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Description

GitAuto is an AI-driven coding assistant that seamlessly connects with GitHub (and optionally Jira) to assess backlog tickets or issues, evaluate your repository's structure and code, and autonomously create and review pull requests, usually completing this process in around three minutes per ticket. It is capable of managing bug fixes, implementing feature requests, and enhancing test coverage. You can activate it through specific issue labels or selections on a dashboard, allowing it to write code or unit tests, initiate a pull request, execute GitHub Actions, and continuously rectify any failing tests until they succeed. Supporting ten programming languages, such as Python, Go, Rust, and Java, GitAuto is free for basic use, with paid plans available for those requiring a greater volume of pull requests and additional enterprise functionalities. Adhering to a strict zero data-retention policy, it processes your code through OpenAI without retaining it. Built to speed up delivery by allowing teams to address technical debt and backlogs without the need for extensive engineering resources, GitAuto functions as an AI backend engineer that drafts, tests, and refines code, thereby significantly enhancing development efficiency. This innovative tool not only streamlines workflows but also empowers teams to focus on more strategic tasks.

Description

An advanced AI-driven testing solution for web applications that identifies issues prior to user encounters is now available. This intelligent agent not only determines the necessary tests but also generates and maintains them to ensure their relevance over time. You can execute these tests directly from our platform or seamlessly integrate them into your CI/CD workflow. The reliability of end-to-end testing has been a significant concern, as failures can stem from more than just faulty code. Factors like external dependencies, timing discrepancies, unpredictable behaviors, race conditions, and state leaks contribute to the unpredictability of test outcomes. To address these challenges, we are implementing effective strategies to help you save valuable time that would otherwise be spent troubleshooting perfectly functioning code. By enhancing the stability of testing processes, we aim to boost overall software quality and developer confidence.