Automated IVR Testing: How to Build a Regression Suite That Runs on Every Deploy
Blog post from Coval
Automated Interactive Voice Response (IVR) testing addresses the challenges of manual testing by converting test cases into a regression suite that can run programmatically, ensuring every path is tested with each deployment. Unlike web applications, IVR systems are difficult to test automatically due to their complexity, including multi-modal inputs, such as DTMF and voice, multi-path flows, stateful behavior, and audio/telephony requirements. Automated testing for traditional DTMF IVRs involves placing calls, detecting prompts, sending DTMF tones, and verifying outcomes, while testing conversational AI IVRs requires simulating realistic caller interactions and evaluating outcomes with metrics. Integrating IVR tests into CI/CD pipelines ensures that every code change is validated before merging, with GitHub Actions providing a framework for launching evaluations and reporting results. A comprehensive IVR regression suite should cover critical paths, error handling, transfer and routing, compliance, and edge cases, expanding as new issues are encountered in production. Regular scheduling of tests helps catch degradations due to external factors, maintaining the reliability of IVR systems over time.
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