GenAI Security Testing From Test Logs to New Feature Code
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Software testing requires significant manual effort from developers, leading to inefficiencies and increased chances of human error, especially in the test design and execution phases.
Innovation Solution
Utilizing generative artificial intelligence (GenAI) models to automate the generation of software tests, automation scripts, and source code, reducing the need for manual intervention and improving test design efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual testing is used, then test design can be customized and understood by developers, but testing time increases and human errors occur
Solution Approach 1:
The system enables self-service testing by automatically generating test cases from natural language requirements using GenAI models. The testing system serves itself by converting requirement descriptions into executable test cases without manual intervention, thereby reducing testing time while maintaining reliability through automated consistency.
Solution Approach 2:
The patent replaces the mechanical manual process of test design with an automated GenAI-based system. The GenAI model processes natural language requirements and automatically generates test cases, substituting the manual mechanical process with an intelligent automated system that reduces time consumption while improving consistency and reliability.
2Adaptability or versatility
If manual test design is performed, then test cases can be tailored to specific requirements, but developer effort and complexity increase
Solution Approach 1:
The GenAI model acts as an intermediary between natural language requirements and automated test case generation. It translates human-readable requirement descriptions into structured test cases, maintaining adaptability and customization while reducing process complexity by eliminating manual test design steps.
Solution Approach 2:
The system performs self-service by automatically generating customized test cases from requirement descriptions without human intervention. The GenAI model understands the specific requirements and autonomously creates tailored test cases, reducing developer effort while maintaining high adaptability to different testing scenarios.
3Reliability
If more testing is performed to ensure quality, then software quality improves, but testing time and resource consumption increase
Solution Approach 1:
The GenAI-based testing system enables continuous automated test case generation and execution. The system continuously processes requirement descriptions and generates test cases without interruption, maintaining high software quality through comprehensive testing while improving productivity through uninterrupted automated operation.
Solution Approach 2:
The patent replaces manual testing mechanics with automated GenAI-based testing. The intelligent system continuously generates and executes test cases automatically, ensuring high software quality through thorough testing while dramatically improving testing efficiency by eliminating manual repetitive tasks.
Data Source
AI summary
An example operation may include one or more of executing tests on a software application via a test environment of a test platform and logging results of the tests in a log file, identifying a new feature to be added to the software application based on execution of a machine learning model on logged results of the tests stored in the log file, generating source code for the new feature to be added to the software application based on execution of a generative artificial intelligence (GenAI) model on the new feature and a repository of source code, and displaying the generated source code via a user interface of the software application.