Software Project Risk Identification Based on Scrum Artifacts

Risk identification, as a foundational step in risk management, is essential for the success of software development projects, including those using the Scrum methodology. However, risk management in Scrum often lacks structured practices, relying instead on the iterative and collaborative nature of the methodology. This paper presents a novel risk identification framework tailored for Scrum projects, leveraging Scrum artifacts and their associated attributes to enhance risk detection and analysis. The framework encompasses automated data collection from project management environments, such as Jira, thus minimizing the effort required from the project team for risk-related data gathering. By monitoring deviations in artifact attributes and applying predefined thresholds, the framework facilitates the detection of risks at any point in the project lifecycle. Experimental evaluation across three distinct Scrum projects demonstrated the framework’s applicability in identifying a wide range of risks, including long-term ones. The proposed framework contributes to Agile project management by offering a structured, automated approach to risk identification, fostering a culture of proactive risk management within Scrum teams.

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Publication Details

Journal
Applied Sciences
Published
2025-01-16
DOI
https://doi.org/10.3390/app15020824
Citations
1
Primary Topic
Software Engineering Techniques and Practices
Type
article
Field-Weighted Citation Impact
3.25
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article

Software Project Risk Identification Based on Scrum Artifacts

Lina Bisikirskienė, G. Vilutis, Lina Čeponienė, Adelė Nečionytė
1 citations
Applied Sciences
Software Engineering Techniques and Practices
3.25
article

Software Project Risk Identification Based on Scrum Artifacts

Lina Bisikirskienė, G. Vilutis, Lina Čeponienė, Adelė Nečionytė
article en
1 citations

Abstract

Risk identification, as a foundational step in risk management, is essential for the success of software development projects, including those using the Scrum methodology. However, risk management in Scrum often lacks structured practices, relying instead on the iterative and collaborative nature of the methodology. This paper presents a novel risk identification framework tailored for Scrum projects, leveraging Scrum artifacts and their associated attributes to enhance risk detection and analysis. The framework encompasses automated data collection from project management environments, such as Jira, thus minimizing the effort required from the project team for risk-related data gathering. By monitoring deviations in artifact attributes and applying predefined thresholds, the framework facilitates the detection of risks at any point in the project lifecycle. Experimental evaluation across three distinct Scrum projects demonstrated the framework’s applicability in identifying a wide range of risks, including long-term ones. The proposed framework contributes to Agile project management by offering a structured, automated approach to risk identification, fostering a culture of proactive risk management within Scrum teams.

Applied SciencesVol. 15(2)
Kaunas University of Technology (LT)
Openalex Percentile: Top 11%
Software Engineering Techniques and Practices
3.25
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