Probabilistic Approach to Predicting Risk in Software Projects Using Software Repository Data

Changkyun Jeon, Neunghoe Kim, Hoh Peter In

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


Although the factors that need to be focused on for a successful software project appear to be difficult to define, risk management has become one of the key activities for achieving such success because significant risk is involved in each software development phase. Software project failures are often a result of insufficient and ineffective risk information regarding the future. To overcome this, software risk prediction should be performed in advance to allow project managers insight into providing more valuable information for decision making, such as scope coverage, resource allocation, and schedule changes. In this research, we propose a risk prediction model from the perspective of quality using a software repository. We evaluated the risk threat level by mapping some defect attributes that exist in the defect lifecycle, defined their risk threat transition states, and applied a Markov chain for predicting the potential risk level. We evaluated the proposed approach using practical real-industry mobile software projects. The experimental results confirm that our approach is applicable to software threat risk estimation.

Original languageEnglish
Pages (from-to)1017-1032
Number of pages16
JournalInternational Journal of Software Engineering and Knowledge Engineering
Issue number6
Publication statusPublished - 2015 Aug 1

Bibliographical note

Funding Information:
This research was supported by the Next-Generation Information Computing Development Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (2012M3C4A7033345), and Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education, Science and Technology (2012R1A1A2009021).

Publisher Copyright:
© 2015 World Scientific Publishing Company.


  • Software risk
  • project management
  • software engineering
  • software repository

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications
  • Computer Graphics and Computer-Aided Design
  • Artificial Intelligence


Dive into the research topics of 'Probabilistic Approach to Predicting Risk in Software Projects Using Software Repository Data'. Together they form a unique fingerprint.

Cite this