Automated Code Generation from Requirements Context

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Solution Overview

Problem

Current software development techniques are time-intensive, inefficient, and prone to errors due to a lack of automation in understanding software requirements and making corresponding code changes.

Innovation Solution

An instinctive and intelligent cipher compilation and implementation mechanism in a continuous integration and delivery environment, utilizing a computing platform to extract context data from requirements documents, identify and modify code, generate updated code, deploy, test, and report variances, with options for regeneration based on predetermined thresholds.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If manual software development techniques are used, then developers can write application code, but the process is time-intensive and inefficient

Engineering Contradiction:

Improvesoftware development efficiencyVSAvoidimplementation time

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The system enables self-service by allowing the computing platform to automatically extract context from requirements documents, identify necessary code modifications, generate updated code, and deploy changes without continuous manual intervention. The platform serves itself by autonomously completing the software development workflow from requirements to deployment.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system performs preliminary action by pre-processing requirements documents to extract context data before code modification begins. The computing platform proactively identifies code changes needed based on extracted context, preparing the modification plan before actual code generation occurs, thus streamlining the overall process.

Inventive Principle:

Principle #10Preliminary action

2Reliability

If manual code modification processes are used, then code can be updated, but the process is prone to errors

Engineering Contradiction:

Improvecode accuracyVSAvoidmanual intervention complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The system replaces manual mechanical processes with automated computing operations. The computing platform uses algorithmic processes to extract context, identify modifications, and generate code, substituting human manual intervention with automated mechanical-like operations that are more consistent and error-resistant.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system implements feedback by comparing the generated code against the extracted context from requirements documents. The computing platform validates that the modified code aligns with the original requirements, creating a feedback loop that ensures accuracy and identifies discrepancies for correction.

Inventive Principle:

Principle #23Feedback

3Productivity

If automated code generation is implemented, then implementation time is reduced, but variance between code and requirements may increase

Engineering Contradiction:

Improvedevelopment speedVSAvoidcode-requirements alignment

Core Design Contradiction:

ProductivityVSManufacturing precision

Solution Approach 1:

The system uses feedback to continuously monitor and compare generated code against the original requirements context. The computing platform validates each generated modification against the extracted context, ensuring that automation does not compromise alignment with requirements. Discrepancies are detected and can be corrected through iterative refinement.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system applies partial action by generating only the specific code modifications necessary to fulfill requirements, rather than complete rewrites. This targeted approach maintains precision by focusing changes only where needed, reducing the risk of introducing unnecessary variances while still achieving significant automation benefits.

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS11822903B2Instinctive cipher compilation and implementation

Publication Date: 2023.11.21 BANK OF AMERICA CORP

AI summary

Aspects of the disclosure relate to instinctive cipher compilation and implementation in a continuous integration and delivery environment. In some embodiments, a computing platform may receive, via the communication interface, a requirements document for an application. The computing platform may extract context data from the requirements document. The computing platform may scan a repository of code to identify code to be modified based on the context data. The computing platform may identify modifications to the code based on the context data and generate updated code based on the identified modifications. The computing platform may deploy and test the updated code in a test environment. The computing platform may determine a variance between the updated code and the requirements document and generate a variance report. In some embodiments, the computing platform may compare the variance to a predetermined threshold, and accept or redeploy the updated code based on the comparison.