Open Source Software Testing Tools

GoogleTest is Google's C++ mocking and test framework. It's used by many internal projects at Google, as well as a number of notable projects such as The Chromium projects, the OpenCV computer vision library, and the LLVM compiler. This GoogleTest project is actually a union of what used to be two separate projects: the old GoogleTest and GoogleMock, an extension of GoogleTest for writing and using C++ mock classes. Since they were so closely related, they were merged to create an even better GoogleTest. GoogleTest features an xUnit test framework, a rich set of assertions, user-defined assertions, death tests, among many others. It's been used on a variety of platforms, including Cygwin, Symbian, MinGW and PlatformIO.

Deepchecks is the leading tool for testing and for validating your machine learning models and data, and it enables doing so with minimal effort. Deepchecks accompany you through various validation and testing needs such as verifying your data’s integrity, inspecting its distributions, validating data splits, evaluating your model and comparing between different models. While you’re in the research phase, and want to validate your data, find potential methodological problems, and/or validate your model and evaluate it. To run a specific single check, all you need to do is import it and then to run it with the required (check-dependent) input parameters. More details about the existing checks and the parameters they can receive can be found in our API Reference. An ordered collection of checks, that can have conditions added to them. The Suite enables displaying a concluding report for all of the Checks that ran.

Artifical World simulator, it simulate virtual 3D world and execute IA programs. It have API for programming IAs in C++. it use Irrlicht as 3D engine.

The experimental source code for the paper, "A Novel Recommendation Approach Based on Chronological Cohesive Units in Content Consuming"

D-Cog (Declarative-Cognition) is a Java based framework for training software components (reusable, object-oriented, interface-driven components). Instead of programmed, software components are trained by example to get the expected results.

The aim of the project is to provide a testing tool that would reduce the cost associated with the regression testing process. The tool provides test case subset selection so that the user need not run the redundant test cases.

Siafu simulates individual agents and their context, from home to city-wide scenarios. As a developer, you use the API to write your simulation for the purposes of data-set generation, test or visualization, optionally hooking it to your own application.

The TDD MAS Toolkit provides a set of tools to perform Test Driven Development of MAS based on Jade. The toolkit allows developers to set up simulation based and test case scenario based testing, providing powerful insights of the MAS under construction and assuring that the interation protocols and agent interaction in general are been enacted as expected.

Here we present the lines of code for creating a taylor plot with python to display several machine learning models. We show the solution for displaying 10 models, but the list and number can be changed simply by modifying the sample list.