Search Results for "source testing unit testing"
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Showing 290 open source projects for "source testing unit testing"
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Fastbot-Android Open Source Handbook
Testing tool for modeling GUI transitions
Fastbot_Android (Fastbot 2.0) is a model-based automated testing tool by ByteDance designed to discover stability or usability issues in Android apps by modeling GUI transitions rather than relying purely on random interactions. It blends machine learning and reinforcement-learning approaches to build a transition graph of UI states and use that model to intelligently explore possible user interactions — aiming to replicate more human-like usage patterns and uncover hidden bugs, crashes, or... -
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Expect
Let agents test your code in a real browser
...The design suggests a focus on productivity, reducing cognitive load when writing and reviewing tests or validation scripts. It is likely adaptable across multiple contexts, including unit testing, integration testing, and runtime assertions. By abstracting repetitive validation logic, expect helps developers focus on behavior rather than implementation details. Overall, it serves as a lightweight but powerful tool for improving software reliability and clarity in testing workflows. -
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PentestGPT
Automated Penetration Testing Agentic Framework Powered by LLMs
PentestGPT is an AI-powered autonomous penetration testing agent designed to perform intelligent, end-to-end security assessments using large language models. Published at USENIX Security 2024, it combines advanced reasoning with an agentic workflow to automate tasks traditionally handled by human pentesters. The platform supports multiple penetration testing categories, including web security, cryptography, reversing, forensics, privilege escalation, and binary exploitation. PentestGPT runs... -
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LangCheck
Simple, Pythonic building blocks to evaluate LLM applications
Simple, Pythonic building blocks to evaluate LLM applications. -
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Giskard
Collaborative & Open-Source Quality Assurance for all AI models
The testing framework dedicated to ML models, from tabular to LLMs. Giskard is an open-source testing framework dedicated to ML models, from tabular models to LLMs. Testing Machine Learning applications can be tedious. Since ML models depend on data, testing scenarios depend on the domain specificities and are often infinite. At Giskard, we believe that Machine Learning needs its own testing framework. -
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PentAGI
Perform penetration testing tasks
PentAGI is a fully autonomous AI agent system designed to perform complex penetration testing tasks by orchestrating multiple intelligent components into a coordinated offensive security workflow. The platform aims to automate significant portions of the penetration testing lifecycle, including reconnaissance, vulnerability discovery, and exploitation planning, reducing the amount of manual effort required from security professionals. It leverages agent-based architecture and AI reasoning to... -
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OctoMind MCP
An MCP server for octomind tools, resources and prompts
The Octomind MCP Server is designed to integrate Octomind's end-to-end testing tools and resources into local development environments. It enables AI-powered interfaces to create, execute, and manage e2e tests, enhancing the testing workflow. -
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DeepEval is a simple-to-use, open-source LLM evaluation framework, for evaluating and testing large-language model systems. It is similar to Pytest but specialized for unit testing LLM outputs. DeepEval incorporates the latest research to evaluate LLM outputs based on metrics such as G-Eval, hallucination, answer relevancy, RAGAS, etc., which uses LLMs and various other NLP models that run locally on your machine for evaluation.
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iOS Simulator MCP
MCP server for interacting with the iOS simulator
The iOS Simulator MCP Server is a Model Context Protocol implementation that allows interaction with iOS simulators. It enables users to retrieve information about simulators, control UI interactions, and inspect UI elements, facilitating automated testing and development workflows. -
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MCPJam
Postman for MCPs - A tool for testing and debugging MCPs
Inspector by MCPJam is a visual developer tool—akin to Postman—for testing and debugging MCP servers, with capabilities to simulate and trace tool execution via various transports and LLM integrations. -
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Apache Hamilton
Helps data scientists define testable self-documenting dataflows
Apache Hamilton is an open-source Python framework designed to simplify the creation and management of dataflows used in analytics, machine learning pipelines, and data engineering workflows. The framework enables developers to define data transformations as simple Python functions, where each function represents a node in a dataflow graph and its parameters define dependencies on other nodes. Hamilton automatically analyzes these functions and constructs a directed acyclic graph... -
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Strix
Open-source AI hackers to find and fix your app’s vulnerabilities
Strix is an open source agent-driven security platform that uses autonomous AI agents to identify, investigate, and validate vulnerabilities in software applications. The system is designed to mimic the behavior of real attackers by executing dynamic testing and verifying findings through proof-of-concept exploitation. Unlike traditional vulnerability scanners that rely heavily on static analysis, Strix agents actively run code, probe systems, and attempt exploitation to confirm whether vulnerabilities are genuinely exploitable. ... -
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CodeBurn
See where your AI coding tokens go
CodeBurn is a security-focused tool designed to evaluate and stress-test codebases using adversarial techniques, often leveraging AI to identify vulnerabilities and weaknesses. It simulates attack scenarios against code to uncover potential security risks, helping developers proactively identify issues before they reach production. The system is designed to integrate into development workflows, allowing continuous testing as code evolves. It emphasizes automation, enabling large-scale... -
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PentestAgent
AI agent framework for black-box security testing
PentestAgent is an open-source autonomous security testing platform designed to help organizations identify vulnerabilities and assess security posture by simulating real-world attack scenarios without manual intervention. It brings a modular and automated approach to penetration testing by orchestrating a suite of tools and scripts that can emulate common exploitation techniques, reconnaissance workflows, and post-exploitation activities across targets. -
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Auto Claude
Autonomous multi-session AI coding
Auto-Claude is an autonomous, multi-agent coding framework that organizes software work into a structured workflow where agents plan, build, and validate code with minimal manual micromanagement. Instead of relying on a single chat thread to do everything, it uses coordinated agents and a task-driven approach so multiple steps—like investigation, implementation, and testing—can be executed systematically. The project aims to make “agentic software engineering” feel like running a small... -
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FuzzyAI Fuzzer
A powerful tool for automated LLM fuzzing
...The framework can be integrated into development pipelines to continuously test AI APIs and detect weaknesses before deployment. FuzzyAI provides testing tools, datasets, and evaluation workflows that help researchers measure how well models resist harmful instructions or attempts to bypass safety mechanisms. -
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Kheish
Kheish: A multi-role LLM agent for tasks like code auditing
Kheish is a framework designed for cybersecurity professionals to automate penetration testing tasks, providing tools to streamline security assessments. -
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Ollama Grid Search
A multi-platform desktop application to evaluate and compare LLM
Ollama Grid Search is a desktop application designed to automate the evaluation and comparison of large language models, prompts, and inference parameters in a structured and repeatable way. Instead of manually testing combinations, the tool performs grid search experiments by iterating across different models, prompt variations, and parameter configurations, allowing users to quickly identify optimal setups for specific tasks. It provides a visual interface where experiment results can be... -
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Genkit
An open source framework for building AI-powered apps
Genkit is an open-source framework developed by Firebase for building AI-powered applications using familiar code-centric patterns. It simplifies the development, integration, and testing of AI features, providing observability and evaluation tools, and supports various models and platforms for versatile AI application development. -
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GoogleTest
Google Testing and Mocking Framework
GoogleTest is Google's C++ mocking and test framework. It's used by many internal projects at Google, as well as a number of notable projects such as The Chromium projects, the OpenCV computer vision library, and the LLVM compiler. This GoogleTest project is actually a union of what used to be two separate projects: the old GoogleTest and GoogleMock, an extension of GoogleTest for writing and using C++ mock classes. Since they were so closely related, they were merged to create an even... -
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PySpur
Visual tool for building, testing, and deploying AI agent workflows
PySpur is a visual development environment designed to help AI engineers build, test, and iterate on agent-based workflows more efficiently. It provides a structured playground where users can define test cases, construct agents either through Python code or a graphical interface, and continuously refine their behavior. It addresses common challenges in AI agent development such as prompt tuning difficulties and lack of visibility into workflow execution. By offering a visual representation... -
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Rogue
AI Agent Evaluator & Red Team Platform
...The system allows developers to define specific scenarios, expected outcomes, and business rules so that the framework can verify whether an agent behaves according to required policies. During testing, Rogue records conversations and produces detailed reports that explain whether the agent passed or failed each scenario. These reports include reasoning and evidence, helping developers understand why a particular failure occurred. -
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kMCP
Kubernetes Controller for building, testing and deploying MCP servers
KMCP is a companion toolchain for building, testing, and deploying MCP servers with a workflow that spans local development through Kubernetes production deployments. It includes a CLI for day-to-day development tasks like scaffolding new MCP projects, managing tools, building container images, and running an MCP server locally for validation. For cluster operations, it includes a Kubernetes controller that manages MCP server lifecycles using a dedicated Custom Resource Definition (CRD),... -
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adversarial-spec
A Claude Code plugin that iteratively refines product specifications
adversarial-spec is a framework focused on designing and testing systems using adversarial thinking to uncover weaknesses and improve robustness. It encourages developers to define specifications that anticipate failure modes, edge cases, and malicious inputs before implementing solutions. The project emphasizes proactive design, ensuring that systems are built with resilience in mind from the beginning. It provides structured approaches for identifying vulnerabilities and stress-testing... -
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Claude Code Haha
Claude Code leaked source - locally runnable version
Claude Code Haha is an experimental and often humorous adaptation of Claude-style coding agents, designed to explore and demonstrate how agentic coding systems behave under different configurations and prompts. While it retains the core functionality of analyzing and modifying codebases, the project introduces variations that highlight both the strengths and quirks of autonomous coding assistants. It serves as a sandbox for testing how agents interpret instructions, manage context, and...
