Best AI tools for< Quality Assurance Engineers >

Bench is an AI tool designed to automate hardware documentation for Hardware Engineers. It helps users document less and create more by utilizing AI for documentation writing, management, and discoverability. The tool offers features such as adapting to specific use cases, AI documentation writing, single source of truth, data-rich asset pages, highlighting compliance gaps, automated reports, and physical asset logging. Bench is advantageous for increasing productivity, improving documentation accuracy, streamlining workflows, enhancing compliance, and enabling seamless integrations. However, it may have limitations in customization options, initial learning curve, and potential dependency on AI accuracy. The tool is suitable for Hardware Engineers, Technical Writers, Documentation Specialists, Compliance Officers, and Quality Assurance Engineers. Users can find Bench using keywords like AI documentation, hardware documentation automation, AI writing tool, documentation management tool, and asset logging AI. Tasks users can perform with Bench include automate documentation, manage assets, write AI documentation, generate reports, and log physical assets.

The website provides resources for learning end-to-end testing using the Playwright automation framework. It includes a blog with in-depth subjects about end-to-end testing, a feature to ask AI ChatGPT Playwright questions, a toolbox for QA engineers, handpicked QA and automation job opportunities, answered questions about Playwright, an archive of Discord forum posts, tutorials, conference talks, release videos, a browser extension for generating Playwright locators, definitions of common testing terms, and a shortcut to access all tools.

Trag is an AI-powered tool designed to review pull requests in minutes, empowering engineering teams to save time and focus on building products. With Trag, users can create custom patterns for code review, ensuring best practices are followed and bugs are caught early. The tool offers features like autofix with AI, monitoring progress, connecting multiple repositories, pull request review, analytics, and team workspaces. Trag stands out from traditional linters by providing complex code understanding, semantic code analysis, predictive bug detection, and refactoring suggestions. It aims to streamline code reviews and help teams ship faster with AI-powered reviews.

Coherent Solutions is a custom software development and engineering company that offers a range of services including digital product engineering, artificial intelligence, data and analytics, mobile development, DevOps and cloud, quality assurance, Salesforce, and product design and UX. They work collaboratively and transparently with clients to deliver successful projects. The company values set the standard for all decisions, and they have a strong focus on understanding and meeting the business needs of their clients. Coherent Solutions has a strong track record of success in various industries and is known for empowering business success through global expertise and industry-specific product engineering consulting services.

Weam is an AI adoption platform designed for digital agencies to supercharge their operations with collaborative AI. It offers a comprehensive suite of tools for simplifying AI implementation, including project management, resource allocation, training modules, and ongoing support to ensure successful AI integration. Weam enables teams to interact and collaborate over their preferred LLMs, facilitating scalability, time-saving, and widespread AI adoption across the organization.

testRigor is an AI-based test automation tool that allows users to create and execute test cases using plain English instructions. It leverages generative AI in software testing to automate test creation and maintenance, offering features such as no code/codeless testing, web, mobile, and desktop testing, Salesforce automation, and accessibility testing. With testRigor, users can achieve test coverage faster and with minimal maintenance, enabling organizations to reallocate QA engineers to build API tests and increase test coverage significantly. The tool is designed to simplify test automation, reduce QA headaches, and improve productivity by streamlining the testing process.

Tusk is an AI-powered tool designed to generate unit and integration tests with codebase context to catch edge cases that engineers might miss. It helps increase feature coverage, suggests test cases based on codebase and documentation, and integrates seamlessly into GitHub and CI/CD pipelines. Tusk offers a user-centric interface design, personalization features, integration with third-party APIs, and scalable architecture for high performance. It aims to build a testing culture that goes beyond mere test coverage, providing targeted suggestions to prevent bugs before deployment.

AgentQL is an AI-powered tool for painless data extraction and web automation. It eliminates the need for fragile XPath or DOM selectors by using semantic selectors and natural language descriptions to find web elements reliably. With controlled output and deterministic behavior, AgentQL allows users to shape data exactly as needed. The tool offers features such as extracting data, filling forms automatically, and streamlining testing processes. It is designed to be user-friendly and efficient for developers and data engineers.

Jam is a bug-tracking tool that helps developers reproduce and debug issues quickly and easily. It automatically captures all the information engineers need to debug, including device and browser information, console logs, network logs, repro steps, and backend tracing. Jam also integrates with popular tools like GitHub, Jira, Linear, Slack, ClickUp, Asana, Sentry, Figma, Datadog, Gitlab, Notion, and Airtable. With Jam, developers can save time and effort by eliminating the need to write repro steps and manually collect information. Jam is used by over 90,000 developers and has received over 150 positive reviews.

Tempo Labs is an AI-powered platform that enables designers and developers to collaborate efficiently by providing a single source of truth. With features like generating functional React apps, designing effortlessly with a drag-and-drop editor, and building and maintaining design systems, Tempo Labs empowers users to work 10x faster. The platform supports any React codebase, allows code editing locally in VSCode, and offers a variety of components and templates for quick start. Tempo Labs offers different pricing plans, including a free tier and a premium Agent+ plan with human engineers and designers for quality assurance.

MAIHEM is an AI-powered quality assurance platform that helps businesses test and improve the performance and safety of their AI applications. It automates the testing process, generates realistic test cases, and provides comprehensive analytics to help businesses identify and fix potential issues. MAIHEM is used by a variety of businesses, including those in the customer support, healthcare, education, and sales industries.

Pixeebot is an automated product security engineer that helps developers fix vulnerabilities, harden code, squash bugs, and improve code quality. It integrates with your existing workflow and can be used locally via CLI or through the GitHub app. Pixeebot is powered by the open source Codemodder framework, which allows you to build your own custom codemods.

Codiga is a static code analysis tool that helps developers write clean, safe, and secure code. It works in real-time in your IDE and CI/CD pipelines, and it can be customized to meet your specific needs. Codiga supports a wide range of languages and frameworks, and it integrates with popular tools like GitHub, GitLab, and Bitbucket.

GitStart is an AI-powered platform that offers Elastic Engineering Capacity by assigning tickets and delivering high-quality production code. It leverages AI agents and a global developer community to increase engineering capacity without hiring more staff. GitStart is supported by top tech leaders and provides solutions for bugs, tech debt, frontend and backend development. The platform aims to empower developers, create economic opportunities, and grow the world's future software talent.

Korbit is an AI-powered code review tool that helps developers write better code, faster. It integrates directly into your GitHub PR workflow and provides instant feedback on your code, identifying issues and providing actionable recommendations. Korbit also provides valuable insights into code quality, project status, and developer performance, helping you to boost your productivity and elevate your code.

QA.tech is an advanced end-to-end testing application designed for B2B SaaS companies. It offers AI-powered testing solutions to help businesses ship faster, cut costs, and improve testing efficiency. The application features an AI agent named Jarvis that automates the testing process by scanning web apps, creating detailed memory structures, generating tests based on user interactions, and continuously testing for defects. QA.tech provides developer-friendly bug reports, supports various web frameworks, and integrates with CI/CD pipelines. It aims to revolutionize the testing process by offering faster, smarter, and more efficient testing solutions.

Heal.dev is an AI-powered platform that offers an easy way to write stable end-to-end tests by automating regression testing, end-to-end tests, and production smoke tests in minutes. It provides tools for defining stable tests in plain English, automating complex checks with AI-powered assertions, composing tests with blocks, extending functionality with JavaScript code, and detecting bugs smartly. Heal.dev aims to speed up development cycles, eliminate flaky tests, and allow teams to focus on shipping great software.

Digital.ai is an AI-powered DevOps platform that helps organizations automate software releases, improve mobile application testing and security, and provide insights across the software lifecycle. The platform includes a suite of products that can be used to manage the complexities of software delivery, including analytics and intelligence, enterprise agile planning, application protection and security, continuous testing, release orchestration, and deployment automation.

What The Diff is an AI-powered code review assistant that helps you to write pull request descriptions, send out summarized notifications, and refactor minor issues during the review. It uses natural language processing to understand the changes in your code and generate clear and concise descriptions. What The Diff also provides rich summary notifications that are easy for non-technical stakeholders to understand, and it can generate beautiful changelogs that you can share with your team or the public.

Metabob is an AI-powered code review tool that helps developers detect, explain, and fix coding problems. It utilizes proprietary graph neural networks to detect problems and LLMs to explain and resolve them, combining the best of both worlds. Metabob's AI is trained on millions of bug fixes performed by experienced developers, enabling it to detect complex problems that span across codebases and automatically generate fixes for them. It integrates with popular code hosting platforms such as GitHub, Bitbucket, Gitlab, and VS Code, and supports various programming languages including Python, Javascript, Typescript, Java, C++, and C.

Auto Playwright is a tool that allows users to run Playwright tests using AI. It eliminates the need for selectors by determining actions at runtime based on plain-text instructions. Users can automate complex scenarios, write tests concurrently with or before functionality development, and benefit from rapid test creation. The tool supports various Playwright actions and offers additional options for debugging and customization. It uses HTML sanitization to reduce costs and improve text quality when interacting with the OpenAI API.

The AI Enablement Stack is a curated collection of venture-backed companies, tools, and technologies that enable developers to build, deploy, and manage AI applications. It provides a structured view of the AI development ecosystem across five key layers: Agent Consumer Layer, Observability and Governance Layer, Engineering Layer, Intelligence Layer, and Infrastructure Layer. Each layer focuses on specific aspects of AI development, from end-user interaction to model training and deployment. The stack aims to help developers find the right tools for building AI applications faster and more efficiently, assist engineering leaders in making informed decisions about AI infrastructure and tooling, and help organizations understand the AI development landscape to plan technology adoption.

Supervisely is a computer vision platform that provides a range of tools and services for developing and deploying computer vision solutions. It includes a data labeling platform, a model training platform, and a marketplace for computer vision apps. Supervisely is used by a variety of organizations, including Fortune 500 companies, research institutions, and government agencies.

Analyze the following text from a github repository (name and readme text at end) . Then, generate a JSON object with the following keys and provide the corresponding information for each key, in lowercase letters: 'description' (detailed description of the repo, must be less than 400 words，Ensure that no line breaks and quotation marks.),'for_jobs' (List 5 jobs suitable for this tool,in lowercase letters), 'ai_keywords' (keywords of the tool,user may use those keyword to find the tool,in lowercase letters), 'for_tasks' (list of 5 specific tasks user can use this tool to do,in lowercase letters), 'answer' (in english languages)

ARTKIT is a Python framework developed by BCG X for automating prompt-based testing and evaluation of Gen AI applications. It allows users to develop automated end-to-end testing and evaluation pipelines for Gen AI systems, supporting multi-turn conversations and various testing scenarios like Q&A accuracy, brand values, equitability, safety, and security. The framework provides a simple API, asynchronous processing, caching, model agnostic support, end-to-end pipelines, multi-turn conversations, robust data flows, and visualizations. ARTKIT is designed for customization by data scientists and engineers to enhance human-in-the-loop testing and evaluation, emphasizing the importance of tailored testing for each Gen AI use case.

Code Review GPT uses Large Language Models to review code in your CI/CD pipeline. It helps streamline the code review process by providing feedback on code that may have issues or areas for improvement. It should pick up on common issues such as exposed secrets, slow or inefficient code, and unreadable code. It can also be run locally in your command line to review staged files. Code Review GPT is in alpha and should be used for fun only. It may provide useful feedback but please check any suggestions thoroughly.

Arbigent (Arbiter-Agent) is an AI agent testing framework designed to make AI agent testing practical for modern applications. It addresses challenges faced by traditional UI testing frameworks and AI agents by breaking down complex tasks into smaller, dependent scenarios. The framework is customizable for various AI providers, operating systems, and form factors, empowering users with extensive customization capabilities. Arbigent offers an intuitive UI for scenario creation and a powerful code interface for seamless test execution. It supports multiple form factors, optimizes UI for AI interaction, and is cost-effective by utilizing models like GPT-4o mini. With a flexible code interface and open-source nature, Arbigent aims to revolutionize AI agent testing in modern applications.

The 'nlp-llms-resources' repository is a comprehensive resource list for Natural Language Processing (NLP) and Large Language Models (LLMs). It covers a wide range of topics including traditional NLP datasets, data acquisition, libraries for NLP, neural networks, sentiment analysis, optical character recognition, information extraction, semantics, topic modeling, multilingual NLP, domain-specific LLMs, vector databases, ethics, costing, books, courses, surveys, aggregators, newsletters, papers, conferences, and societies. The repository provides valuable information and resources for individuals interested in NLP and LLMs.

Awesome MLSecOps is a curated list of open-source tools, resources, and tutorials for MLSecOps (Machine Learning Security Operations). It includes a wide range of security tools and libraries for protecting machine learning models against adversarial attacks, as well as resources for AI security, data anonymization, model security, and more. The repository aims to provide a comprehensive collection of tools and information to help users secure their machine learning systems and infrastructure.

CodiumAI Cover Agent is a tool designed to help increase code coverage by automatically generating qualified tests to enhance existing test suites. It utilizes Generative AI to streamline development workflows and is part of a suite of utilities aimed at automating the creation of unit tests for software projects. The system includes components like Test Runner, Coverage Parser, Prompt Builder, and AI Caller to simplify and expedite the testing process, ensuring high-quality software development. Cover Agent can be run via a terminal and is planned to be integrated into popular CI platforms. The tool outputs debug files locally, such as generated_prompt.md, run.log, and test_results.html, providing detailed information on generated tests and their status. It supports multiple LLMs and allows users to specify the model to use for test generation.

**Description:** PromptFuzz is an automated tool that generates high-quality fuzz drivers for libraries via a fuzz loop constructed on mutating LLMs' prompts. The fuzz loop of PromptFuzz aims to guide the mutation of LLMs' prompts to generate programs that cover more reachable code and explore complex API interrelationships, which are effective for fuzzing. **Features:** * **Multiply LLM support** : Supports the general LLMs: Codex, Inocder, ChatGPT, and GPT4 (Currently tested on ChatGPT). * **Context-based Prompt** : Construct LLM prompts with the automatically extracted library context. * **Powerful Sanitization** : The program's syntax, semantics, behavior, and coverage are thoroughly analyzed to sanitize the problematic programs. * **Prioritized Mutation** : Prioritizes mutating the library API combinations within LLM's prompts to explore complex interrelationships, guided by code coverage. * **Fuzz Driver Exploitation** : Infers API constraints using statistics and extends fixed API arguments to receive random bytes from fuzzers. * **Fuzz engine integration** : Integrates with grey-box fuzz engine: LibFuzzer. **Benefits:** * **High branch coverage:** The fuzz drivers generated by PromptFuzz achieved a branch coverage of 40.12% on the tested libraries, which is 1.61x greater than _OSS-Fuzz_ and 1.67x greater than _Hopper_. * **Bug detection:** PromptFuzz detected 33 valid security bugs from 49 unique crashes. * **Wide range of bugs:** The fuzz drivers generated by PromptFuzz can detect a wide range of bugs, most of which are security bugs. * **Unique bugs:** PromptFuzz detects uniquely interesting bugs that other fuzzers may miss. **Usage:** 1. Build the library using the provided build scripts. 2. Export the LLM API KEY if using ChatGPT or GPT4. 3. Generate fuzz drivers using the `fuzzer` command. 4. Run the fuzz drivers using the `harness` command. 5. Deduplicate and analyze the reported crashes. **Future Works:** * **Custom LLMs suport:** Support custom LLMs. * **Close-source libraries:** Apply PromptFuzz to close-source libraries by fine tuning LLMs on private code corpus. * **Performance** : Reduce the huge time cost required in erroneous program elimination.

Momentum is an open-source behavioral auditor for backend code that helps developers generate powerful insights into their codebase. It analyzes code behavior, tests it at every git push, and ensures readiness for production. Momentum understands backend code, visualizes dependencies, identifies behaviors, generates test code, runs code in the local environment, and provides debugging solutions. It aims to improve code quality, streamline testing processes, and enhance developer productivity.

Mutahunter is an open-source language-agnostic mutation testing tool maintained by CodeIntegrity. It leverages LLM models to inject context-aware faults into codebase, ensuring comprehensive testing. The tool aims to empower companies and developers to enhance test suites and improve software quality by verifying the effectiveness of test cases through creating mutants in the code and checking if the test cases can catch these changes. Mutahunter provides detailed reports on mutation coverage, killed mutants, and survived mutants, enabling users to identify potential weaknesses in their test suites.

Agentless is an open-source tool designed for automatically solving software development problems. It follows a two-phase process of localization and repair to identify faults in specific files, classes, and functions, and generate candidate patches for fixing issues. The tool is aimed at simplifying the software development process by automating issue resolution and patch generation.

NotHotDog is an open-source testing framework for evaluating and validating voice and text-based AI agents. It offers a user-friendly interface for creating, managing, and executing tests against AI models. The framework supports WebSocket and REST API, test case management, automated evaluation of responses, and provides a seamless experience for test creation and execution.

wacat is a tool designed to challenge web applications by simulating chaotic user behavior, such as random navigation, form input, and button clicks. It also incorporates AI-powered error detection, supporting features like detecting error messages, generating AI-driven content, and detecting HTTP errors and console log errors. wacat can be configured for various testing scenarios, including authentication, excluding specific pages, running in headless mode, and setting wait times and timeouts. It is built using TypeScript, oclif, Playwright, and Next.js for test applications.

Pythagora is an automated testing tool designed to generate unit tests using GPT-4. By running a single command, users can create tests for specific functions in their codebase. The tool leverages AST parsing to identify related functions and sends them to the Pythagora server for test generation. Pythagora primarily focuses on JavaScript code and supports Jest testing framework. Users can expand existing tests, increase code coverage, and find bugs efficiently. It is recommended to review the generated tests before committing them to the repository. Pythagora does not store user code on its servers but sends it to GPT and OpenAI for test generation.

iOS Engineer expert in crafting and refining unit tests.

Expert in testing, inspection, certification, compliant with OpenAI policies, developed on OpenAI.

Assists with code review, pull requests, and writing tests.

code security expert to do code review

Critically analyze SLIs/SLOs with a deeper, provocative approach

Friendly JSON, HTML, XML validator with detailed advice.

Ensures project deliverables meet predetermined quality standards.

Ensures product quality through systematic process monitoring and evaluation.

Designed for excellence in Quality Assurance, fine-tuning custom GPT configurations through continuous refinement.

制定和实施质量管理体系；审核和改进质量管理体系；培训和指导员；处理质量问题；与其他部门协调；持续改进

Enhanced QA/QC expertise with user-driven improvements, powered by OpenAI

Gives structure to messy GitHub issues.

Ensures product quality through rigorous, systematic testing processes.

Ensures software quality through automated testing strategies.

Direct, concise engineer with a hint of humor.

Improves product quality through innovative research and development.

Makes every Sofware Tester an Expert Prompt Engineer

I create Playwright test cases for specific URLs.

I provide Manual QA interview prep and conduct mock interviews.

Expert on IAEA Safety Standards