Search Results for "test coverage"
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Showing 11 open source projects for "test coverage"
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Qodo Cover
AI tool that generates tests to improve code coverage quickly
...It follows an iterative workflow where generated tests are executed, validated, and refined to ensure they contribute meaningful coverage improvements. Internally, Qodo Cover uses a modular architecture that includes components for prompt generation, AI interaction, coverage analysis, and test validation. It supports scanning entire repositories to automatically detect test files, gather relevant context, and extend test suites accordingly. -
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CodiumAI Cover-Agent
CodiumAI Cover-Agent: An AI-Powered Tool for Automated Test Generation
CodiumAI Cover Agent aims to help efficiently increasing code coverage, by automatically generating qualified tests to enhance existing test suites. -
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TONL
TONL (Token-Optimized Notation Language)
...The platform comes with a complete command-line interface that supports interactive dashboards and cross-platform usage in browsers and server environments, and its high test coverage gives developers confidence in stability. -
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ASSERT
Requirement-driven evaluation harness for AI agents and LLM
ASSERT is a requirement-driven evaluation harness for AI agents and LLM applications. It turns natural-language specifications, policies, product requirements, and launch criteria into structured tests that can be reviewed, executed, scored, and improved. The pipeline derives behavior categories, generates single-turn and multi-turn test cases, runs them against a target system, and uses an LLM judge to score conversations against the stated policies. It can evaluate hosted models, custom... -
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5
Codex Autoresearch
A codex plugin for running optimization loops inside a codebase
...The system operates in a loop where the agent modifies code, evaluates results against measurable metrics, and either keeps or discards changes based on performance. It generalizes the concept of autoresearch beyond machine learning, allowing optimization of test coverage, latency, lint errors, and overall code quality. Developers define a goal and verification command, and the agent continuously runs experiments to reach the desired outcome. The framework supports multiple operational modes, including debugging, planning, security auditing, and release validation. It can run unattended for extended periods, producing logs of experiments and improvements. ... -
6
dlib
Toolkit for making machine learning and data analysis applications
...It is used in both industry and academia in a wide range of domains including robotics, embedded devices, mobile phones, and large high performance computing environments. Dlib's open source licensing allows you to use it in any application, free of charge. Good unit test coverage, the ratio of unit test lines of code to library lines of code is about 1 to 4. The library is tested regularly on MS Windows, Linux, and Mac OS X systems. No other packages are required to use the library, only APIs that are provided by an out of the box OS are needed. There is no installation or configure step needed before you can use the library. ... -
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promptmap2
A security scanner for custom LLM applications
...Its scanning workflow uses a dual-LLM architecture in which one model acts as the target being tested and another acts as a controller that evaluates whether an attack succeeded. The repository emphasizes broad coverage, including test rules for prompt stealing, jailbreaks, harmful content generation, hate-related outputs, social bias, and distraction attacks. It also supports multiple providers such as OpenAI, Anthropic, Google, xAI, and open-source models through Ollama, making it flexible for both commercial and local deployments. -
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ZeroStep
Supercharge your Playwright tests with AI
ZeroStep is a tool that enhances Playwright tests with AI capabilities, aiming to improve the efficiency and effectiveness of end-to-end testing. -
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HttpRunner
Testing framework that began with API and performance testing
HttpRunner is an open-source testing framework that began with API and performance testing and has evolved into a general, extensible test platform. The current major version is implemented in Go, with the legacy Python edition split to a separate repository; this shift emphasizes a single, fast, cross-platform runtime for modern pipelines. It provides declarative test cases, data-driven parametrization, and plugin mechanisms so teams can compose reusable steps and validations at scale. ... -
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10
Reliable Metrics for Generative Models
Code base for the precision, recall, density, and coverage metrics
Reliable Fidelity and Diversity Metrics for Generative Models (ICML 2020). Devising indicative evaluation metrics for the image generation task remains an open problem. The most widely used metric for measuring the similarity between real and generated images has been the Fréchet Inception Distance (FID) score. Because it does not differentiate the fidelity and diversity aspects of the generated images, recent papers have introduced variants of precision and recall metrics to diagnose those... -
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lastest
AI-supported visual verification and tests you can actually trust.
Lastest.cloud is a free, open-source verification of development, self-hosted visual regression and end-to-end testing platform for web applications. An AI agent records you clicking through your running app and generates Playwright tests with multi-selector fallback. Replays are deterministic and token-free, so your CI/CD bill doesn't scale with your test suite. Lastest ships three diff engines side-by-side — pixel (pixelmatch), structural (SSIM), and perceptual (Butteraugli) — so...
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