JCov

JCov

OpenJDK

About

Coverage.py is a tool for measuring code coverage of Python programs. It monitors your program, noting which parts of the code have been executed, then analyzes the source to identify code that could have been executed but was not. Coverage measurement is typically used to gauge the effectiveness of tests. It can show which parts of your code are being exercised by tests, and which are not. Use coverage run to run your test suite and gather data. However you normally run your test suite, and you can run your test runner under coverage. If your test runner command starts with “python”, just replace the initial “python” with “coverage run”. To limit coverage measurement to code in the current directory, and also find files that weren’t executed at all, add the source argument to your coverage command line. By default, it will measure line (statement) coverage. It can also measure branch coverage. It can tell you what tests ran which lines.

About

The JCov open-source project is used to gather quality metrics associated with the production of test suites. JCov is being opened in order to facilitate the practice of verifying test execution of regression tests in OpenJDK development. The main motivation behind JCov is the transparency of test coverage metrics. The advantage to promoting standard coverage based on JCov is that OpenJDK developers will be able to use a code coverage tool that stays in the 'lock step' with Java language and VM developments. JCov is a pure java implementation of a code coverage tool that provides a means to measure and analyze dynamic code coverage of Java programs. JCov provides functionality to collect method, linear block, and branch coverage, as well as show uncovered execution paths. It is also able to show a program's source code annotated with coverage information. From a testing perspective, JCov is most useful to determine execution paths.

About

Enjoy the highest performance and unlimited possibilities when working with SQL Server. SQL Server Data Access Components (SDAC) is a library of components that provides native connectivity to SQL Server from Delphi and C++Builder including Community Edition, as well as Lazarus (and Free Pascal) for Windows, Linux, macOS, iOS, and Android for both 32-bit and 64-bit platforms. SDAC-based applications connect to SQL Server directly through OLE DB, which is a native SQL Server interface. SDAC is designed to help programmers develop faster and cleaner SQL Server database applications. SDAC, a high-performance, and feature-rich SQL Server connectivity solution is a complete replacement for standard SQL Server connectivity solutions and presents an efficient native alternative to the Borland Database Engine (BDE) and standard dbExpress driver for access to SQL Server. SDAC-based DB applications are easy to deploy, and do not require the installation of other data provider layers.

About

Imageio is a Python library that provides an easy interface to read and write a wide range of image data, including animated images, volumetric data, and scientific formats. It is cross-platform, runs on Python 3.5+, and is easy to install. Imageio is written in pure Python, so installation is easy. Imageio works on Python 3.5+. It also works on Pypy. Imageio depends on Numpy and Pillow. For some formats, imageio needs additional libraries/executables (e.g. ffmpeg), which imageio helps you to download/install. If something doesn’t work as it should, you need to know where to search for causes. The overview on this page aims to help you in this regard by giving you an idea of how things work, and - hence - where things may go sideways.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Any user looking for a solution to measure line and branch coverage to produce test reports

Audience

Developers seeking a solution to gather quality metrics associated with the production of test suites

Audience

Programmers in need of a tool to develop faster and cleaner SQL Server database applications

Audience

Component Library solution for developers

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Pricing

$199.95 per year
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

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Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Coverage.py
United States
coverage.readthedocs.io/en/7.0.0/

Company Information

OpenJDK
United States
wiki.openjdk.org/display/CodeTools/jcov

Company Information

Devart
Founded: 1997
Czech Republic
www.devart.com/sdac/

Company Information

imageio
imageio.readthedocs.io/en/stable/

Alternatives

Alternatives

Alternatives

Alternatives

JDeli

JDeli

IDR Solutions
JCov

JCov

OpenJDK
RKTracer

RKTracer

RKVALIDATE
yarl

yarl

Python Software Foundation
blanket.js

blanket.js

Blanket.js
Devel::Cover

Devel::Cover

metacpan
blanket.js

blanket.js

Blanket.js

Categories

Categories

Categories

Categories

Integrations

AWS Marketplace
Amazon Corretto
Apache NetBeans
Azure SQL Database
C
Codecov
Delphi
Django
HTML
Java
Mako
NumPy
Pillow
Python
Red Hat Runtimes
SQL Server
Tidelift
XML
pytest
pytest-cov

Integrations

AWS Marketplace
Amazon Corretto
Apache NetBeans
Azure SQL Database
C
Codecov
Delphi
Django
HTML
Java
Mako
NumPy
Pillow
Python
Red Hat Runtimes
SQL Server
Tidelift
XML
pytest
pytest-cov

Integrations

AWS Marketplace
Amazon Corretto
Apache NetBeans
Azure SQL Database
C
Codecov
Delphi
Django
HTML
Java
Mako
NumPy
Pillow
Python
Red Hat Runtimes
SQL Server
Tidelift
XML
pytest
pytest-cov

Integrations

AWS Marketplace
Amazon Corretto
Apache NetBeans
Azure SQL Database
C
Codecov
Delphi
Django
HTML
Java
Mako
NumPy
Pillow
Python
Red Hat Runtimes
SQL Server
Tidelift
XML
pytest
pytest-cov
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