Natural Language Testing Framework for Software Error Data Capture

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Solution Overview

Problem

Conventional software testing frameworks require programming expertise and specific languages, making them time-consuming and costly, especially when adapting to new software versions or instances, as they often necessitate extensive recompilation and custom programming for fixture layers.

Innovation Solution

A testing framework with a persistent static 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 by separating static and dynamic components.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If conventional programming languages are used for testing, then test precision and reliability are improved, but the complexity of operation and time required increase significantly

Engineering Contradiction:

Improvetest reliabilityVSAvoidease of test creation

Core Design Contradiction:

ReliabilityVSEase of operation

Solution Approach 1:

The patent introduces a natural language processing layer as an intermediary between the user and the testing framework. This mediator translates natural language test descriptions into executable test code, eliminating the need for users to directly program while maintaining test reliability through automated interpretation and execution.

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent replaces the mechanical process of manual programming with an automated natural language processing system. Instead of requiring users to write, compile, and debug code, the system automatically interprets natural language instructions and generates executable test routines, significantly reducing operational complexity.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Measurement precision

If programming expertise is required for testing, then test precision is improved, but the time consumption and cost increase

Engineering Contradiction:

Improvetest precisionVSAvoidtime for test creation

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent enables the testing system to serve itself by automatically generating test code from natural language descriptions. The natural language processing component self-interprets user intentions, generates appropriate test routines, and handles execution without requiring external programming expertise, thereby reducing time loss while maintaining precision.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent changes the fundamental parameter of test creation from requiring programming knowledge to requiring only natural language communication. This parameter change transforms the creation process from a technical skill-based activity to a language-based activity, significantly reducing the time and expertise required while maintaining test quality.

Inventive Principle:

Principle #35Parameter changes

3Adaptability or versatility

If fixture layers are customized for each software instance, then adaptability is improved, but device complexity and time required increase

Engineering Contradiction:

Improveadaptability to software versionsVSAvoidcomplexity of test framework

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent introduces dynamic adaptability through natural language processing that can interpret software-specific terminology and behavior patterns. The system dynamically adjusts test generation based on the software instance being tested, allowing the same framework to adapt to different software versions without increasing structural complexity.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The patent creates a universal testing framework that can handle multiple software instances through natural language processing. The single framework serves multiple purposes by interpreting different software-specific natural language descriptions, eliminating the need for separate fixture layers for each software version while maintaining full adaptability.

Inventive Principle:

Principle #6Universality (Multi-functionality)

4Ease of operation

If natural language is used for testing, then ease of operation is improved, but measurement precision and control over test execution may be compromised

Engineering Contradiction:

Improveease of test creationVSAvoidprecision of test execution

Core Design Contradiction:

Ease of operationVSMeasurement precision

Solution Approach 1:

The patent implements feedback mechanisms where the natural language processing system continuously refines test generation based on execution context and results. This feedback loop ensures that the simplified natural language interface maintains precision by adjusting test parameters and execution details based on actual software behavior and test outcomes.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS8839201B2Capturing test data associated with error conditions in software item testing

Publication Date: 2014.09.16 VMWARE INC

AI summary

In a method of testing a software item, an automated test of a software item is conducted. In response to occurrence of an error condition during the test, test data associated with the error condition is captured. A portion of the captured test data is forwarded to a designated electronic notification location.