Skip to contentSkip to footer

Software Development Engineer In Test Interview Questions

Salaries
Interviews

5,157 software development engineer in test interview questions shared by candidates

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 ->
avatar

Software Development Engineer In Test (SDET)

Interviewed at RingCentral

3.5★
Oct 14, 2021

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 ->

Viewing 621 - 630 interview questions

Glassdoor has 5,157 interview questions and reports from Software development engineer in test interviews. Prepare for your interview. Get hired. Love your job.