GithubHelp home page GithubHelp logo

minha12 / decide Goto Github PK

View Code? Open in Web Editor NEW

This project forked from krooken/decide

0.0 1.0 0.0 147 KB

Launch Interceptor Program (exercise in software engineering)

License: GNU General Public License v3.0

Python 99.57% Batchfile 0.21% Shell 0.21%

decide's Introduction

DECIDE(); Launch Interceptor Program (exercise in software engineering)

DECIDE() is a part of a hypothetical anti-ballistic missile system. DECIDE() will generate a boolean signal which determines whether an interceptor should be launched based upon input radar tracking information. This radar tracking information is available at the instant the function is called.

DECIDE() determines which combination of the several possible Launch Interceptor Conditions (LIC’s) are relevant to the immediate situation. The interceptor launch button is normally considered locked; only if all relevant combinations of launch conditions are met will the launchunlock signal be issued.

DECIDE() determines whether each of fifteen LIC’s is true for an input set of up to 100 planar data points representing radar echoes. The fifteen elements of a Conditions Met Vector (CMV) will be assigned boolean values true or false; each element of the CMV corresponds to one LIC’s condition.

The input Logical Connector Matrix (LCM), defines which individual LIC’s must be considered jointly in some way. The LCM is a 15x15 symmetric matrix with elements valued ANDD, ORR, or NOTUSED. The combination of LCM and CMV is stored in the Preliminary Unlocking Matrix (PUM), a 15x15 symmetric matrix.

Another input, the Preliminary Unlocking Vector (PUV) represents which LIC actually matters in this particular launch determination. Each element of the UV indicates how to combine the PUM values to form the corresponding element of the Final Unlocking Vector (FUV), a 15-element vector. If, and only if, all the values in the FUV are true, should the launch-unlock signal be generated.

Testing

The python unittest framework is used to test the code. For every function or method found in the decide folder, a corresponding test case file is found in the test folder. Each test case contains test methods that test different aspects of the function/method under test. All tests can be run by running either of

run_tests.sh

and

run_tests.bat

Alternatively, run python -m unittest discover directly in a terminal from the root folder of the Git repository.

Project guidelines

All commits shall have a short and concise summary, preferably less than 70 characters. If additional explanation is needed, leave a blank line between the summary and the detailed explanations. Try to explain why a change was made, if not really obvious. (The 'what' and 'how' is less important since it usually is included in the commit diff.)

Prefix the commit summary with ADD:, FIX:, DOC:, or REFACTOR: if it is a new feature, bug fix, documentation, or refactor, respectively. Try to separate the commits into parts such that the prefix is consistent with the commit contents.

decide's People

Contributors

krooken avatar

Watchers

 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.