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Assigning-Tasks Method for Developers in Software Projects Using up Similarity Coefficients

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Applied Computer Sciences in Engineering (WEA 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 742))

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Abstract

In the Software industry, big software projects are carried out with hundreds of developers. The fast change in technologies and development environments increase the complexity. Usually, there are project teams with a project leader. However, it is very difficult to know the profile of each developer. The development tasks also have their profile. Hence, it is necessary to assign each task to the most suitable developer. The erroneous assigning of tasks can cause delays and increase the project costs. Thus, a bad assigning of tasks can cause stress and low productivity. Therefore, we make a proposal to enhance tasks assignment to developers regarding the task and developer profiles. The task profile includes characteristics such as: knowledge, kind of task, complexity, experience, etc., in other aspects as codification: paradigm, programming language, version, etc. Using algorithms with similarity coefficients, we look for the best match to assign the tasks to developers. In this work, we used five techniques of similarity coefficient in order to find results and to recommend the best solution for this problem. We conclude that with the Sokal and Sneath technique we obtain better results to solve the problem.

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Correspondence to Sergio Ruiz .

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Ruiz, S., Escudero, D., Cervantes, J., Trueba, A. (2017). Assigning-Tasks Method for Developers in Software Projects Using up Similarity Coefficients. In: Figueroa-García, J., López-Santana, E., Villa-Ramírez, J., Ferro-Escobar, R. (eds) Applied Computer Sciences in Engineering. WEA 2017. Communications in Computer and Information Science, vol 742. Springer, Cham. https://doi.org/10.1007/978-3-319-66963-2_12

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  • DOI: https://doi.org/10.1007/978-3-319-66963-2_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-66962-5

  • Online ISBN: 978-3-319-66963-2

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