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  • 1.
    Chatzipetrou, Panagiota
    et al.
    Software Research Engineering Lab (SERL), Blekinge Institute of Technology, Karlskrona, Sweden.
    Alégroth, Emil
    Software Research Engineering Lab (SERL), Blekinge Institute of Technology, Karlskrona, Sweden.
    Papatheocharous, Efi
    RISE SICS AB, Lund, Sweden.
    Borg, Markus
    RISE SICS AB, Lund, Sweden.
    Gorschek, Tony
    Software Research Engineering Lab (SERL), Blekinge Institute of Technology, Karlskrona, Sweden.
    Wnuk, Krzysztof
    Software Research Engineering Lab (SERL), Blekinge Institute of Technology, Karlskrona, Sweden.
    Component selection in Software Engineering: Which attributes are the most important in the decision process?2018Ingår i: 44th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2018: Proceedings / [ed] Bures, T; Angelis, L, IEEE conference proceedings , 2018, s. 198-205Konferensbidrag (Refereegranskat)
    Abstract [en]

    Component-based software engineering is a common approach to develop and evolve contemporary software systems where different component sourcing options are available: 1)Software developed internally (in-house), 2)Software developed outsourced, 3)Commercial of the shelf software, and 4) Open Source Software.

    However, there is little available research on what attributes of a component are the most important ones when selecting new components. The object of the present study is to investigate what matters the most to industry practitioners during component selection. We conducted a cross-domain anonymous survey with industry practitioners involved in component selection. First, the practitioners selected the most important attributes from a list. Next, they prioritized their selection using the Hundred-Dollar ($100) test. We analyzed the results using Compositional Data Analysis. The descriptive results showed that Cost was clearly considered the most important attribute during the component selection. Other important attributes for the practitioners were: Support of the component, Longevity prediction, and Level of off-the-shelf fit to product. Next, an exploratory analysis was conducted based on the practitioners' inherent characteristics. Nonparametric tests and biplots were used. It seems that smaller organizations and more immature products focus on different attributes than bigger organizations and mature products which focus more on Cost.

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