Natural Language Testing Framework for Software Automation
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Solution Overview
Problem
Conventional software testing frameworks require programming expertise and are costly due to the need for custom programming languages, making it difficult for non-programmers to create and modify tests, especially when software versions or builds change, leading to inefficiencies and high re-write times.
Innovation Solution
A testing framework with a persistent static framework layer and a dynamic custom action layer that allows users to create and modify tests using natural language, reducing the need for programming skills and enabling easy adaptation to software changes without re-compiling code.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional software testing frameworks use custom programming languages, then testing precision and control are improved, but ease of operation deteriorates requiring programming expertise
Solution Approach 1:
The patent introduces an intermediary layer that translates natural language test descriptions into executable test code. This mediator component allows users to write tests in plain English while the system handles the conversion to precise executable instructions, thereby maintaining testing precision without requiring users to learn programming languages.
Solution Approach 2:
The patent replaces the mechanical system of learning and using custom programming languages with a natural language processing system. Instead of requiring users to manually write and compile code, the system uses language translation mechanisms to convert natural language descriptions into executable tests, eliminating the need for programming expertise while maintaining test precision.
2Reliability
If custom programming languages are required for testing, then testing control is improved, but device complexity increases
Solution Approach 1:
The patent extracts the complexity of programming language interpretation from the user's workflow and consolidates it into a dedicated translation component within the testing framework. This separation allows the rest of the system to work with simple natural language inputs while the translation layer handles the complexity of generating precise executable code, thereby maintaining testing control without increasing overall system complexity.
3Measurement precision
If programming expertise is required to create tests, then testing precision is improved, but productivity deteriorates due to re-write times when software versions change
Solution Approach 1:
The patent implements a dynamic testing framework where test specifications are stored as editable natural language descriptions rather than fixed compiled code. When software versions change, users can dynamically update their test descriptions in plain English, and the system automatically recompiles the translated code, eliminating the need to manually rewrite entire test suites and maintaining productivity while preserving testing precision.
4Reliability
If conventional testing frameworks are used, then testing control is improved, but loss of time increases due to re-writing tests for new software instances
Solution Approach 1:
The patent performs preliminary translation of natural language test descriptions into executable code templates that are version-agnostic. When new software instances are released, the pre-translated templates can be quickly adapted by modifying the natural language descriptions rather than rewriting entire test suites, thereby reducing time loss while maintaining testing control through the structured translation process.
Data Source
AI summary
In a method of binding a software item to a plain English name, a user input of a plain English control name is received into a test file. A user interface under test is automatically searched for a control corresponding to the plain English control name. The corresponding control in the software item under test is automatically bound to the plain English control name.