17,523 research outputs found

    Towards Integrated Variant Management in Global Software Engineering: An Experience Report

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    In the automotive domain, customer demands and market constraints are progressively realized by electric/ electronic components and corresponding software. Variant traceability in SPL is crucial in the context of different tasks, like change impact analysis, especially in complex global software projects. In addition, traceability concepts must be extended by partly automated variant configuration mechanisms to handle restrictions and dependencies between variants. Such variant configuration mechanism helps to reduce complexity when configuring a valid variant and to establish an explicit documentation of dependencies between components. However, integrated variant management has not been sufficiently addressed so far. Especially, the increasing number of software variants requires an examination of traceable and configurable software variants over the software lifecycle. This paper emphasizes variant traceability achievements in a large global software engineering project, elaborates existing challenges, and evaluates an industrial usage of an integrated variant management based on experiences

    Coordinating Knowledge Work in Multi-Team Programs: Findings from a Large-Scale Agile Development Program

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    Software development projects have undergone remarkable changes with the arrival of agile development methods. While intended for small, self-managing teams, these methods are increasingly used also for large development programs. A major challenge in programs is to coordinate the work of many teams, due to high uncertainty in tasks, a high degree of interdependence between tasks and because of the large number of people involved. This revelatory case study focuses on how knowledge work is coordinated in large-scale agile development programs by providing a rich description of the coordination practices used and how these practices change over time in a four year development program with 12 development teams. The main findings highlight the role of coordination modes based on feedback, the use of a number of mechanisms far beyond what is described in practitioner advice, and finally how coordination practices change over time. The findings are important to improve the outcome of large knowledge-based development programs by tailoring coordination practices to needs and ensuring adjustment over time.Comment: To appear in Project Management Journa

    State-of-the-Art in Parallel Computing with R

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    R is a mature open-source programming language for statistical computing and graphics. Many areas of statistical research are experiencing rapid growth in the size of data sets. Methodological advances drive increased use of simulations. A common approach is to use parallel computing. This paper presents an overview of techniques for parallel computing with R on computer clusters, on multi-core systems, and in grid computing. It reviews sixteen different packages, comparing them on their state of development, the parallel technology used, as well as on usability, acceptance, and performance. Two packages (snow, Rmpi) stand out as particularly useful for general use on computer clusters. Packages for grid computing are still in development, with only one package currently available to the end user. For multi-core systems four different packages exist, but a number of issues pose challenges to early adopters. The paper concludes with ideas for further developments in high performance computing with R. Example code is available in the appendix
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