Authors : S. M. T. D. Samarakoon; R. L. Dangalla

Volume/Issue : Volume 11 - 2026, Issue 2 - February

Google Scholar : https://tinyurl.com/3ytrspjz

Scribd : https://tinyurl.com/ycx2s3hw

DOI : https://doi.org/10.38124/ijisrt/26feb300

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : Agile project management, focusing on flexibility and iterative delivery, has a tendency to view issue resolution timing as vague and thus has a tendency to result in schedule overruns and resource planning inefficiency. This research contributes a large-scale statistical approach to predicting issue resolution patterns from historical JIRA data, providing quantitative analysis to the project managers to enhance sprint planning and resource allocation. It utilizes time-series analysis with a broad dataset of 1,095 days of issue tracking record sourced from a publicly available Kaggle dataset, being actual software development projects. It uses an Auto Regressive Integrated Moving Average (ARIMA) model that effectively tests various setups of parameters using stringent statistical tests. The optimal ARIMA (1,1,1) model demonstrated strong forecasting capability, as indicated by the performance metrics: AIC (Akaike Information Criterion) = 1872.52, BIC (Bayesian Information Criterion) = 1887.07, & extremely low error metrics (Mean Absolute Error = 0.0006525, Root mean squared Error = 3.2501). The results validate the efficiency of the model for forecasting issues resolved per day and establishing patterns over time in team productivity. This research provides robust variations in resolution rate prediction across development cycle stages, with high performance in stable sprints. The model output shows good estimation of team capacity for data-driven sprint backlogs and deadline realignment. This research adds a practical, scalable approach for JIRA-using teams, bridging the gap between Agile principles and data science.

Keywords : Agile Project Management, Issue Resolution Forecasting, JIRA, ARIMA Modeling, Sprint Backlog.

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