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TechMatrix Corporation will begin selling “Jtest 2025.1,” a Java-compatible test automation tool developed by Parasoft Corporation , from September 4, 2025.
Jtest is a Java test automation tool that provides powerful support for visualizing the quality of Java source code and streamlining unit testing through static analysis and unit testing support. Static analysis uses two methods: coding rule analysis and flow analysis, to identify potential problems in source code. Coding rule analysis validates source code using over 4,000 rules, helping to prevent program problems and improve maintainability. Flow analysis detects specific flows that may be causing resource leaks, security vulnerabilities, and other bugs from the vast number of processing flows that cross classes and packages. Unit testing support automatically creates test templates and mocks that can be used with JUnit, an open-source framework for Java unit testing, reducing the effort required for unit testing. Furthermore, it features a reporting function that displays a variety of information via a dashboard in a web browser, providing an environment where project members can efficiently review source code quality, even when working remotely.
In addition to Jtest’s built-in integration with OpenAI and Azure OpenAI, this latest update also strengthens integration with Large Language Model (LLM) providers that are compatible with the OpenAI REST API and have chat completion endpoints. The static analysis feature now supports 18 security compliance rules, including CWE (Common Weakness Enumeration) version 4.17 and CERT for Java, a coding guideline for improving security and reliability in Java programming. Additionally, an AI assistant has been added that allows users to ask questions in natural language. Users can type questions about how to use Jtest in the IDE, and the AI assistant will respond based on the product documentation and pre-configured integration with LLM providers. Even first-time Jtest users can efficiently access the information they need, facilitating product learning.
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As the exclusive distributor of Parasoft products in Japan, テックマトリックス will strengthen its activities in sales, marketing, user support, and more for Jtest as the ideal tool for solving the problems of all customers involved in Java software development.
New features and improvements in Jtest 2025.1
Enhanced LLM collaboration functionality
- Choose your local LLM provider
In addition to OpenAI and Azure OpenAI, you can now choose any LLM provider that is compatible with the OpenAI REST API and has a chat completion endpoint, allowing you to
work with locally deployed models and leverage LLM in a secure environment without data being sent outside the company. - Added diff editor feature
You can now see AI-recommended fixes in the diff editor and apply them directly to your code. You can apply all or a selection of fixes right in the editor, accelerating the process of fixing static analysis violations.
- AI improves failed test cases
A new Unit Test Assistant feature has been added, which uses AI to suggest fixes for failed test cases. Using AI to improve test cases contributes to improving testing efficiency.
- Support for inquiries via AI assistantWe
have added an AI assistant feature that allows you to ask questions in natural language. When you enter a question about how to use Jtest, our large-scale language model (LLM) provider will instantly guide you to the most appropriate answer based on the content of the product documentation. Even if you are using Jtest for the first time, you can efficiently obtain the information you need, making it easier to learn the product.
Automatically generate fixes for static analysis violations with GitHub Copilot Chat integration
When developing with Visual Studio Code, GitHub Copilot Chat integration is now supported to efficiently resolve static analysis violations. This eliminates issues that have been a problem with traditional static analysis tools, such as the time it takes to fix violations and not knowing how to fix them, and accelerates the process of correcting violations.
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