Learning-Based SIP Call Flow Testing for Comprehensive Coverage

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Manual testing of network equipment is time-consuming, costly, and prone to gaps in coverage, leading to slow upgrades and increased R&D resource expenditure, with customers reluctant to adopt new releases due to high failure rates and security vulnerabilities.

Innovation Solution

Implement a learning-based automated testing system that generates test cases from continuous in-production sampling of real network traffic, simulates production environments, and automates the configuration and execution of tests, reducing human intervention and resource costs.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If manual testing is used to test network equipment new releases, then testing can be performed with simple setup, but testing time and cost increase significantly and coverage gaps occur

Engineering Contradiction:

Improvetesting coverageVSAvoidtesting time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The patent creates virtual copies of production network environments, devices, and call flows to enable automated testing. Test systems replicate production configurations and traffic patterns in virtualized test beds, allowing comprehensive testing without manual intervention and reducing both time and coverage gaps.

Inventive Principle:

Principle #26Copying

Solution Approach 2:

The testing system automatically generates test cases, executes tests, and analyzes results without requiring manual human operation. The system self-manages the entire testing workflow including automated test case generation from production data, execution orchestration, and result evaluation, eliminating the need for manual testing labor.

Inventive Principle:

Principle #25Self-service

2Reliability

If manual testing is used by R&D staff, then testing can be performed with simple procedures, but R&D resources are significantly consumed limiting new feature development

Engineering Contradiction:

Improvetesting thoroughnessVSAvoidR&D resource allocation

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent replaces manual mechanical testing operations with automated electronic systems. Software-based test execution engines, virtualization platforms, and automated analysis tools substitute for human R&D staff performing manual testing, maintaining thoroughness while freeing R&D resources for new feature development.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Measurement precision

If lab configuration is updated to match production changes, then testing accuracy improves, but configuration time and error risk increase

Engineering Contradiction:

Improvetesting accuracyVSAvoidconfiguration ease

Core Design Contradiction:

Measurement precisionVSEase of manufacture

Solution Approach 1:

The system proactively captures production configuration changes and automatically propagates them to test environments before testing is needed. Configuration synchronization occurs in advance through automated data collection and environment provisioning, ensuring test accuracy without requiring manual configuration updates at the time of testing.

Inventive Principle:

Principle #10Preliminary action

4Productivity

If multiple call flows are collapsed into single test cases to reduce overhead, then testing efficiency improves, but true coverage is compromised

Engineering Contradiction:

Improvetesting efficiencyVSAvoidcall flow coverage

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The patent segments call flows into atomic test cases based on unique characteristics and failure modes. Rather than collapsing multiple call flows into single tests, the system identifies distinct testable units and creates separate automated test cases for each, maintaining comprehensive coverage while enabling efficient automated execution through structured organization.

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS12388704B2Learning-based automated call flow testing

Publication Date: 2025.08.12 RIBBON COMMUNICATIONS OPERATING CO INC

AI summary

The present invention relates to methods, systems, and apparatus for learning-based automated call flow testing. An exemplary method of testing a Session Initiation Protocol (SIP) call processing entity includes the steps of generating a first test case based on a first reference call flow record for a first SIP call or a trace record for the first SIP call; executing the first test case which includes sending one or more SIP messages to the first SIP call processing entity; generating a first test case call flow record for a first SIP test call corresponding to the first test case; and determining whether or not the first SIP call processing entity failed the first test case based on a comparison of the first test case call flow record and the first reference call flow record.