van Reenan 2003). We need, therefore, to rethink our approaches to curriculum, instruction and assessment in science education, particularly because of the rapid growth of the scientific knowledge, tools/technologies and theories that have originated over the last 50 years (Duschl and Grandy 2013).

Understanding replication of experiments in software engineering: a classification

Context: Replication plays an important role in experimental disciplines. There are still many uncertain- ties about how to proceed with replications of SE experiments. Should replicators reuse the baseline experiment materials? How much liaison should there be among the original and replicating experiment- ers, if any? What elements of the experimental configuration can be changed for the experiment to be considered a replication rather than a new experiment? Objective: To improve our understanding of SE experiment replication, in this work we propose a classi- fication which is intend to provide experimenters with guidance about what types of replication they can perform. Method: The research approach followed is structured according to the following activities: (1) a litera- ture review of experiment replication in SE and in other disciplines, (2) identification of typical elements that compose an experimental configuration, (3) identification of different replications purposes and (4) development of a classification of experiment replications for SE. Results: We propose a classification of replications which provides experimenters in SE with guidance about what changes can they make in a replication and, based on these, what verification purposes such a replication can serve. The proposed classification helped to accommodate opposing views within a broader framework, it is capable of accounting for less similar replications to more similar ones regarding the baseline experiment. Conclusion: The aim of replication is to verify results, but different types of replication serve special ver- ification purposes and afford different degrees of change. Each replication type helps to discover partic- ular experimental conditions that might influence the results. The proposed classification can be used to identify changes in a replication and, based on these, understand the level of verification.

Structural models for architectural and engineering education,

Includes bibliography.

The use of computers in engineering education; report. 1st-3d; 1960-62.

Cover title, 1960: Electronic computers in engineering education; report.

Nuclear science in engineering education : a selected list of references for instructors /

Includes bibliographical references.

Evaluation of an engineering education.

Mode of access: Internet.

The Journal of engineering education.

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Mode of access: Internet.