Abstract
This paper presents a dynamic reverse engineering approach to extract User Interface (UI) Patterns from existent Web Applications. Firstly, information related to user interaction is saved, in particular: user actions and parameters; the HTML source pages; and the URLs. Secondly, the collected information is analysed in order to calculate several metrics (e.g., the differences between subsequent HTML pages). Thirdly, the existent UI Patterns are inferred from the overall information calculated based on a set of heuristic rules. The overall reverse engineering approach is evaluated with some experiments over several public Web Applications.

Abstract
To cope with the needs raised by the demographic changes in our society, several Ambient-Assisted Living (AAL) technologies have emerged in recent years, but those 'first offers' are often monolithic, incompatible and thus expensive and potentially not sustainable. The AAL4ALL project aims at improving that situation through the development of an open ecosystem of interoperable AAL components (products and services), tied together by an integration infrastructure, comprising a message-queue based service bus and gateways bridging the communication with devices. To that end, the project encompasses the specification of interfaces and requirements for interoperable components, against which candidates can be tested and certified before entering the ecosystem. This paper proposes a testing and certification methodology for such an ecosystem. Besides fulfilling specified pre-requisites, candidate components must pass unit tests that check their conformance with interface specifications and integration tests that check their semantic interoperability with other components in specified orchestration scenarios. Copyright © 2014, IGI Global.

Abstract
In previous work we proposed a performance analysis model for automatically identifying potential root causes of performance problems in personal software development. In this paper we present an approach for automatically ranking those potential root causes based on a cost-benefit estimate that takes into account historical data. The approach was applied for the Personal Software Process, taking advantage of a large data set referring to more than 30,000 projects, but can be replicated in other contexts.

Abstract

Abstract

Abstract
Software development is a knowledge-intensive activity. Software products usually start as a simple idea, or a vision, and then progress towards a final deliverable product. Along this evolution, there is a lot of knowledge that is captured, organized, and shared, leading to new knowledge, both as a whole and within specific development activities. The concept of "Ba" provides a foundation to advance individual and collective knowledge, which describes knowledge creation as a spiral involving tacit and explicit knowledge: the Socialization, Externalization, Combination, Internalization model (a.k.a. SECI model). By applying this foundation to software development, we found issues that may hinder the effective knowledge management cycle. In this paper, we present a vision and a set of requirements for tools to overcome such issues and therefore better support the whole process of software knowledge evolution.