A conversation around the analysis of the SiP effort estimation dataset
This work addresses estimation accuracy in software development for Agile teams, but it is incremental as it builds on existing datasets and methods without major breakthroughs.
The paper analyzed a decade of Agile development data (10,100 task estimates from 22 developers) to identify factors influencing task effort estimation accuracy, such as the estimator, project, and use of round numbers, but found that practice did not significantly improve regression model accuracy.
The analysis of over ten years of commercial development using Agile (10,100 unique task estimates made by 22 developers, under 20 project codes) is documented via a conversation involving the data analyst and a director of the company that created the SiP dataset. Factors found to influence task implementation effort estimation accuracy include the person making the estimate, the project involved, and the propensity to use round numbers. Any improvement in estimation accuracy, with practice, did not noticeably improve regression models fitted.