Streamlining User Interface Quality in Gunshot Alert Systems
Engagement Highlights
- Designed and implemented a scalable Web UI automation framework using Playwright and TypeScript.
- Enhanced the reliability and stability of test execution through structured and maintainable test cases.
- Streamlined regression testing by removing redundancies and optimizing test coverage.
- Strengthened the QA process by aligning automation practices with project quality goals.
Company Introduction
Shooter Detection Systems (SDS) is a leader in gunshot detection technology, providing real-time alerts to enhance safety and security. The Guardian Indoor Active Shooter Detection System incorporates the world’s finest acoustic gunshot identification software and combines it with infrared gunfire flash detection to produce the highest performing, fully automatic, and most accurate gunshot detection technology available today. With millions of hours of use, The Guardian Indoor Active Shooter Detection System has delivered a fantastic detection rate, without a single false alert, and a perfect operational record.
Challenges
- Lengthy Regression Cycles: Manual testing required ~8 days for a complete regression run.
- Unstable Coverage: Existing test cases were flaky and unstructured, leading to inconsistent outcomes.
- Limited Test Readiness: QA efforts were mostly manual, resulting in slower delivery and reduced confidence.
- DevOps Misalignment: Test execution was not compatible with CI/CD pipelines, delaying feedback and impacting time-to-market.
Solutions
- Developed a modern test automation framework using Playwright with TypeScript tailored to SDS Web UI.
- Consolidated and optimized test cases, reducing redundant and flaky tests while maintaining robust coverage.
- Validated across both MongoDB and MSSQL-backed deployments to ensure consistency.
Business Impact
- ~118 hours saved per month by reducing regression cycle time from 8 days (64 hours) to 5 hours (~97% faster).
- 82% optimization of test coverage achieved by consolidating 578 flaky/unstructured test cases into 104 reliable automated scenarios.
- Improved release confidence with stable, reliable, and repeatable test execution across MongoDB & MSSQL-backed deployments.
- Accelerated time-to-market with faster regression cycles and earlier defect detection.
- Increased productivity and skill uplift as the team transitioned from manual-intensive efforts to structured automation practices.
- Established a scalable foundation for extending automation into performance and security testing.
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