Weighted Random messages

We have a set of N (1 ≤ N ≤ 100) different versions of advertising messages that we would like to randomly select and send out to the public. Each version has a weight w[i] (0 ≤ w[i] ≤ 109) of being selected.

Implement a function to take an array w[] as input and return a message version i (0 ≤ i ≤ N-1) that satisfies the weighted random condition.

* Add up all the weights for all the items
* Pick a random number from 1 to sum of weights
* Iterate over the items, subtracting their weight from your random number until you get the item where the random number is less than that item's weight.

I applied the test techniques such as boundary test and partition test.

• Positive Cases of the inputed versions' value
  • Input the weight array by 1 version.
  • Input the weight array by 100 versions
  • Input the weight array by 50 version.
• Positive Cases of the inputed weight value
  • Input the weight value is 1.
  • Input the weight value is 1000000000.
  • Input the weight value is 500000000.
• Negative Cases of the inputed versions' value
  • Input the weight array by 0 version.
  • Input the weight array by 101 versions
  • Input the weight array by 150 version.
• Negative Cases of the inputed weight value
  • Input the weight value is -1.
  • Input the weight value is 1000000001.
  • Input the weight value is 1000000050.

• Input a array of weights with many cases of the number of selected message. Ex:
  1. Weight array: new int[]{50, 30, 60}
     • Selected version number: 1400 messages,
     • Selected version number: 280 messages,
  2. Weight array: ew int[]{30, 10, 20, 60}
     • Selected version number: 360 messages,
• Count the random number of each version following the specified weight.
• The randomness is relative so the result of randomness have to compare with the deviation, and I set the deviation is +-10% for each selected version.

1. https://www.rubyguides.com/2016/05/weighted-random-numbers/
2. https://medium.com/@peterkellyonline/weighted-random-selection-3ff222917eb6
3. https://stackoverflow.com/questions/1761626/weighted-random-numbers