Unified Data Visualization for Software Development Decision-Making
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Solution Overview
Problem
Software development is complex and influenced by numerous factors, including business needs, user requirements, and market trends, making it challenging to make informed decisions due to the vast amount of data and potential obsolescence of software components during development.
Innovation Solution
A computer-implemented method that collects and transforms various types of data related to software development into data visualizations, selecting relevant data based on user characteristics and intent, and presenting these visualizations in a single visual representation to facilitate decision-making.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If multiple types of data are collected and visualized separately, then comprehensive information is provided, but the complexity of the interface and difficulty of understanding increase
Solution Approach 1:
The patent combines multiple separate data visualizations (commit history, code review status, build status, test results) into a single unified visual representation called a 'graphical commit summary'. This consolidation presents comprehensive development information in one integrated view, eliminating the need for users to navigate multiple separate interfaces while maintaining all essential data elements.
Solution Approach 2:
The graphical commit summary serves multiple functions simultaneously: it displays commit metadata, visualizes code review status, shows build and test results, and provides navigation capabilities. This multi-functional single interface replaces what would traditionally require multiple specialized tools or views, reducing overall system complexity while maintaining comprehensive information display.
2Measurement precision
If detailed data visualizations are provided for each data type, then measurement precision is improved, but the time to process and interpret the data increases
Solution Approach 1:
The system performs preliminary organization and structuring of multiple data types into a pre-integrated graphical summary before presentation to the user. By pre-arranging commit history, reviews, builds, and tests into a coordinated visual layout with established relationships and navigation paths, the system eliminates the time users would otherwise spend manually gathering and correlating this information from separate sources.
Solution Approach 2:
Multiple precise data visualizations are merged into a single graphical commit summary that maintains the precision of individual data representations while presenting them in an integrated format. The summary preserves detailed information about each data type through dedicated visual elements while reducing interpretation time through unified presentation and contextual relationships.
3Reliability
If comprehensive data is collected for software development decision-making, then decision quality is improved, but the risk of data obsolescence during the collection process increases
Solution Approach 1:
The system collects and integrates comprehensive development data (commits, reviews, builds, tests) into a unified graphical summary before the development process significantly advances. By establishing this baseline visual representation early, the system captures the state of the software at a specific point in time, reducing the window during which data could become obsolete and maintaining decision-relevant accuracy.
Data Source
AI summary
A computer-implemented method, in accordance with one embodiment, includes collecting data relating to development of a software product, the collected data including a plurality of different types of data relating to the development of the software product. A portion of the collected data is selected based on a characteristic of an intended user, the portion of the collected data including a plurality of the types of data. The selected portion of the collected data is transformed into data visualizations representing the data, the different types of the data having different data visualizations relative to one another. The data visualizations are output in a single visual representation for display to the intended user.