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A data-driven risk measurement model of software developer turnover

  • Zifei Ma
  • Ruiyin Li
  • Tong Li
  • Rui ZhuEmail author
  • Rong Jiang
  • Juan Yang
  • Mingjing Tang
  • Ming Zheng
Foundations
  • 14 Downloads

Abstract

During the software development life cycle, the turnover of software developers is one of the critical risks that may lead to severe problems (such as postponement and failure of projects), which is often ignored by many professionals. To address this problem, we focus on the uncertainty of turnover risk of software developer (TRSD) and its loss incurred to projects. To tackle this problem, we propose a method to quantify the uncertain risks related to developer turnover, including resignation and replacement. Additionally, to calculate the extent of loss caused by TRSD, we employed machine learning, natural language processing, and data mining techniques to identify software development activities and establish the importance of developers by mining and analyzing the commit event logs. Moreover, based on the information entropy theory, we established a risk measurement model of TRSD that can be used to measure the risk level of each developer and the holistic risk of ongoing software projects. Finally, we validated the feasibility and efficacy through a case study.

Keywords

Data mining Staff turnover Risk measurement Software project management Information entropy 

Notes

Acknowledgements

We thank all anonymous interviewees and reviewers and appreciate their time and effort. This work is supported by National Natural Science Foundation of China (Grant Nos. 61662085, 61763048, 71972165), the Yunnan University Data-Driven Software Engineering Provincial Science and Technology Innovation Team Project (Grant No. 2017HC012), the 9th Post-Graduate Research Innovation Project of Yunnan University (Grant No. YDY17093), Science and Technology Foundation of Yunnan Province (Grant Nos. 2017FB095, 201901S070110), the Yunnan Provincial Natural Science Foundation Fundamental Research Project (Grant No. 2019FB-16), and the Yunnan University “Dong Lu Young-backbone Teacher” Training Program (Grant No. C176220200).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and national research committee and with the 1975 Helsinki Declaration and its later amendments or comparable ethical standards.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Zifei Ma
    • 1
    • 3
  • Ruiyin Li
    • 1
  • Tong Li
    • 2
    • 3
  • Rui Zhu
    • 1
    • 3
    Email author
  • Rong Jiang
    • 4
  • Juan Yang
    • 5
  • Mingjing Tang
    • 6
  • Ming Zheng
    • 1
  1. 1.School of SoftwareYunnan UniversityKunmingChina
  2. 2.School of Big DataYunnan Agricultural UniversityKunmingChina
  3. 3.Key Lab of Software Engineering of Yunnan ProvinceKunmingChina
  4. 4.School of InformationYunnan University of Finance and EconomicsKunmingChina
  5. 5.Kunming Open CollegeKunmingChina
  6. 6.School of Information Science and TechnologyYunnan Normal UniversityKunmingChina

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