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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

Description

Our platform uses a variety of security techniques, including feedback-based fuzz testing and coverage-guided fuzz testing, in order to generate millions upon millions of test cases that trigger difficult-to-find bugs deep in your application. This white-box approach helps to prevent edge cases and speed up development. Advanced fuzzing engines produce inputs that maximize code coverage. Powerful bug detectors check for errors during code execution. Only uncover true vulnerabilities. You will need the stack trace and input to prove that you can reproduce errors reliably every time. AI white-box testing is based on data from all previous tests and can continuously learn the inner workings of your application. This allows you to trigger security-critical bugs with increasing precision.

Description

Coverage.py serves as a powerful utility for assessing the code coverage of Python applications. It tracks the execution of your program, recording which segments of the code have been activated, and subsequently reviews the source to pinpoint areas that could have been executed yet remained inactive. This measurement of coverage is primarily utilized to evaluate the efficacy of testing efforts. It provides insights into which portions of your code are being tested and which are left untested. To collect data, you can use the command `coverage run` to execute your test suite. Regardless of how you typically run your tests, you can incorporate coverage by executing your test runner with the coverage tool. If the command for your test runner begins with "python," simply substitute the initial "python" with "coverage run." To restrict coverage evaluation to only the code within the current directory and to identify files that have not been executed at all, include the source parameter in your coverage command. By default, Coverage.py measures line coverage, but it is also capable of assessing branch coverage. Additionally, it provides information on which specific tests executed particular lines of code, enhancing your understanding of test effectiveness. This comprehensive approach to coverage analysis can significantly improve the quality and reliability of your codebase.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

C
C++
CLion
Codecov
Docker
GitHub
GitLab
Go
Gradle
HTML
Jenkins
Kubernetes
Mako
SQLite
Travis CI
Vim
Visual Basic
Visual Studio
pytest
pytest-cov

Integrations

C
C++
CLion
Codecov
Docker
GitHub
GitLab
Go
Gradle
HTML
Jenkins
Kubernetes
Mako
SQLite
Travis CI
Vim
Visual Basic
Visual Studio
pytest
pytest-cov

Pricing Details

No price information available.
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

Code Intelligence

Country

Germany

Website

www.code-intelligence.com

Vendor Details

Company Name

Coverage.py

Country

United States

Website

coverage.readthedocs.io/en/7.0.0/

Product Features

Application Security

Analytics / Reporting
Open Source Component Monitoring
Source Code Analysis
Third-Party Tools Integration
Training Resources
Vulnerability Detection
Vulnerability Remediation

Product Features

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