Agile Sprint Productivity Analysis via Commit History
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Solution Overview
Problem
It is challenging to objectively measure the productivity and stability of agile development teams, as existing methods rely heavily on subjective assessments and increase the burden on development members.
Innovation Solution
An analyzing device and method that acquire commit history from development repositories, calculate statistical information by aggregating commit histories in units of development cycles, and display this information to provide objective metrics for productivity and stability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If questionnaire, man-months, and test density measurement techniques are strengthened to calculate objective productivity index, then measurement objectivity is improved, but burden on development members increases
Solution Approach 1:
The system automatically collects commit history data from the version control repository without requiring active participation or input from development members. The commit history is passively extracted and analyzed, allowing the system to serve itself by using already-existing development artifacts (commit records) rather than requiring additional data collection efforts from the team.
Solution Approach 2:
The patent introduces commit history as an intermediary artifact that indirectly reflects productivity. Instead of directly measuring productivity through questionnaires or time tracking, the system uses commit history records as a mediator that objectively captures development activity, thereby avoiding direct burden on development members while maintaining measurement objectivity.
2Loss of information
If retrospective analysis is conducted based on developer subjectivity, then process improvement insights are obtained, but measurement objectivity deteriorates
Solution Approach 1:
The patent replaces the subjective human judgment mechanism with an automated computational analysis mechanism. Instead of relying on developers' subjective retrospective assessments, the system mechanically processes commit history data through automated algorithms to generate objective productivity metrics, thereby substituting human subjectivity with computational objectivity.
Solution Approach 2:
The system establishes a feedback loop where commit history data is continuously collected, analyzed, and converted into objective productivity metrics that can inform process improvements. This automated feedback mechanism replaces subjective retrospective discussions with data-driven insights, maintaining both information quality and measurement objectivity.
Data Source
AI summary
An analyzing device for analyzing a result of a software development team that repeatedly executes a sprint includes an acquisition unit that acquires a commit history from a development repository that stores a product of the software development team, an analysis unit that calculates statistical information by aggregating the commit histories in units of the sprint, and a display unit that displays the statistical information. The analysis unit calculates the Gini coefficient in which a maldistribution of the result of the software development team is considered in the unit of the development cycle.