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Advanced AI-powered testing solutions for Java offer unparalleled productivity and optimized workflows across every stage of the SDLC for applications to ensure continuous software quality.
Deliver high-quality, secure, and reliable software to the market faster with Parasoft’s automated software testing solutions tailored for Java applications. Seamlessly optimize testing processes throughout the SDLC, reducing project costs by increasing productivity and efficiency.
Shift security left. Get broad support for security standards like OWASP, CWE, CERT, and more. Remediate faster with AI-driven triaging and generated code fixes.
Jump to: Static Analysis »
Increase productivity with AI-powered automated unit test generation. Drive code coverage with high-quality test cases and meet requirements with ease.
Jump to: Unit Testing »
Use AI-enhanced functional testing and service virtualization solutions to easily create robust test scenarios and control environments for stable automation.
Jump to: Functional Testing »
Harness AI for efficient, robust Selenium test automation and increase the scalability, maintainability, and efficiency of web UI testing.
Jump to: Selenium Testing »
Analyze coverage data from all testing practices for a complete application coverage view. Identify coverage gaps and bridge them effectively.
Jump to: Code Coverage »
Get feedback 90% faster with intelligent test impact analysis for unit testing, automated functional testing, and manual regression testing.
Jump to: Test Impact Analysis »
Ensure thorough testing with quality metrics. Release applications with confidence that they’re safe, secure, and reliable.
Jump to: Reporting »
Use Jtest’s extensive static analysis checkers and testing techniques to ensure Java code quality. Teams can verify compliance with industry standards or enforce custom coding guidelines using built-in or user-defined configurations. Shift-left testing detects issues early, while AI rapidly resolves violations preventing late-stage defects.
Key capabilities:
Increased
Code quality for Java applications.
Enhanced
Code stability, reuse, and maintainability.
Striking a balance between thoroughness and efficiency poses a critical challenge for dev teams grappling to meet Java unit testing and code coverage requirements while sustaining high productivity levels.
With AI-enhanced Jtest, teams gain a head start in building effective unit test suites and reaching code coverage targets. Jtest uses proprietary built-in AI algorithms to swiftly generate a suite of JUnit tests with assertions for uncovered lines of code, rapidly increasing code coverage metrics.
Integrated within the IDE, Jtest’s Unit Test Assistant generates unit tests for newly developed code and provides actionable AI-driven recommendations to mock or stub dependencies, parameterize, or clone and mutate specific test cases to drive higher coverage levels.
For added customization, integrate Jtest with various LLM providers like OpenAI and Azure OpenAI to tailor and improve test cases. As code changes, use live unit testing in the IDE or test impact analysis in the CI/CD pipeline to automatically run only the tests impacted by source modifications. Get immediate feedback to safeguard against downstream regression failures.
Using Jtest’s CLI, teams can integrate unit test generation directly into their build pipelines. Jtest identifies uncovered lines of code and autonomously generates new tests to fill coverage gaps. This enables teams to meet coverage targets and pass quality gates without requiring developers to write every unit test manually.
Learn how a leading financial firm leveraged Parasoft Jtest to:
100%
Acceleration of unit test generation.
85%
Code coverage achieved in a few weeks.
Parasoft SOAtest coupled with Virtualize for service virtualization revolutionizes how teams achieve continuous test automation goals. One major challenge teams face is the lack of comprehensive test coverage. SOAtest addresses this with robust AI-enhanced capabilities that enable teams to create and execute a diverse range of tests to ensure thorough coverage across all layers of the application:
Seamless integration into popular CI/CD pipelines enables execution, quality gate enforcement, and reporting. Teams can optimize testing of pull requests by using SOAtest’s test impact analysis to identify and run the subset of test cases required to validate the application changes. Continuously publishing test results into Parasoft DTP provides:
Another challenge is the dependency on external systems or services, which can impede test execution and slow down the automation process. Teams can simulate the behavior of these dependencies with Virtualize to ensure seamless, uninterrupted test automation, even in complex environments or architectures like distributed microservices.
60%
Reduction of functional test creation time.
80%
Increase in API test coverage.
Application teams encounter the following common challenges in Selenium testing:
Parasoft Selenic, augmented with AI/ML capabilities, empowers development teams to:
Download Free Edition of Parasoft Selenic »
Collect, monitor, and analyze code coverage from unit, functional, and manual testing for Java applications. Drive higher levels of code coverage by understanding what lines of code have been tested and targeting coverage gaps.
Meeting code coverage requirements in Java projects poses challenges due to complex modern software systems, diverse testing scenarios, and the need for comprehensive testing across components and functionalities. Use our solution to:
Read Blog Post: Application Coverage Is the Most Powerful Metric You’re Not Measuring »
Parasoft provides broad and flexible AI-enhanced Test Impact Analysis (TIA) support across the Java software development lifecycle:
Parasoft’s Java code coverage agents collect detailed coverage data across test types and executions (manual or automated), then pass this data the TIA engine within Parasoft tools. The AI intelligently maps code changes to impacted tests and automatically selects only the relevant test cases to execute.
Release applications with confidence knowing they’re safe, secure, and reliable based on quality metrics from all of the team’s testing practices including static analysis, unit testing, functional testing, nonfunctional testing, and code coverage.
Teams can publish testing results from the CI/CD pipelines into Parasoft DTP for advanced reporting and build-to-build trends analysis. Using predefined or customized dashboards, get a specific view of testing results and trends data to easily track the following:
Go beyond simple reporting using DTP’s award-winning analytics widgets for insights into business risks and productivity improvements. Streamline triaging of static analysis results by leveraging AI/ML-enhanced analytics and recommendations. Train DTP’s ML models to understand the violations to fix and who to assign them to. Our optional integration with OpenAI/Azure OpenAI providers enables teams to use DTP’s CVE match analysis, ensuring remediation efforts focus on real security vulnerabilities.
Teams can customize the analytics to measure and monitor key performance indicators to assess potential risks, prioritize findings, and validate that applications meet quality, security, and reliability requirements to ensure release readiness.
Read Blog: Modern Analytics for Modern Software Testing »
