52,486 research outputs found

    Early aspects: aspect-oriented requirements engineering and architecture design

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    This paper reports on the third Early Aspects: Aspect-Oriented Requirements Engineering and Architecture Design Workshop, which has been held in Lancaster, UK, on March 21, 2004. The workshop included a presentation session and working sessions in which the particular topics on early aspects were discussed. The primary goal of the workshop was to focus on challenges to defining methodical software development processes for aspects from early on in the software life cycle and explore the potential of proposed methods and techniques to scale up to industrial applications

    The Ideal Candidate. Analysis of Professional Competences through Text Mining of Job Offers

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    The aim of this paper is to propose analytical tools for identifying peculiar aspects of job market for graduates. We propose a strategy for dealing with daa tat have different source and nature

    K-core decomposition of Internet graphs: hierarchies, self-similarity and measurement biases

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    We consider the kk-core decomposition of network models and Internet graphs at the autonomous system (AS) level. The kk-core analysis allows to characterize networks beyond the degree distribution and uncover structural properties and hierarchies due to the specific architecture of the system. We compare the kk-core structure obtained for AS graphs with those of several network models and discuss the differences and similarities with the real Internet architecture. The presence of biases and the incompleteness of the real maps are discussed and their effect on the kk-core analysis is assessed with numerical experiments simulating biased exploration on a wide range of network models. We find that the kk-core analysis provides an interesting characterization of the fluctuations and incompleteness of maps as well as information helping to discriminate the original underlying structure

    Discovery-led refinement in e-discovery investigations: sensemaking, cognitive ergonomics and system design.

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    Given the very large numbers of documents involved in e-discovery investigations, lawyers face a considerable challenge of collaborative sensemaking. We report findings from three workplace studies which looked at different aspects of how this challenge was met. From a sociotechnical perspective, the studies aimed to understand how investigators collectively and individually worked with information to support sensemaking and decision making. Here, we focus on discovery-led refinement; specifically, how engaging with the materials of the investigations led to discoveries that supported refinement of the problems and new strategies for addressing them. These refinements were essential for tractability. We begin with observations which show how new lines of enquiry were recursively embedded. We then analyse the conceptual structure of a line of enquiry and consider how reflecting this in e-discovery support systems might support scalability and group collaboration. We then focus on the individual activity of manual document review where refinement corresponded with the inductive identification of classes of irrelevant and relevant documents within a collection. Our observations point to the effects of priming on dealing with these efficiently and to issues of cognitive ergonomics at the human–computer interface. We use these observations to introduce visualisations that might enable reviewers to deal with such refinements more efficiently

    The use of data-mining for the automatic formation of tactics

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    This paper discusses the usse of data-mining for the automatic formation of tactics. It was presented at the Workshop on Computer-Supported Mathematical Theory Development held at IJCAR in 2004. The aim of this project is to evaluate the applicability of data-mining techniques to the automatic formation of tactics from large corpuses of proofs. We data-mine information from large proof corpuses to find commonly occurring patterns. These patterns are then evolved into tactics using genetic programming techniques

    IDENTIFYING CORE COMPONENTS IN SOFTWARE SYSTEMS

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    As large software systems are highly complex, they can be difficult for a developer to understand. If a core subset of a software system could be extracted which contains the most important classes and connections of the larger system, studying this core would be useful for efficiently understanding the overall system. In this research we examine research into core/periphery structures in networks, primarily focusing on the use of k-core decomposition. The extracted dependencies of three open source Java software systems provide the inputs, with forty different versions of these systems analyzed in total. We derive inter-class dependencies from these releases and represent them as undirected graphs. We extract the k-core values by recursively pruning the least connected nodes within the networks, leaving an inner core. The resulting coreness values are analyzed against centrality metrics and high-level communities detected by the Louvain method. Both system level and component level evolution of coreness values for these systems are studied. The validity of this approach for identifying software system cores is discussed and analyzed
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