Ratings and Reviews 0 Ratings

Total 0 out of 5 stars
ease 0 out of 5 stars
features 0 out of 5 stars
design 0 out of 5 stars
support 0 out of 5 stars

This software has no reviews. Be the first to write a review.

Write a Review

Ratings and Reviews 0 Ratings

Total 0 out of 5 stars
ease 0 out of 5 stars
features 0 out of 5 stars
design 0 out of 5 stars
support 0 out of 5 stars

This software has no reviews. Be the first to write a review.

Write a Review

Alternatives to Consider

  • MuukTest Reviews & Ratings
    4.6 out of 5 stars 34 Ratings
    Company Website for MuukTest
  • Parasoft Reviews & Ratings
    4.6 out of 5 stars 152 Ratings
    Company Website for Parasoft
  • QA Wolf Reviews & Ratings
    4.8 out of 5 stars 273 Ratings
    Company Website for QA Wolf
  • Virtuoso QA Reviews & Ratings
    4.5 out of 5 stars 131 Ratings
    Company Website for Virtuoso QA
  • Checksum.ai Reviews & Ratings
    5.0 out of 5 stars 2 Ratings
    Company Website for Checksum.ai
  • TrustInSoft Analyzer Reviews & Ratings
    4.3 out of 5 stars 6 Ratings
    Company Website for TrustInSoft Analyzer
  • Okyline Reviews & Ratings
    5.0 out of 5 stars 2 Ratings
    Company Website for Okyline
  • Source Defense Reviews & Ratings
    5.0 out of 5 stars 7 Ratings
    Company Website for Source Defense
  • Flagsmith Reviews & Ratings
    4.8 out of 5 stars 43 Ratings
    Company Website for Flagsmith
  • Apify Reviews & Ratings
    4.8 out of 5 stars 1,800 Ratings
    Company Website for Apify

What is JCov?

The JCov open-source project was established to gather quality metrics pertinent to the creation of test suites. By making JCov readily available, the initiative seeks to improve the verification process of regression test executions in the development of OpenJDK. The main objective of JCov is to provide clarity regarding test coverage metrics. Advocating for a standardized coverage tool such as JCov offers advantages to OpenJDK developers by delivering a code coverage solution that progresses alongside developments in the Java language and virtual machine. Completely developed in Java, JCov functions as a tool for evaluating and analyzing dynamic code coverage in Java applications. It encompasses features that assess method coverage, linear block coverage, and branch coverage, while also pinpointing execution paths that go untested. Furthermore, JCov has the capability to annotate the source code of the program with coverage information. This tool is particularly significant from a testing perspective, as it aids in uncovering execution paths and provides insights into how various code segments are utilized during testing. Such comprehensive understanding empowers developers to refine their testing methodologies and elevate the overall quality of their code, ultimately contributing to more robust software development practices.

What is Coco Code Coverage?

Coco by Qt is an advanced code coverage and test analysis platform designed for developers, QA engineers, and compliance leads building safety-critical or performance-sensitive software. Supporting C, C++, C#, QML, and Tcl, Coco measures coverage from statement and branch analysis to Modified Condition/Decision Coverage (MC/DC), giving a granular view of code quality and test completeness. It integrates seamlessly with IDEs like Visual Studio, Eclipse, and Qt Creator, as well as CI/CD tools such as Jenkins and CMake, enabling automated coverage feedback within existing workflows. Coco’s instrumentation engine works across desktop, embedded, and cross-compiled environments, supporting diverse toolchains like GCC, Clang, ARM, and Green Hills. The platform helps teams meet functional safety requirements under ISO 26262, DO-178C, EN 50128, and IEC 62304, with ready-to-use qualification kits that save months of manual certification work. Its Cross-Compilation Add-on enables coverage analysis on constrained systems and microcontrollers, while the Test Center integration consolidates coverage data and test results for a unified QA dashboard. By highlighting untested logic, redundant test cases, and compliance gaps, Coco reduces testing time while increasing accuracy. Its audit-ready reports and traceable artifacts make it indispensable for industries like automotive, medical devices, rail, and aerospace. Whether running on Windows, Linux, macOS, or real hardware, Coco ensures developers know exactly what’s tested—and what’s missed. In a world where software quality and certification matter more than ever, Coco helps teams measure, optimize, and certify with confidence.

Media

Media

Integrations Supported

AWS Marketplace
Amazon Corretto
Apache NetBeans
Red Hat Runtimes

Integrations Supported

BlackBerry QNX
C
C#
C++
Coverity Static Analysis
FreeRTOS
Git
GitLab
Jenkins
Jira
NUnit
SystemC
Tcl
TestRail
Visual Studio
VxWorks

API Availability

Has API

API Availability

Pricing Information

Free
Free Version

Pricing Information

Pricing not provided
Free Trial Offered?

Supported Platforms

Windows
Mac
Linux

Supported Platforms

Windows
Linux

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
Webinars
On-Site Training

Company Facts

Organization Name

OpenJDK

Company Location

United States

Company Website

wiki.openjdk.org/display/CodeTools/jcov

Company Facts

Organization Name

Qt Group

Date Founded

1994

Company Location

Finland

Company Website

www.qt.io/quality-assurance/coco

Categories and Features

Code Coverage

Not specified

Regression Testing

Not specified

Categories and Features

Code Coverage

Not specified

Static Code Analysis

Not specified

Popular Alternatives

Popular Alternatives

BullseyeCoverage Reviews & Ratings

BullseyeCoverage

Bullseye Testing Technology
RKTracer Reviews & Ratings

RKTracer

RKVALIDATE
RKTracer Reviews & Ratings

RKTracer

RKVALIDATE
VectorCAST Reviews & Ratings

VectorCAST

VECTOR Informatik
Parasoft Reviews & Ratings

Parasoft

4.6 out of 5 stars