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What is Coverlet?

Coverlet operates with the .NET Framework on Windows and also supports .NET Core across a range of compatible platforms, specifically offering coverage for deterministic builds. The current implementation, however, has its limitations and often necessitates a workaround for optimal functionality. For developers interested in visualizing Coverlet's output while coding within Visual Studio, various platform-specific add-ins can be utilized. Moreover, Coverlet integrates effortlessly with the build system to facilitate code coverage analysis after tests are executed. Enabling code coverage is a simple process; you only need to set the CollectCoverage property to true in your configuration. To effectively use Coverlet, it is essential to specify the path to the assembly that contains the unit tests. In addition, you must designate both the test runner and the corresponding arguments through the --target and --targetargs options. It’s important to ensure that invoking the test runner with these options does not require recompiling the unit test assembly, as such recompilation would hinder the generation of accurate coverage results. Adequate configuration and a clear understanding of these components will lead to a more efficient experience while utilizing Coverlet for assessing code coverage. Ultimately, mastering these details can significantly enhance your development workflow and contribute to more reliable software quality assessments.

What is Code Intelligence?

Our platform employs a range of robust security strategies, such as feedback-driven fuzz testing and coverage-guided fuzz testing, to produce an extensive array of test cases that identify elusive bugs within your application. This white-box methodology not only helps mitigate edge cases but also accelerates the development process. Cutting-edge fuzzing engines are designed to generate inputs that optimize code coverage effectively. Additionally, sophisticated bug detection tools monitor for errors during the execution of code, ensuring that only genuine vulnerabilities are exposed. To consistently reproduce errors, you will require both the stack trace and the input data. Furthermore, AI-driven white-box testing leverages insights from previous tests, enabling a continuous learning process regarding the application's intricacies. As a result, you can uncover security-critical bugs with ever-increasing accuracy, ultimately enhancing the reliability of your software. This innovative approach not only improves security but also fosters confidence in the development lifecycle.

Media

Media

Integrations Supported

Visual Studio
.NET
Codecov

Integrations Supported

Visual Studio
Apache Maven
C
C++
CLion
CircleCI
Docker
GitHub
GitLab
Go
Gradle
JUnit
Java
Jenkins
Kubernetes
Travis CI
Vim
Visual Basic

API Availability

API Availability

Has API

Pricing Information

Free
Free Version

Pricing Information

Pricing not provided

Supported Platforms

Windows
Mac
Linux

Supported Platforms

SaaS
Windows
Mac
On-Prem
Linux

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Coverlet

Company Website

github.com/coverlet-coverage/coverlet

Company Facts

Organization Name

Code Intelligence

Company Location

Germany

Company Website

www.code-intelligence.com

Categories and Features

Code Coverage

Not specified

Categories and Features

Application Security

Analytics / Reporting
Training Resources
Vulnerability Detection
Vulnerability Remediation

Code Coverage

Not specified

Fuzz Testing

Not specified

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