# tsiege/Tech-Interview-Cheat-Sheet

Studying for a tech interview sucks. Here's an open source cheat sheet to help

Repository: https://github.com/tsiege/Tech-Interview-Cheat-Sheet
Canonical: https://ross.abutalabs.com/products/tech-interview-cheat-sheet
Language: TypeScript
License: MIT
License Family: permissive
Last push: 2024-07-01T06:37:55+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2557, "days_push": 793, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 4679, forks 980 (observed 2026-08-28T04:08:56.846950+00:00)

## What it is
An open-source cheat sheet summarizing core computer science topics like asymptotic notation, data structures, and algorithms for tech interview preparation. It includes reference notes plus hands-on code challenges covering the material.

## Use cases
- prepare for a technical coding interview
- review big-o notation and algorithm complexity
- study common data structures like hash tables and binary trees
- refresh sorting and search algorithms before an interview
- practice coding challenges on interview topics

## When to choose
- you need a quick refresher on CS fundamentals before an interview
- you want a concise summary of data structures and algorithms in one place
- you prefer community-reviewed study notes with practice challenges

## When to avoid
- you need in-depth textbook coverage of algorithms
- you want system design or behavioral interview prep
- you need an interactive learning platform with graded exercises

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: documentation, developer-tools
- domain: education, tutorials
- platform: cross-platform
- tags: cheat-sheet, interview-preparation, data-structures, big-o-notation, computer-science, algorithms

## Member repositories
- tsiege/Tech-Interview-Cheat-Sheet (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:56.846950+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 2026-08-29T18:19:20.638659+00:00, confidence not recorded.
  - readme: https://github.com/tsiege/Tech-Interview-Cheat-Sheet (fetched 2026-08-28T04:08:56.846950+00:00, sha 047ca2e2963c)
- Data as of 2026-08-30T08:39:29.467469+00:00.