FOSSEE Summer Fellowship 2018 FOSSEE Signal Processing/DSP Toolbox Screening Round 1

Thank you for your interest in FOSSEE Toolbox project. We would like to assess your coding/testing skills. Please read the details mentioned below.

Phase 1 Assignment

Develop Scilab examples to test any 5 functions available in FOSSEE Signal Processing/DSP toolbox.

Develop examples for any 5 functions available in the /toolbox/macros folder. All functions will have .sci extension.

Examples of each function are available in the help documentation for each function. The functions have been coded to match Matlab functions in syntax, input, and output. There are few exceptions to this rule.You may refer to these examples to understand how to develop your own examples. We expect applicants to show originality and develop examples that test the function. Submitting examples by changing few coefficients or degree of equations of existing examples will not score highly. You may refer to IEEE papers and textbooks to develop examples.

Software setup

  1. Install Ubuntu 14.04. We cannot provide technical support for the toolbox on any other OS. Please do not mail us asking if you can install any other OS- the answer is no.
  2. Install Scilab 5.5.0/5.5.2. The toolbox will not install on any other Scilab version.
  3. Install FOSSEE SP/DSP Toolbox- https://scilab.in/fossee-scilab-toolbox/signal-processing-toolbox-instal...

Procedure to attempt Phase 1:

  1. Develop examples for any 5 functions available in /toolbox/macros folder. There is no upper limit to the number of examples you may submit. More number of unique examples will score higher than few number of similar examples for the same function. Each example code should be inside a separate .sce file. Example files should be named as example1.sce, example2.sce etc.
  2. Add comments in the code that explain what is being tested, what the input arguments are and if the example would generate any error. Lucid comments that provide information about the example code will score highly.
  3. Copy and paste the output in each example file for every function. You should include the output that is seen on the Scilab console. If the toolbox/Scilab crashes include that as a comment. If an error is seen, copy and paste the error. Developing examples that generate errors will earn brownie points. Also mention if your example generates plots, if any.
  4. Cite your references. On no account will plagiarism be tolerated. Such submissions will be rejected summarily.
  5. Create a README file for each function that has clear instructions about how to use the corresponding example codes that you write. The README file should also include the toolbox installation instructions and ofcourse a set of rich instructions that explains the content inside each of the submitted code. If the README file fails to provide all instructions in order to be able to use your submitted code, you will lose points.

Preparing for Code Submission:

  1. The examples developed for each function and its respective README should be kept together in a folder. For example, if you code 2 examples for a function “func”, create a folder named as “func”. Then put all examples that are related to “func”, inside this folder. Also put its respective README inside the “func” folder. Repeat the same for other functions. If you code examples for 5 functions you should have 5 folders. Each folder should be named after the function name. Each folder should contain its respective example files and README file.
  2. Zip the folders separately. For example, if you have 5 folders, you should have 5 respective zip files. Avoid 7zip, tar, rar etc. Use only Zip file format to compress a folder.