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A Semi-supervised Learning Framework for Decision Modeling of Software Project Management

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Information and Software Technologies (ICIST 2014)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 465))

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Abstract

Managing the decisions in organizations raises substantial challenges in regards of the associated processes. In software project management decision making has the critical role in this scenario since it defines the manager’s responsibilities and stems from the various sources linked to the process. The decision making constructs the essential foundation and thereby it needs a reliable framework for modeling of the decision structure. In this paper a conceptual multi-method simulation based framework will be introduced in a modality to cover multiple levels of the decision structure over software project management process. The framework is base on a model in which is inspired by a semi-supervised learning technique known as partially observable Markov decision process (POMDP). The methods used are integrated towards a multi-method simulation model whereas each of these methods exclusively realizes distinct aspect of software project management. The framework evolves the manner of decision making by a paradigm which establishes the foundation for a tactical level understanding and decision support for practitioners. At the results section an optimal decision policy for the framework will be presented.

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Author information

Authors and Affiliations

  1. Department of Software Engineering, Advanced Informatics School, Universiti Teknologi Malaysia, Kuala Lumpur, 54100, Malaysia

    Ali Tizkar Sadabadi

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  1. Ali Tizkar Sadabadi
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Editor information

Editors and Affiliations

  1. Kaunas University of Technology, Studentu g. 50-409a,, LT-51368, Kaunas, Lithuania

    Giedre Dregvaite

  2. Kaunas University of Technology, Studentu g. 50-409a, LT-51368, Kaunas, Lithuania

    Robertas Damasevicius

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Sadabadi, A.T. (2014). A Semi-supervised Learning Framework for Decision Modeling of Software Project Management. In: Dregvaite, G., Damasevicius, R. (eds) Information and Software Technologies. ICIST 2014. Communications in Computer and Information Science, vol 465. Springer, Cham. https://doi.org/10.1007/978-3-319-11958-8_11

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  • DOI: https://doi.org/10.1007/978-3-319-11958-8_11

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11957-1

  • Online ISBN: 978-3-319-11958-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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