Problem intelligence
Integer to Roman
MEDIUM · 30 companies · Hash Table · Math · String
Interview priority
73
high
Target overlap
0/0
Recency
100
Trend
36
Frequency
100
Company observations
Adobeolder79.8
Adobeall74.7
Agodaolder52.1
Agodaall49.2
Amazon90d28.9
Amazon6m39
Amazonolder53.2
Amazonall52.4
AMDolder75
AMDall74.7
BlackRockolder44.3
BlackRockall43.4
Bloomberg90d36.8
Bloomberg6m34.2
Bloombergolder51.7
Bloombergall51
Booking.comolder83.4
Booking.comall65.2
Docusignolder81.1
Docusignall74.1
DoorDasholder34.7
DoorDashall34.2
Geicoolder59.4
Geicoall58.9
Goldman Sachsolder22.5
Goldman Sachsall20.4
Google30d29
Google90d35.9
Google6m40.1
Googleolder43.6
Googleall44.6
IBM90d100
IBM6m77.2
IBMolder94.3
IBMall91.3
Infosys6m56.2
Infosysall40.2
LinkedInolder35.1
LinkedInall32.1
Meta30d53.8
Meta90d49.8
Meta6m38.7
Metaolder37
Metaall39.2
Microsoft90d48.3
Microsoft6m46.2
Microsoftolder52.4
Microsoftall52.8
Oracleolder44.8
Oracleall43.7
Palo Alto Networksolder55.4
Palo Alto Networksall59.6
Salesforceolder32.1
Salesforceall27.7
Swiggyolder74.1
Swiggyall69.2
tcs90d90.3
tcs6m86.5
tcsolder26.8
tcsall61.5
TikTokall24.6
UiPatholder100
UiPathall73.7
Verkadaolder86
Verkadaall76.9
Walmart Labsolder62.4
Walmart Labsall60.1
Warnermediaall69
Wixolder100
Wixall90.4
Xall93.7
Zohoolder41.3
Zohoall38.9
Why this score
high frequency100
recent activity100
unsolved100
Local progress
unseen