# Olshansk/interview

Everything you need to prepare for your technical interview

Repository: https://github.com/Olshansk/interview
Canonical: https://ross.abutalabs.com/products/olshansk-interview
License: WTFPL
License Family: permissive
Topics: interview, interview-questions, google-interview, list, guide
Last push: 2024-12-25T19:55:23+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 4599, "days_push": 616, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 18360, forks 3671 (observed 2026-08-28T04:11:26.595271+00:00)

## What it is
A curated list of resources for preparing for technical interviews, covering algorithms, coding practice, system design, and language-specific guides. It aggregates books, courses, sites, videos, and mock interview platforms.

## Use cases
- prepare for a technical interview
- find coding practice sites like leetcode
- study algorithms for interviews
- learn system design for interviews
- find mock interview platforms
- get interview prep resources for a specific language

## When to choose
- you want a single curated index of interview prep materials
- you need links to books, courses, and practice sites across many topics
- you are preparing for interviews at companies like Google

## When to avoid
- you want interactive practice rather than a list of links
- you need structured lessons or a course with progression
- you expect the linked content itself to be maintained

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: documentation, developer-tools
- domain: education, tutorials, developer-tools, awesome-lists
- platform: cross-platform
- tags: interview-preparation, awesome-list, coding-interview, system-design, career, algorithms

## Member repositories
- Olshansk/interview (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:26.595271+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 2026-08-29T17:02:04.205474+00:00, confidence not recorded.
  - readme: https://github.com/Olshansk/interview (fetched 2026-08-28T04:11:26.595271+00:00, sha d75904cbf9c8)
- Data as of 2026-08-30T08:39:29.467469+00:00.