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features
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support

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Description

EvoSuite is a free, open-source tool designed to automatically create JUnit test suites for Java classes by leveraging search-based software testing (SBST) methods to improve code coverage and uncover possible defects. It analyzes Java bytecode to generate executable unit tests that include assertions, with the goal of achieving significant structural coverage, which encompasses branch, line, and mutation coverage. The tool employs a hybrid strategy that merges evolutionary algorithms with mutation testing to yield efficient and concise test suites. Supporting multiple Java versions, EvoSuite seamlessly integrates with various build systems and integrated development environments (IDEs) such as Maven, Eclipse, IntelliJ IDEA, and can also be used via command-line interfaces. Additionally, it provides capabilities for regression testing through its EvoSuiteR component, generating test suites that help identify discrepancies between two versions of a Java class. Benchmarking on a wide array of open-source projects has demonstrated EvoSuite's effectiveness, and it has been widely adopted in both academic research and practical industry applications to improve the software testing process. This versatility ensures that developers can rely on EvoSuite to enhance the reliability and quality of their Java applications.

Description

The JCov open-source initiative is designed to collect quality metrics related to the development of test suites. By making JCov accessible, the project aims to enhance the verification of regression test executions within OpenJDK development. The primary goal of JCov is to ensure transparency regarding test coverage metrics. Promoting a standard coverage tool like JCov benefits OpenJDK developers by providing a code coverage solution that evolves in harmony with advancements in the Java language and VM. JCov is entirely implemented in Java and serves as a tool to assess and analyze dynamic code coverage for Java applications. It offers features that measure method, linear block, and branch coverage, while also identifying execution paths that remain uncovered. Additionally, JCov can annotate the program's source code with coverage data. From a testing standpoint, JCov is particularly valuable for identifying execution paths and understanding how different pieces of code are exercised during testing. This detailed insight helps developers enhance their testing strategies and improve overall code quality.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Java
AWS Marketplace
Amazon Corretto
Apache NetBeans
Azure Marketplace
Eclipse IDE
Helidon
IntelliJ IDEA
Maven
Red Hat Runtimes
XML

Integrations

Java
AWS Marketplace
Amazon Corretto
Apache NetBeans
Azure Marketplace
Eclipse IDE
Helidon
IntelliJ IDEA
Maven
Red Hat Runtimes
XML

Pricing Details

Free
Free Trial
Free Version

Pricing Details

Free
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

EvoSuite

Country

United States

Website

www.evosuite.org

Vendor Details

Company Name

OpenJDK

Country

United States

Website

wiki.openjdk.org/display/CodeTools/jcov

Product Features

Automated Testing

Hierarchical View
Move & Copy
Parameterized Testing
Requirements-Based Testing
Security Testing
Supports Parallel Execution
Test Script Reviews
Unicode Compliance

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