CASP-DM: Context Aware Standard Process for Data Mining

We propose an extension of the Cross Industry Standard Process for Data Mining (CRISPDM) which addresses specific challenges of machine learning and data mining for context and model reuse handling. This new general context-aware process model is mapped with CRISP-DM reference model proposing some new or enhanced outputs

Reusability in software engineering

This paper surveys recent work concerning reusability in software engineering. The current directions in software reusability are discussed, and the two major approaches of reusable building blocks and reusable patterns studied. An extensive bibliography, parts of which are annotated, is included

Using neural networks in software repositories

The first topic is an exploration of the use of neural network techniques to improve the effectiveness of retrieval in software repositories. The second topic relates to a series of experiments conducted to evaluate the feasibility of using adaptive neural networks as a means of deriving (or more specifically, learning) measures on software. Taken together, these two efforts illuminate a very promising mechanism supporting software infrastructures - one based upon a flexible and responsive technology

An IMS-Learning Design Editor for a Higher Education Blended Learning Scenario

The IMS-Learning Design has been developed to support the creation of reusable and pedagogically neutral learning scenarios and content. Although it is especially suitable for eLearning, there is a lot of interest on using it in higher education blended learning scenarios. However there are some related key issues which must be managed such as cultural bias and the need for expensive human resources to design and develop specification compliant units of learning. They can be addressed by the design of ad-hoc editors supporting concrete learning design units of learning. We suggest some solutions to overcome these limitations, based on our experience designing the user interface of an IMS-LD compliant editor, GDUS+. We also explain our user centering approach, and give some conclusions about the benefits of using IMS-LD

Mining and quality assessment of mashup model patterns with the crowd: A feasibility study

Pattern mining, that is, the automated discovery of patterns from data, is a mathematically complex and computationally demanding problem that is generally not manageable by humans. In this article, we focus on small datasets and study whether it is possible to mine patterns with the help of the crowd by means of a set of controlled experiments on a common crowdsourcing platform. We specifically concentrate on mining model patterns from a dataset of real mashup models taken from Yahoo! Pipes and cover the entire pattern mining process, including pattern identification and quality assessment. The results of our experiments show that a sensible design of crowdsourcing tasks indeed may enable the crowd to identify patterns from small datasets (40 models). The results, however, also show that the design of tasks for the assessment of the quality of patterns to decide which patterns to retain for further processing and use is much harder (our experiments fail to elicit assessments from the crowd that are similar to those by an expert). The problem is relevant in general to model-driven development (e.g., UML, business processes, scientific workflows), in that reusable model patterns encode valuable modeling and domain knowledge, such as best practices, organizational conventions, or technical choices, that modelers can benefit from when designing their own models

Quality-aware model-driven service engineering

Service engineering and service-oriented architecture as an integration and platform technology is a recent approach to software systems integration. Quality aspects ranging from interoperability to maintainability to performance are of central importance for the integration of heterogeneous, distributed service-based systems. Architecture models can substantially influence quality attributes of the implemented software systems. Besides the benefits of explicit architectures on maintainability and reuse, architectural constraints such as styles, reference architectures and architectural patterns can influence observable software properties such as performance. Empirical performance evaluation is a process of measuring and evaluating the performance of implemented software. We present an approach for addressing the quality of services and service-based systems at the model-level in the context of model-driven service engineering. The focus on architecture-level models is a consequence of the black-box character of services

Component-based software engineering: a quantitative approach

Dissertação apresentada para a obtenção do Grau de Doutor em Informática pela Universidade Nova de Lisboa, Faculdade de Ciências e TecnologiaBackground: Often, claims in Component-Based Development (CBD) are only supported by qualitative expert opinion, rather than by quantitative data. This contrasts with the normal practice in other sciences, where a sound experimental validation of claims is standard practice. Experimental Software Engineering (ESE) aims to bridge this gap. Unfortunately, it is common to find experimental validation efforts that are hard to replicate and compare, to build up the body of knowledge in CBD. Objectives: In this dissertation our goals are (i) to contribute to evolution of ESE, in what concerns the replicability and comparability of experimental work, and (ii) to apply our proposals to CBD, thus contributing to its deeper and sounder understanding. Techniques: We propose a process model for ESE, aligned with current experimental best practices, and combine this model with a measurement technique called Ontology-Driven Measurement (ODM). ODM is aimed at improving the state of practice in metrics definition and collection, by making metrics definitions formal and executable,without sacrificing their usability. ODM uses standard technologies that can be well adapted to current integrated development environments. Results: Our contributions include the definition and preliminary validation of a process model for ESE and the proposal of ODM for supporting metrics definition and collection in the context of CBD. We use both the process model and ODM to perform a series experimental works in CBD, including the cross-validation of a component metrics set for JavaBeans, a case study on the influence of practitioners expertise in a sub-process of component development (component code inspections), and an observational study on reusability patterns of pluggable components (Eclipse plug-ins). These experimental works implied proposing, adapting, or selecting adequate ontologies, as well as the formal definition of metrics upon each of those ontologies. Limitations: Although our experimental work covers a variety of component models and, orthogonally, both process and product, the plethora of opportunities for using our quantitative approach to CBD is far from exhausted. Conclusions: The main contribution of this dissertation is the illustration, through practical examples, of how we can combine our experimental process model with ODM to support the experimental validation of claims in the context of CBD, in a repeatable and comparable way. In addition, the techniques proposed in this dissertation are generic and can be applied to other software development paradigms.Departamento de Informática of the Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa (FCT/UNL); Centro de Informática e Tecnologias da Informação of the FCT/UNL; Fundação para a Ciência e Tecnologia through the STACOS project(POSI/CHS/48875/2002); The Experimental Software Engineering Network (ESERNET);Association Internationale pour les Technologies Objets (AITO); Association forComputing Machinery (ACM

SOFTWARE REUSE: SURVEY AND RESEARCH DIRECTIONS

Software reuse is the use of software resources from all stages of the software development process in new applications. Given the high cost and difficulty of developing high quality software, the idea of capitalizing on previous software investments is appealing. However, software reuse has not been as effective as expected and has not been very broadly or systematically used in industry. This paper surveys recent software reuse research using a framework that helps identify and organize the many factors that must be considered to achieve the benefits of software reuse in practice. We argue that software reuse needs to be viewed in the context of a total systems approach that addresses a broad range of technical, economic, managerial, organizational and legal issues and conclude with a summary of the major research issues in each of these areas.Information Systems Working Papers Serie