Best AI tools for< Test Generation >

Meticulous is an AI tool that revolutionizes frontend testing by automatically generating and maintaining test suites for web applications. It eliminates the need for manual test writing and maintenance, ensuring comprehensive test coverage without the hassle. Meticulous uses AI to monitor user interactions, generate test suites, and provide visual end-to-end testing capabilities. It offers lightning-fast testing, parallelized across a compute cluster, and integrates seamlessly with existing test suites. The tool is battle-tested to handle complex applications and provides developers with confidence in their code changes.

Octomind is an AI-powered Playwright end-to-end testing tool for web applications. It automatically discovers, generates, and runs tests to find bugs before customers do. With features like auto-generating tests, running tests to find bugs, and maintaining tests automatically, Octomind aims to simplify the testing process for developers. It offers real-world wins with testimonials from industry professionals and ensures stability, speed, and a better developer experience. Octomind is built on top of Playwright and can be seamlessly integrated into CI/CD pipelines for continuous testing and monitoring.

Qodo is a quality-first generative AI coding platform that helps developers write, test, and review code within IDE and Git. The platform offers automated code reviews, contextual suggestions, and comprehensive test generation, ensuring robust, reliable software development. Qodo integrates seamlessly to maintain high standards of code quality and integrity throughout the development process.

CreateMyTest is an online tool that uses artificial intelligence to automatically convert documents and YouTube videos into tests. It offers various question types, including multiple choice, true/false, matching, and fill in the blank. The platform aims to enhance studying by helping users retain knowledge through practice testing and reduce test anxiety.

CodiumAI is an AI-powered tool that helps developers write better code by generating meaningful tests, finding edge cases and suspicious behaviors, and suggesting improvements. It integrates with popular IDEs and Git platforms, and supports a wide range of programming languages. CodiumAI is designed to help developers save time, improve code quality, and stay confident in their code.

Tusk is an AI-powered tool designed to help prevent bugs caused by edge cases in software development. It generates unit and integration tests with codebase context, suggesting test cases by reading the codebase and documentation. Tusk seamlessly integrates into the workflow, sitting within GitHub and CI/CD pipelines. It offers features such as mock services, user-centric interface design, personalization, integration with third-party APIs, and scalable architecture for high performance.

TestCraft is an AI-powered assistant in software testing that leverages the capabilities of GPT-4 to simplify the testing process and enhance product quality. It generates automated tests for various automation frameworks and programming languages, helps in ideation by producing innovative test ideas, ensures project accessibility by identifying potential issues, and streamlines the testing process by transforming test ideas into automated tests. TestCraft aims to make software testing more efficient and effective.

Celp is a contextually aware AI-driven unit test generation tool designed for Typescript Node.js projects. It intelligently parses and deeply understands your code, saving you time and ensuring code stability. It uses an agentic design pattern to build context through parsing with Abstract Syntax Trees and intermediary AI prompting. Celp focuses on essential context, formulates detailed plans, and automatically runs and resolves tests. It generates unit tests from selection, reuses existing code, and learns as you use it.

Supertest is an AI copilot designed for software testing, offering a cutting-edge solution to automate various day-to-day QA engineering tasks using AI technology. It revolutionizes the way software testing is done by providing features like generating unit tests, auto-adding test IDs, and integrating seamlessly with VS Code. With Supertest, QA engineers can save time and effort in writing tests, ultimately improving the efficiency and accuracy of the testing process.

Stately is a visual logic builder that enables users to create complex logic diagrams and code in minutes. It provides a drag-and-drop editor that brings together contributors of all backgrounds, allowing them to collaborate on code, diagrams, documentation, and test generation in one place. Stately also integrates with AI to assist in each phase of the development process, from scaffolding behavior and suggesting variants to turning up edge cases and even writing code. Additionally, Stately offers bidirectional updates between code and visualization, allowing users to use the tools that make them most productive. It also provides integrations with popular frameworks such as React, Vue, and Svelte, and supports event-driven programming, state machines, statecharts, and the actor model for handling even the most complex logic in predictable, robust, and visual ways.

Refraction is an AI-powered code generation tool designed to help developers learn, improve, and generate code effortlessly. It offers a wide range of features such as bug detection, code conversion, function creation, CSP generation, CSS style conversion, debug statement addition, diagram generation, documentation creation, code explanation, code improvement, concept learning, CI/CD pipeline creation, SQL query generation, code refactoring, regex generation, style checking, type addition, and unit test generation. With support for 56 programming languages, Refraction is a versatile tool trusted by innovative companies worldwide to streamline software development processes using the magic of AI.

Momentic is a purpose-built AI tool for modern software testing, offering automation for E2E, UI, API, and accessibility testing. It leverages AI to streamline testing processes, from element identification to test generation, helping users shorten development cycles and enhance productivity. With an intuitive editor and the ability to describe elements in plain English, Momentic simplifies test creation and execution. It supports local testing without the need for a public URL, smart waiting for in-flight requests, and integration with CI/CD pipelines. Momentic is trusted by numerous companies for its efficiency in writing and maintaining end-to-end tests.

CodeComplete is an AI-powered coding assistant designed specifically for enterprise needs. It is efficient, reliable, and equipped with cutting-edge technology to improve developer productivity. CodeComplete offers a comprehensive suite of coding tools to improve end-to-end developer workflow, including code generation, code chat, automated unit test generation, automated documentation, and refactoring & migrations.

The website offers AI solutions for enterprises, focusing on cutting-edge technology and business acumen. They provide services from discovery and strategy to development and integration of custom AI solutions. The team consists of technologists, business experts, and product specialists who work closely with clients to optimize AI strategies for time, cost, and security. The application specializes in AI solutions for various business functions such as sales, marketing, operations, HR, finance, legal, risk, and IT. They emphasize an AI-first approach, co-creating roadmaps with clients to deliver impactful projects. The website also highlights their expertise in AI for IT, including code review, test generation, DevOps, monitoring, alerting, and security audits.

AI Generated Test Cases is an innovative tool that leverages artificial intelligence to automatically generate test cases for software applications. By utilizing advanced algorithms and machine learning techniques, this tool can efficiently create a comprehensive set of test scenarios to ensure the quality and reliability of software products. With AI Generated Test Cases, software development teams can save time and effort in the testing phase, leading to faster release cycles and improved overall productivity.

Tonic.ai is a platform that allows users to build AI models on their unstructured data. It offers various products for software development and LLM development, including tools for de-identifying and subsetting structured data, scaling down data, handling semi-structured data, and managing ephemeral data environments. Tonic.ai focuses on standardizing, enriching, and protecting unstructured data, as well as validating RAG systems. The platform also provides integrations with relational databases, data lakes, NoSQL databases, flat files, and SaaS applications, ensuring secure data transformation for software and AI developers.

Roost.ai is an AI-driven testing tool that offers automated test case generation using Large Language Models (LLMs). It helps in building reliable software by providing 100% test coverage, every single time. Roost.ai acts as a testing co-pilot, powered by generative AI, and is trusted by global financial institutions. The tool automates test case generation, freeing up developer time to focus on coding and innovation. It enhances test accuracy and coverage by uncovering overlooked edge cases and detects static vulnerabilities in artifacts like source code and logs.

Sofy is a revolutionary no-code testing platform for mobile applications that integrates AI to streamline the testing process. It offers features such as manual and ad-hoc testing, no-code automation, AI-powered test case generation, and real device testing. Sofy helps app development teams achieve high-quality releases by simplifying test maintenance and ensuring continuous precision. With a focus on efficiency and user experience, Sofy is trusted by top industries for its all-in-one testing solution.

Teste.ai is an AI-powered platform offering a comprehensive set of software testing tools based on artificial intelligence. It enables users to create test cases, test plans, and step-by-step guides easily from software requirements or documentation. The platform covers functional, usability, performance, security, and API testing, simplifying test data generation and offering specialized prompts for each type of test. Teste.ai aims to streamline the test specification process, optimize tester's time, and enhance testing effectiveness by providing personalized prompts and a variety of testing tools.

Softbuilder is a software development company that focuses on creating innovative database tools. Their products include AbstraLinx, a powerful metadata discovery tool for Salesforce; ERBuilder Data Modeler, an easy-to-use database modeling software; and SB Data Generator, a tool for generating and populating databases with realistic test data. Softbuilder's tools aim to unlock limitless potential for businesses, teams, and databases by providing straightforward solutions that leverage the latest technology to enhance productivity and focus on delivering solutions.

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.

LLM-RGB is a repository containing a collection of detailed test cases designed to evaluate the reasoning and generation capabilities of Language Learning Models (LLMs) in complex scenarios. The benchmark assesses LLMs' performance in understanding context, complying with instructions, and handling challenges like long context lengths, multi-step reasoning, and specific response formats. Each test case evaluates an LLM's output based on context length difficulty, reasoning depth difficulty, and instruction compliance difficulty, with a final score calculated for each test case. The repository provides a score table, evaluation details, and quick start guide for running evaluations using promptfoo testing tools.

DevQualityEval is an evaluation benchmark and framework designed to compare and improve the quality of code generation of Language Model Models (LLMs). It provides developers with a standardized benchmark to enhance real-world usage in software development and offers users metrics and comparisons to assess the usefulness of LLMs for their tasks. The tool evaluates LLMs' performance in solving software development tasks and measures the quality of their results through a point-based system. Users can run specific tasks, such as test generation, across different programming languages to evaluate LLMs' language understanding and code generation capabilities.

Kaizen is an open-source project that helps teams ensure quality in their software delivery by providing a suite of tools for code review, test generation, and end-to-end testing. It integrates with your existing code repositories and workflows, allowing you to streamline your software development process. Kaizen generates comprehensive end-to-end tests, provides UI testing and review, and automates code review with insightful feedback. The file structure includes components for API server, logic, actors, generators, LLM integrations, documentation, and sample code. Getting started involves installing the Kaizen package, generating tests for websites, and executing tests. The tool also runs an API server for GitHub App actions. Contributions are welcome under the AGPL License.

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.

Twinny is a free and private AI extension for Visual Studio Code that offers AI-based code completion and code discussion features. It provides real-time code suggestions, function explanations, test generation, refactoring requests, and more. Twinny operates both online and offline, supports customizable API endpoints, conforms to OpenAI API standards, and offers various customization options for prompt templates, API providers, model names, and more. It is compatible with multiple APIs and allows users to accept code solutions directly in the editor, create new documents from code blocks, and copy generated code solution blocks. Twinny is open-source under the MIT license and welcomes contributions from the community.

AutoDev is an AI-powered coding wizard that supports multiple languages, including Java, Kotlin, JavaScript/TypeScript, Rust, Python, Golang, C/C++/OC, and more. It offers a range of features, including auto development mode, copilot mode, chat with AI, customization options, SDLC support, custom AI agent integration, and language features such as language support, extensions, and a DevIns language for AI agent development. AutoDev is designed to assist developers with tasks such as auto code generation, bug detection, code explanation, exception tracing, commit message generation, code review content generation, smart refactoring, Dockerfile generation, CI/CD config file generation, and custom shell/command generation. It also provides a built-in LLM fine-tune model and supports UnitEval for LLM result evaluation and UnitGen for code-LLM fine-tune data generation.

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.

Ragas is a framework that helps you evaluate your Retrieval Augmented Generation (RAG) pipelines. RAG denotes a class of LLM applications that use external data to augment the LLM’s context. There are existing tools and frameworks that help you build these pipelines but evaluating it and quantifying your pipeline performance can be hard. This is where Ragas (RAG Assessment) comes in. Ragas provides you with the tools based on the latest research for evaluating LLM-generated text to give you insights about your RAG pipeline. Ragas can be integrated with your CI/CD to provide continuous checks to ensure performance.

llm-swarm is a tool designed to manage scalable open LLM inference endpoints in Slurm clusters. It allows users to generate synthetic datasets for pretraining or fine-tuning using local LLMs or Inference Endpoints on the Hugging Face Hub. The tool integrates with huggingface/text-generation-inference and vLLM to generate text at scale. It manages inference endpoint lifetime by automatically spinning up instances via `sbatch`, checking if they are created or connected, performing the generation job, and auto-terminating the inference endpoints to prevent idling. Additionally, it provides load balancing between multiple endpoints using a simple nginx docker for scalability. Users can create slurm files based on default configurations and inspect logs for further analysis. For users without a Slurm cluster, hosted inference endpoints are available for testing with usage limits based on registration status.

LLM-PLSE-paper is a repository focused on the applications of Large Language Models (LLMs) in Programming Language and Software Engineering (PL/SE) domains. It covers a wide range of topics including bug detection, specification inference and verification, code generation, fuzzing and testing, code model and reasoning, code understanding, IDE technologies, prompting for reasoning tasks, and agent/tool usage and planning. The repository provides a comprehensive collection of research papers, benchmarks, empirical studies, and frameworks related to the capabilities of LLMs in various PL/SE tasks.

Awesome AI-Powered Developer Tools is a curated list of AI-powered developer tools that leverage AI to assist developers in tasks such as code completion, refactoring, debugging, documentation, and more. The repository includes a wide range of tools, from IDEs and Git clients to assistants, agents, app generators, UI generators, snippet generators, documentation tools, code generation tools, agent platforms, OpenAI plugins, search tools, and testing tools. These tools are designed to enhance developer productivity and streamline various development tasks by integrating AI capabilities.

LLM4EDA is a repository dedicated to showcasing the emerging progress in utilizing Large Language Models for Electronic Design Automation. The repository includes resources, papers, and tools that leverage LLMs to solve problems in EDA. It covers a wide range of applications such as knowledge acquisition, code generation, code analysis, verification, and large circuit models. The goal is to provide a comprehensive understanding of how LLMs can revolutionize the EDA industry by offering innovative solutions and new interaction paradigms.

A collection of AI-powered prompts designed to streamline software development workflows. The library contains prompts at various stages of development, with structured sequences of connected prompts, project initialization support, development assistance, and documentation generation. It aims to provide consistent guidance across different development phases, promote systematic development processes, and enable progress tracking and validation.

This repository, Online RLHF, focuses on aligning large language models (LLMs) through online iterative Reinforcement Learning from Human Feedback (RLHF). It aims to bridge the gap in existing open-source RLHF projects by providing a detailed recipe for online iterative RLHF. The workflow presented here has shown to outperform offline counterparts in recent LLM literature, achieving comparable or better results than LLaMA3-8B-instruct using only open-source data. The repository includes model releases for SFT, Reward model, and RLHF model, along with installation instructions for both inference and training environments. Users can follow step-by-step guidance for supervised fine-tuning, reward modeling, data generation, data annotation, and training, ultimately enabling iterative training to run automatically.

AITreasureBox is a comprehensive collection of AI tools and resources designed to simplify and accelerate the development of AI projects. It provides a wide range of pre-trained models, datasets, and utilities that can be easily integrated into various AI applications. With AITreasureBox, developers can quickly prototype, test, and deploy AI solutions without having to build everything from scratch. Whether you are working on computer vision, natural language processing, or reinforcement learning projects, AITreasureBox has something to offer for everyone. The repository is regularly updated with new tools and resources to keep up with the latest advancements in the field of artificial intelligence.

The repository 'Awesome-LLM4Cybersecurity' provides a comprehensive overview of the applications of Large Language Models (LLMs) in cybersecurity. It includes a systematic literature review covering topics such as constructing cybersecurity-oriented domain LLMs, potential applications of LLMs in cybersecurity, and research directions in the field. The repository analyzes various benchmarks, datasets, and applications of LLMs in cybersecurity tasks like threat intelligence, fuzzing, vulnerabilities detection, insecure code generation, program repair, anomaly detection, and LLM-assisted attacks.

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)

Speakeasy is a tool that helps developers create production-quality SDKs, Terraform providers, documentation, and more from OpenAPI specifications. It supports a wide range of languages, including Go, Python, TypeScript, Java, and C#, and provides features such as automatic maintenance, type safety, and fault tolerance. Speakeasy also integrates with popular package managers like npm, PyPI, Maven, and Terraform Registry for easy distribution.

The collection is actively updated with the help of an internal literature search engine.

The official GPT for the MegaMock library

Python code annotator and test generator

Algorithm-focused test case generator.

AI Voice Generation Expert - FREE TEST

For "Generative AI Test". Examiner in Generative AI, posing questions and providing feedback.

Research a given topic and generate multiple-choice questions

Generates items for psychometric instruments to measure psychological constructs.

Generates TTX scenarios

Generate and format Lorem Ipsum Text

Specialist in Flutter development, offering code assistance and best practices.

Assists teachers in marking tests and generating score reports.

Expert Aid in Behavior Intervention Plans and MTSS, crafting educational and practical client handouts, inputting test scores, and generating reports.

Help with generating unit tests using Spock framework

A practical assistant for generating custom checklists.

Generates multiple choice tests from theory files

Crea pruebas técnicas para programadores.

Assistant for creating and studying diverse academic tests.

Convert knowledge into flashcard format

Versatile Python programming assistant, adept in TDD and pytest across various projects.

This GPT writes tickets for software features. It uses Gherkin to specify scenarios. @cxmacedo