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                                                            Cracking the coding interview pdf 7t
    ✅ C++ Solutions ✅ Python Solutions ✅ Automated Unit Test ✅ Active Development ✅ Multiplatform Support: Mac, Linux and Windows This repo contains C++ and Python solutions for Gayle Laakmann McDowell's Cracking the Coding Interview 6th Edition. Of course, there are other GitHub repository with solutions for
    this book. But how do you know their code is correct? If he's not tested, then you don't! In this project, each C++ solution has unit testing using the C++ Capture Framework, and each Python solution has unit testing using the Python unittest framework. We perform the correctness of the test automatically using
    continuous integration servers, ensuring that solutions are made of living code that is executed and tested on each individual commit. To my knowledge, this is the only repository of Internet solutions with this level of rigor testing: >90% automated testing coverage means that you can refer and contribute solutions with
    confidence. C++ content table Solutions: C++ Total: 81 complete solutions. Python Solutions: Python Total: 58 complete solutions. Grand Total: 139 complete unique solutions. Building: Mac: Using Mac requires the installation of the responsible for the Homebrew and Pip package that is made for you in the Makefile: git
    clone cd ctci make-config-mac Ubuntu: git clone recommend developing this project using the Windows Subsystem for Linux (WSL) function of Windows 10 and then following the Ubuntu construction and testing instructions within WSL. This recommendation is due to the use of Ubuntu, CMake, and makefiles based on
    configuration and execution systems on servers that automatically test code changes. For more information on Windows development, see the Appendix section at the end of this page. Testing: Testing is the most important part of this project: Only unit tests define the problem to be solved. In the root directory, run the
    following tests in Python and C++: do test make test is the command I use most during the development of this project. My workflow follows: I read a problem and codify the problem by implementing its unit tests. I run the test to see where the project fails to meet the test of the unit. I add to the implementation of the
    problem solution until you can do tests. Optional: Generating a test coverage report % Locally (Pitone only): This will show exactly what lines are not covered by tests in each Python source file: pip install make test_coverage Contributing The aim of this project is to write a Python and C++ solution tested for every issue
    in the sixth edition of the textbook. I definitely need help, so public relations are welcome. There is a lot to do because each solution needs its own small set of data and infrastructure to be tested. Here are some ways to help you: Fix bugsSolve or improve problem solutions in both languages (see the progress made in
    the content table). Add multiple unit tests to increase test coverage %. Implement automatic measurement of the C++ test cover using gcov. Integration of automatic coverage of % reporting tests for Python and C++ through Coveralls. Adding prose solution descriptions for problems that do not have them. If you have any
    contributions, please make a PR to the main branch. Feel free to send me a message for clarification on any of the items listed above. Appendix: Windows Development On my Windows computer, it develops me using native CLion running in Windows and testing the code using testing in a WSL terminal window. For
    users who do not want to use WSL, I developed the compilation and testing methodology below: Building The project can only be developed on Windows without WSL using Visual Studio 2017. First clone of the code: git clone cd ctci git submodule update --init So, install Python3 and numpy using the method of choice. I
    prefer to install Python3 and pip3 from the official site then install numpy via pip: pip install numpy Then, open the project in Visual Studio 2017 that has the CMake support. I found that the best workflow is to use Visual Studio to change the code and use the debug feature. Before you build the code, you need to follow
    these instructions to tell Visual Studio to download PDBs you need. In addition,article describes Visual Studio CMake support in more detail if you are interested. A CMakeSettings.json file in the root project directory sets the location of the Visual Studio building folder to be within the main project folder. Run the tests and
    see their output is better done by a PowerShell window as VisualStudio in CMake mode does not allow the output of the test console. exe and test. py files to remain visible even when pressing CTRL + F5 as described in this post that applies to the "normal" Visual Studio usage. I'm monitoring the king's situation: Visual
    Studio, and when I find better solutions I will implement or publish them. If you know anything better, contact me. Meanwhile, from the root directory of the project, you can run the Python tests using ... python test. py ... and you can run C++ tests using ... .\build\x64-Debug\tests.exe .\build\x64-Debug\tests.exe cracking
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