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QUALITY: Quick Unified Automation Leveraging Intelligent Test Yield

Soham Patel et al.

Software Impacts2026https://doi.org/10.1016/j.simpa.2026.100823article
AJG 1
Weight
0.50

What the paper says

This paper introduces an innovative no-code methodology called QUALITY for automated test generation utilizing Excel templates for unit and integration testing. The suggested method allows non-technical stakeholders to engage in test creation while upholding software quality standards. Utilizing familiar Excel interface enables enterprises to lower the entry barriers for test automation and enhance test coverage among development teams. This technique connects business requirements with technical testing, thereby expediting software delivery while ensuring quality assurance. • No-Code Test Generation: QUALITY transforms Excel-based templates into operational API unit and integration tests without necessitating programming proficiency. • Multi-Protocol Support: QUALITY provides native support for REST, SOAP, and GraphQL, facilitating cohesive testing across many API environments. • Template-Driven Maintainability: Test cases can be modified or expanded effortlessly by adjusting spreadsheet rows, hence minimizing maintenance burdens. • Integration and Reporting: QUALITY facilitates dependency-aware execution, CI/CD integration (maven supported), and produces comprehensive HTML, CSV, Console Logs and Extent reports for actionable insights.

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https://doi.org/https://doi.org/10.1016/j.simpa.2026.100823

Or copy a formatted citation

@article{soham2026,
  title        = {{QUALITY: Quick Unified Automation Leveraging Intelligent Test Yield}},
  author       = {Soham Patel et al.},
  journal      = {Software Impacts},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1016/j.simpa.2026.100823},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.