2013Unpublished venueRequires access

Prediction of project problem effects on software risk factors

Mustafa Özgür Cingiz, Ahmet Unudulmaz, Oya Kalıpsız

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Abstract

Software risks can be defined as uncertainty and loss in project process. Software risk management consists of risk identification, estimation, refinement, mitigation, monitoring and maintenance steps. In our study we focus on prediction of project problem effects that can cause loss in software project in terms of their values on risk factors and also we want to rank our risk factors to observe how they can give detail about project problem effects separately. For these purpose five classification methods for prediction of problem impact and two filter feature selection methods for ranking importance of risk factors are used in this study.

About this research paper

What this paper is about

Software risks can be defined as uncertainty and loss in project process. Software risk management consists of risk identification, estimation, refinement, mitigation, monitoring and maintenance steps. In our study we focus on prediction of project problem effects that can cause loss in software project in terms of their values on risk factors and also we want to rank our risk factors to observe how they can give detail about project problem effects separately. For these purpose five classification methods for prediction of problem impact and two filter feature selection methods for ranking importance of risk factors are used in this study.

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OpenAlex reports 2 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Software risks can be defined as uncertainty and loss in project process. Software risk management consists of risk identification, estimation, refinement, mitigation, monitoring and maintenance steps. In our study we focus on prediction of project problem effects that can cause loss in software project in terms of their values on risk factors and also we want to rank our risk factors to observe how they can give detail about project problem effects separately. For these purpose five classification methods for prediction of problem impact and two filter feature selection methods for ranking importance of risk factors are used in this study.

Key concepts: Computer science, Project risk management, Ranking (information retrieval), Software project management, Risk analysis (engineering), Software, Risk management, Identification (biology)

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