# liquidslr/leetcode-company-wise-problems

Lists of company wise questions. Every csv file in the companies directory corresponds to a list of questions on leetcode for a specific company based on the leetcode company tags. Updated as of 20 June, 2025

Repository: https://github.com/liquidslr/leetcode-company-wise-problems
Canonical: https://ross.abutalabs.com/products/leetcode-company-wise-problems
License Family: other
Topics: google-interview, interview, online-assessment, meta-interview, uber-interview, amazon-interview
Last push: 2026-08-16T22:18:45+00:00

## Health v2 (maintenance only)
Score: 65/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 98, release rhythm 35, longevity 43
- inputs: {"age_days": 610, "days_push": 17, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 29273, forks 5717 (observed 2026-08-28T04:11:53.235106+00:00)

## What it is
A curated dataset of LeetCode coding questions organized by company (Google, Meta, Amazon, Uber, etc.) in CSV format, based on LeetCode company tags. Each company folder includes questions from the past 30, 60, and 90 days plus all-time lists.

## Use cases
- prepare for a coding interview at a specific company
- find the most frequently asked LeetCode questions for Google or Amazon
- practice recent interview questions from the last 30 or 90 days
- export a company's question list as CSV for tracking progress
- identify common question patterns across tech company interviews

## When to choose
- you are interviewing at a specific tech company and want its tagged question list
- you want a static, regularly updated CSV dataset of company-wise LeetCode problems
- you prefer offline or spreadsheet-based interview prep tracking

## When to avoid
- you need an interactive practice platform with code execution and judging
- you want solutions or explanations rather than just problem lists
- you need guaranteed up-to-date data, since updates depend on the maintainer

## Facets
- artifact type: dataset
- maturity: active
- function: data-science
- domain: education, developer-tools
- platform: cross-platform
- tags: leetcode, interview-preparation, csv, coding-interview, company-wise-problems

## Member repositories
- liquidslr/leetcode-company-wise-problems (main) score 65

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:53.235106+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T16:53:04.029223+00:00, confidence not recorded.
  - readme: https://github.com/liquidslr/leetcode-company-wise-problems (fetched 2026-08-28T04:11:53.235106+00:00, sha 07b6a493a479)
- Data as of 2026-08-30T08:39:29.467469+00:00.