HackerRank-
1. write the code to find how many words are present in the string(Integer won't be considered as words) e.g "You 12 are a good 13 boy" has 5 words.
2. If the given string of brackets is balanced.
F2F: 2 Questions:
Ques1.
R1 = [['cc_01',"pass"],['cc_02',"pass"],['cc_03',"fail"],['cc_04',"pass"],['cc_05',"pass"],['cc_06',"pass"],['cc_07',"fail"],['cc_08',"pass"],['cc_09',"pass"]]
R2 = [['cc_01',"pass"],['cc_02',"pass"],['cc_03',"pass"],['cc_04',"fail"],['cc_05',"pass"],['cc_06',"fail"],['cc_07',"fail"],['cc_08',"pass"],['cc_09',"pass"]]
R1 and R2 are regressions run on build 200 and 204 respectively.
Problem: Programatically find what are the new failures introduced in build 204, given same test cases are run in both regressions.
Ques2:
There is a music streaming app, where a user can listen to his/her choice of music. Given each song can be tagged with following metadata
{"genere","musician","singer","era","album"}
e.g. {"hiphip","xyz","abc","90","indipop"}
Now a "new feature" is introduced in the app, where depending on a user's habit of listening it recommends 10 songs to the user. This feature is AI-enabled.
What is your strategy to test this feature?
Given are the APIs
playSong(SongID,{metadata}) ->
getMetadata(SongID) --> gives above metadata ->
getStats(SongID, meta, userId); -> 10 played songs ->
newFeature(userId)--> List of 10 songs with songsId with metadata ->
