Related Products
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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.
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About
Use optimization and simulation models in your desktop, Web or mobile application. Use the same high-level objects (like Problem, Solver, Variable and Function), collections, properties and methods across different programming languages. The same object-oriented API is exposed "over the wire" through Web Services WS-* standards to remote clients in PHP, JavaScript, C# and other languages. Procedural languages can use conventional calls that correspond naturally to the properties and methods of the Object-Oriented API. Linear and quadratic programming, mixed-integer programming, smooth nonlinear optimization, global optimization, and non-smooth evolutionary and tabu search are all included. The world's best optimizers, from Gurobi™, XPRESS™ and MOSEK™ for linear, quadratic and conic models to KNITRO™, SQP and GRG methods for nonlinear models "plug into" Solver SDK. Easily create a sparse DoubleMatrix object with 1 million rows and columns.
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About
Testwell CTC++ is a powerful instrumentation-based code coverage and dynamic analysis tool for C and C++ code. With certain add-on components CTC++ can be used also on C#, Java and Objective-C code. Further, again with certain add-on components, CTC++ can be used to analyse code basically at any embedded target machines, also in very small ones (limited memory, no operating system). CTC++ provides Line Coverage, Statement Coverage, Function Coverage, Decision Coverage, Multicondition Coverage, Modified Condition/Decision Coverage (MC/DC), Condition Coverage. As a dynamic analysis tool, CTC++ shows the execution counters (how many times executed) in the code, i.e. more than a plain executed/not executed information. You can also use CTC++ to measure function execution costs (normally time) and to enable function entry/exit tracing at test time. CTC++ is easy to use.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
Any user looking for a solution to measure line and branch coverage to produce test reports
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Audience
Companies searching for a solution to create optimization and simulation models
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Audience
IT teams looking for an advanced Code Coverage solution
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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API
Offers API
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Screenshots and Videos |
Screenshots and Videos |
Screenshots and Videos |
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Pricing
Free
Free Version
Free Trial
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Pricing
$2495 one-time payment
Free Version
Free Trial
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Pricing
Free
Free Version
Free Trial
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Reviews/
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationCoverage.py
United States
coverage.readthedocs.io/en/7.0.0/
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Company InformationFrontline Systems
www.solver.com/solver-sdk-platform
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Company InformationTestwell
www.testwell.fi/ctcdesc.html
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Categories |
Categories |
Categories |
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Simulation Features
1D Simulation
3D Modeling
3D Simulation
Agent-Based Modeling
Continuous Modeling
Design Analysis
Direct Manipulation
Discrete Event Modeling
Dynamic Modeling
Graphical Modeling
Industry Specific Database
Monte Carlo Simulation
Motion Modeling
Presentation Tools
Stochastic Modeling
Turbulence Modeling
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Integrations
C
C#
C++
Codecov
Django
HTML
JSON
Java
JavaScript
Mako
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Integrations
C
C#
C++
Codecov
Django
HTML
JSON
Java
JavaScript
Mako
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