Container Image Source Code Provenance for Rapid Bug Identification
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Solution Overview
Problem
Container images lack source-code provenance data, making it difficult to track and remedy bugs, as developers cannot determine the source code's location or commit version used to compile the software, leading to excessive time spent on problem-solving and potential introduction of additional errors.
Innovation Solution
A system generates and incorporates source-code provenance data into container images, allowing users to determine the source code's location and commit version, and compares differences between container images to identify bug introduction points, with the ability to generate and apply software patches.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If container images are built from source code without incorporating provenance data, then the container images remain simple and lightweight, but developers cannot track the source code's location or commit version, making bug identification difficult and time-consuming
Solution Approach 1:
The patent embeds source code provenance data (commit hashes, file paths, version information) directly within the container image structure, nesting metadata inside the image layers. This allows the container image to carry its own build history and source code identification information without requiring external tracking systems, enabling rapid bug identification by comparing provenance data across image versions.
Solution Approach 2:
The system automatically captures and records source code provenance information (commit hashes, file paths, version details) at the time of container image generation. By performing this data collection and embedding action during the build process rather than requiring manual tracking afterward, the system eliminates subsequent debugging time while maintaining automated workflow efficiency.
2Productivity
If developers manually assess container images to determine where problems were introduced, then no additional tracking infrastructure is needed, but excessive time is spent on problem-solving and additional errors are often introduced
Solution Approach 1:
The patent creates and stores copies of source code provenance data (commit hashes, file paths, version information) directly within the container image metadata. These embedded copies allow developers to retrieve and compare source code identification information without accessing the original version control system, enabling rapid bug identification through direct image inspection while maintaining simplicity.
Solution Approach 2:
The container image itself serves as an intermediary that carries source code provenance information from the build environment to the runtime environment. By embedding this metadata within the image, the system provides a self-contained mechanism for tracking source code origins without requiring complex external infrastructure or manual assessment processes.
3Reliability
If container images include detailed source code provenance data and comparison capabilities, then bug identification becomes rapid and automated, but the container image structure becomes more complex
Solution Approach 1:
The patent embeds source code provenance data (commit hashes, file paths, version information) directly within the container image structure, nesting metadata inside the image layers. This allows the container image to carry its own build history and source code identification information without requiring external tracking systems, enabling rapid bug identification by comparing provenance data across image versions.
Data Source
AI summary
Bugs in container images can be rapidly identified. For example, a computing device can receive first metadata about a first container image that includes a first version of a piece of software and second metadata about a second container image that includes a second version of the piece of software. The computing device can obtain first source code from a first location indicated in the first metadata and second source code from a second location indicated in the second metadata. The computing device can determine a difference between the first container image and the second container image by comparing the first source code to the second source code. The computing device can generate an output for display indicating the difference between the first container image and the second container image.