26,625 research outputs found

    Comment-based concept location over system dependency graphs

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    Software maintenance is one of the most expensive phases of software development and understanding a program is one of the most important tasks of software maintenance. Before making the change to the program, software engineers need to find the location, or locations, where the changes will be made, they need to understand the program. Real applications are huge, sometimes old, were written by other person and it is difficult to find the location of the instructions related to a specific problem domain concept. There are various techniques to find these locations minimizing the time spent, but this stage of software development continues to be one of the most expensive and longer. The concept location is a crucial task for program understanding. This paper presents a project whose main objective is to explore and combine two Program Comprehension techniques: visualization of the system dependency graph and concept location over source code comments. The idea is to merge both features in order to perform concept location in system dependency graphs. More than locate a set of hot instructions (based on the associated comments) it will allow to detect the other instructions (the whole method).(undefined

    Comment-based Concept Location over System Dependency Graphs

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    Abstract Software maintenance is one of the most expensive phases of software development and understanding a program is one of the most important tasks of software maintenance. Before making the change to the program, software engineers need to find the location, or locations, where the changes will be made, they need to understand the program. Real applications are huge, sometimes old, were written by other person and it is difficult to find the location of the instructions related to a specific problem domain concept. There are various techniques to find these locations minimizing the time spent, but this stage of software development continues to be one of the most expensive and longer. The concept location is a crucial task for program understanding. This paper presents a project whose main objective is to explore and combine two Program Comprehension techniques: visualization of the system dependency graph and concept location over source code comments. The idea is to merge both features in order to perform concept location in system dependency graphs. More than locate a set of hot instructions (based on the associated comments) it will allow to detect the other instructions (the whole method). ACM Subject Classification D.2.7 Maintenanc

    On the Effect of Semantically Enriched Context Models on Software Modularization

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    Many of the existing approaches for program comprehension rely on the linguistic information found in source code, such as identifier names and comments. Semantic clustering is one such technique for modularization of the system that relies on the informal semantics of the program, encoded in the vocabulary used in the source code. Treating the source code as a collection of tokens loses the semantic information embedded within the identifiers. We try to overcome this problem by introducing context models for source code identifiers to obtain a semantic kernel, which can be used for both deriving the topics that run through the system as well as their clustering. In the first model, we abstract an identifier to its type representation and build on this notion of context to construct contextual vector representation of the source code. The second notion of context is defined based on the flow of data between identifiers to represent a module as a dependency graph where the nodes correspond to identifiers and the edges represent the data dependencies between pairs of identifiers. We have applied our approach to 10 medium-sized open source Java projects, and show that by introducing contexts for identifiers, the quality of the modularization of the software systems is improved. Both of the context models give results that are superior to the plain vector representation of documents. In some cases, the authoritativeness of decompositions is improved by 67%. Furthermore, a more detailed evaluation of our approach on JEdit, an open source editor, demonstrates that inferred topics through performing topic analysis on the contextual representations are more meaningful compared to the plain representation of the documents. The proposed approach in introducing a context model for source code identifiers paves the way for building tools that support developers in program comprehension tasks such as application and domain concept location, software modularization and topic analysis

    The French research system : which evolution and which borders ?

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    We analyse the French Research System with the study of the contracts between the CNRS (Centre National de la Recherche Scientifique) and the companies and test the hypothesis of small world in science. Our working material is the data base of the contracts of the units of the CNRS with economic partners, which has been collecting information since 1986 to 2006. This first application of Network methods and tools to the CNRS contracts allows us to obtain some results: at first, the major firms’s scientific network is not "scale-free" as if competition and strategy between the most large firms dominate the behaviour in R&D investments and management of contracts with public research units. However, in second part, we demonstrate that every discipline network is a "small world", i.e. , that it exists several scientific communities in which the diffusion of information is free and easy, even if its forwards through any actors (some labs or some firms). Probably, there are several "small worlds" in this database as in the scientific collaboration networks. Is seems that the industrial research does not disturb too much the properties of scientific network, as it’s well known in the literature of Sciences Studies

    DALiuGE: A Graph Execution Framework for Harnessing the Astronomical Data Deluge

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    The Data Activated Liu Graph Engine - DALiuGE - is an execution framework for processing large astronomical datasets at a scale required by the Square Kilometre Array Phase 1 (SKA1). It includes an interface for expressing complex data reduction pipelines consisting of both data sets and algorithmic components and an implementation run-time to execute such pipelines on distributed resources. By mapping the logical view of a pipeline to its physical realisation, DALiuGE separates the concerns of multiple stakeholders, allowing them to collectively optimise large-scale data processing solutions in a coherent manner. The execution in DALiuGE is data-activated, where each individual data item autonomously triggers the processing on itself. Such decentralisation also makes the execution framework very scalable and flexible, supporting pipeline sizes ranging from less than ten tasks running on a laptop to tens of millions of concurrent tasks on the second fastest supercomputer in the world. DALiuGE has been used in production for reducing interferometry data sets from the Karl E. Jansky Very Large Array and the Mingantu Ultrawide Spectral Radioheliograph; and is being developed as the execution framework prototype for the Science Data Processor (SDP) consortium of the Square Kilometre Array (SKA) telescope. This paper presents a technical overview of DALiuGE and discusses case studies from the CHILES and MUSER projects that use DALiuGE to execute production pipelines. In a companion paper, we provide in-depth analysis of DALiuGE's scalability to very large numbers of tasks on two supercomputing facilities.Comment: 31 pages, 12 figures, currently under review by Astronomy and Computin

    The sum of edge lengths in random linear arrangements

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    Spatial networks are networks where nodes are located in a space equipped with a metric. Typically, the space is two-dimensional and until recently and traditionally, the metric that was usually considered was the Euclidean distance. In spatial networks, the cost of a link depends on the edge length, i.e. the distance between the nodes that define the edge. Hypothesizing that there is pressure to reduce the length of the edges of a network requires a null model, e.g., a random layout of the vertices of the network. Here we investigate the properties of the distribution of the sum of edge lengths in random linear arrangement of vertices, that has many applications in different fields. A random linear arrangement consists of an ordering of the elements of the nodes of a network being all possible orderings equally likely. The distance between two vertices is one plus the number of intermediate vertices in the ordering. Compact formulae for the 1st and 2nd moments about zero as well as the variance of the sum of edge lengths are obtained for arbitrary graphs and trees. We also analyze the evolution of that variance in Erdos-Renyi graphs and its scaling in uniformly random trees. Various developments and applications for future research are suggested
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