Code Sample Validation in Software Documentation
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Solution Overview
Problem
Creating and maintaining functional code samples in software documentation is challenging due to typographical errors and 'bit rot,' where code samples become stale as dependencies change, making them non-functional.
Innovation Solution
A computer-implemented method and system that receives documentation with code samples, associates them with test modules, and executes these modules to validate the code samples, storing the results, ensuring that only valid code samples are referenced and updated.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If code samples are manually written in word processors, then documentation can be created easily, but the code samples contain typographical errors and become non-functional
Solution Approach 1:
The patent introduces an intermediary system that acts as a bridge between the documentation authoring process and the code execution environment. This system automatically extracts code samples from documentation, validates them against the actual software product, and provides feedback for correction, thereby resolving the conflict between ease of authoring and code functionality.
Solution Approach 2:
The patent implements a feedback mechanism where code samples are automatically tested against the actual software product, and error information is fed back to documentation authors. This closed-loop feedback system enables authors to correct typographical errors and maintain functional code samples without requiring deep programming expertise.
2Reliability
If code samples are copied from coding tools to documentation, then code functionality is initially maintained, but subsequent edits introduce errors
Solution Approach 1:
The patent performs preliminary validation of code samples at the time of documentation creation or update. By automatically testing code samples before they are finalized in the documentation, the system prevents errors from being introduced in the first place, reducing the complexity of subsequent maintenance.
Solution Approach 2:
The system enables code samples to essentially self-validate by automatically testing them against the software product and identifying errors. This self-service capability reduces the manual effort and complexity required to maintain code sample functionality throughout the documentation lifecycle.
3Device complexity
If code samples remain static in documentation, then documentation structure is simple, but code samples become stale as dependencies change
Solution Approach 1:
The patent transforms static code samples into dynamic, living entities that are automatically validated against the current state of the software product. The system continuously or periodically tests code samples to detect changes in software dependencies, ensuring code samples remain current without requiring manual updates to the documentation structure.
Solution Approach 2:
The patent implements continuous validation of code samples against the software product. Rather than performing one-time checks, the system maintains ongoing verification to detect when code samples become stale due to dependency changes, ensuring continuous reliability without complicating the documentation structure.
4Reliability
If manual testing of code samples is performed, then code functionality can be verified, but the process is time-consuming and error-prone
Solution Approach 1:
The patent replaces manual mechanical testing processes with automated computational validation. The system automatically extracts code samples, executes them against the software product, and validates functionality without human intervention, dramatically reducing both time and human error while maintaining high accuracy in code validation.
Solution Approach 2:
The system enables code samples to be automatically tested and validated without requiring manual intervention. The automated testing framework performs validation independently, reducing the time investment required while maintaining accurate verification of code functionality.
Data Source
AI summary
Documentation having code samples is managed. Documentation describing programming code for a software product is received. The documentation references a code sample having an associated test module for determining whether the code sample is valid. The code sample is tested by executing the associated test module to produce a test result indicating whether the code sample is valid. The documentation, code sample, and test result are stored. The documentation, code sample, and test result may be provided to a client adapted to display the code sample and test result to a user of the client. Invalid code samples in the documentation may be identified using the test modules and the invalid code samples may be replaced to make the code samples valid.