# 15kingben/googleprep architecture

> Architecture diagram of the GitHub repository 15kingben/googleprep, generated by GitDiagram from its file tree, README and a sample of source files (last updated 2026-06-21). It is an AI-made overview: check details against the source.

- Interactive diagram: https://gitdiagram.com/15kingben/googleprep
- Repository: https://github.com/15kingben/googleprep

## Overview

This repository is not an application codebase; it is a single-page learning and interview-prep playbook. The entire “architecture” lives in `README.md`, so the main boundaries are organizational rather than technical.

1. **Primary purpose**
   - The repo is a curated study guide for algorithm practice, competitive programming, and technical interviews.
   - It is meant to be consumed by a human, not executed by software.

2. **Content hierarchy**
   - The README is organized into three major layers:
     - learning resources and concept recommendations
     - contest participation guidance
     - interview preparation scripts and practice questions
   - This makes it a knowledge base with a progression from concept acquisition to application.

3. **Concept curriculum subsystem**
   - The “Algorithms Live!” section is the core syllabus.
   - It highlights algorithm families such as Fenwick trees, segment trees, graph connectivity, SCCs, topological sort, DP variants, max flow, binary lifting LCA, and geometric sweeps.
   - These topics form the conceptual backbone of the repo.

4. **Practice-to-reinforcement loop**
   - The README strongly emphasizes solving problems immediately after learning a concept.
   - The intended flow is: watch an episode, solve the related problem independently, then skim the coding technique afterward.
   - This creates a tight feedback loop between theory and implementation practice.

5. **Contest learning subsystem**
   - The “Learning From Contests” section defines a second major input stream: contest failures.
   - The repo recommends reviewing post-contest solutions, extracting unfamiliar techniques, and converting mistakes into future study topics.
   - This is the repo’s main mechanism for continuously expanding the concept catalog.

6. **Contest cadence and external platforms**
   - The repo names specific competitive programming platforms and schedules: LeetCode, Codeforces, CodeChef, Google Code Jam, and clist.by.
   - These are not integrated services in a software sense, but they are the external execution environments where the study plan is applied.

7. **Interview workflow subsystem**
   - The “Interview Script” section is a procedural boundary for problem solving.
   - It prescribes a sequence: clarify requirements, propose brute force, test on a small case, optimize, code, and enumerate edge cases.
   - This is effectively the repo’s operational model for live technical interviews.

8. **Problem catalog**
   - The “Practice Interview” section is a handpicked list of representative problems.
   - The problems are grouped implicitly by technique: graph traversal, union-find/BFS/DFS, topological sorting, reverse reasoning, DP, bitmask DP, monotonic structures, greedy scheduling, and binary search.
   - This section acts like a test suite for validating mastery of the learning objectives.

9. **Behavioral and meta-skills boundary**
   - The README separates algorithmic skill from communication skill.
   - It explicitly calls out articulation, avoiding dead air, and asking interviewer questions as part of the overall system.
   - In architecture terms, this is the “human interface” layer of the repo.

10. **External knowledge dependencies**
   - The repo depends on external content rather than local code: YouTube episodes, blog posts, and LeetCode/contest problem statements.
   - The repository itself contains no implementation artifacts, build tooling, or runtime dependencies.

11. **Information flow**
   - The dominant flow is: curated concept → practice problem → contest experience → retrospective learning → deeper concept mastery.
   - A second flow is interview-oriented: concept study → interview script rehearsal → selected practice questions → communication practice.

12. **Overall structure for diagramming**
   - If you were drawing an architecture diagram, represent this repo as a documentation-driven learning system with:
     - a concept library
     - an exercise/problem bank
     - a contest feedback loop
     - an interview process playbook
     - external learning and evaluation platforms
   - There are no internal code modules, services, or data stores beyond the README content.

Main entry points: [`README.md`](https://github.com/15kingben/googleprep/blob/master/README.md) (Practice Interview)

## Diagram (Mermaid)

```mermaid
flowchart TD

subgraph group_g1["Learning Flow"]
  node_n2["Study Guide<br/>learning overview<br/>[README.md]"]
  node_n3["Algorithms Live<br/>concept syllabus<br/>[README.md]"]
  node_n4["Problem Practice<br/>reinforcement loop<br/>[README.md]"]
  node_n5["Concept Catalog<br/>topic inventory<br/>[README.md]"]
  node_n15(("Mastery Loop<br/>learning flow<br/>[README.md]"))
end

subgraph group_g2["Contest Loop"]
  node_n6["Contest Review<br/>retrospective loop<br/>[README.md]"]
end

subgraph group_g3["Interview Prep"]
  node_n8["Interview Script<br/>procedure<br/>[README.md]"]
  node_n9["Practice Interview<br/>problem bank<br/>[README.md]"]
  node_n10["Communication<br/>soft skills<br/>[README.md]"]
  node_n11["Graph Problems<br/>graph practice<br/>[README.md]"]
  node_n12["DP Problems<br/>dp practice<br/>[README.md]"]
  node_n13["Greedy/Search<br/>technique practice<br/>[README.md]"]
end

subgraph group_g4["External Sources"]
  node_n7["Contest Platforms<br/>external venues"]
  node_n14["External Content<br/>knowledge sources"]
end

node_n1["README<br/>playbook doc<br/>[README.md]"]

node_n1 -->|"organizes"| node_n2
node_n2 -->|"defines"| node_n3
node_n3 -->|"covers"| node_n5
node_n3 -->|"leads to"| node_n4
node_n4 -->|"reinforces"| node_n15
node_n6 -->|"adds topics"| node_n5
node_n7 -->|"feeds"| node_n6
node_n14 -->|"supports"| node_n3
node_n14 -->|"informs"| node_n6
node_n8 -->|"applies to"| node_n9
node_n8 -->|"includes"| node_n10
node_n9 -->|"contains"| node_n11
node_n9 -->|"contains"| node_n12
node_n9 -->|"contains"| node_n13
node_n15 -->|"extends via"| node_n6
node_n15 -->|"branches to"| node_n8

click node_n1 "https://github.com/15kingben/googleprep/blob/master/README.md"
click node_n2 "https://github.com/15kingben/googleprep/blob/master/README.md"
click node_n3 "https://github.com/15kingben/googleprep/blob/master/README.md"
click node_n4 "https://github.com/15kingben/googleprep/blob/master/README.md"
click node_n5 "https://github.com/15kingben/googleprep/blob/master/README.md"
click node_n6 "https://github.com/15kingben/googleprep/blob/master/README.md"
click node_n8 "https://github.com/15kingben/googleprep/blob/master/README.md"
click node_n9 "https://github.com/15kingben/googleprep/blob/master/README.md"
click node_n10 "https://github.com/15kingben/googleprep/blob/master/README.md"
click node_n11 "https://github.com/15kingben/googleprep/blob/master/README.md"
click node_n12 "https://github.com/15kingben/googleprep/blob/master/README.md"
click node_n13 "https://github.com/15kingben/googleprep/blob/master/README.md"
click node_n15 "https://github.com/15kingben/googleprep/blob/master/README.md"

classDef toneNeutral fill:#f8fafc,stroke:#334155,stroke-width:1.5px,color:#0f172a
classDef toneBlue fill:#dbeafe,stroke:#2563eb,stroke-width:1.5px,color:#172554
classDef toneAmber fill:#fef3c7,stroke:#d97706,stroke-width:1.5px,color:#78350f
classDef toneMint fill:#dcfce7,stroke:#16a34a,stroke-width:1.5px,color:#14532d
classDef toneRose fill:#ffe4e6,stroke:#e11d48,stroke-width:1.5px,color:#881337
classDef toneIndigo fill:#e0e7ff,stroke:#4f46e5,stroke-width:1.5px,color:#312e81
classDef toneTeal fill:#ccfbf1,stroke:#0f766e,stroke-width:1.5px,color:#134e4a
class node_n2,node_n3,node_n4,node_n5,node_n15 toneBlue
class node_n6 toneAmber
class node_n8,node_n9,node_n10,node_n11,node_n12,node_n13 toneMint
class node_n7,node_n14 toneRose
class node_n1 toneNeutral
```

## Components

### Learning Flow

Curated concept study and practice reinforcement

- [Study Guide](https://github.com/15kingben/googleprep/blob/master/README.md): learning overview · High-level organization of the repo as a progression from concept acquisition to application. · `README.md`
- [Algorithms Live](https://github.com/15kingben/googleprep/blob/master/README.md): concept syllabus · Core curriculum of algorithm families and coding techniques. · `README.md`
- [Problem Practice](https://github.com/15kingben/googleprep/blob/master/README.md): reinforcement loop · Solve a related problem immediately after learning a concept, then review the technique. · `README.md`
- [Concept Catalog](https://github.com/15kingben/googleprep/blob/master/README.md): topic inventory · Fenwick trees, segment trees, graph connectivity, SCC, topological sort, DP, max flow, LCA, sweeps. · `README.md`
- [Mastery Loop](https://github.com/15kingben/googleprep/blob/master/README.md): learning flow · Concept study feeds practice, contest experience, and then deeper concept mastery. · `README.md`

### Contest Loop

Using contests as a feedback source for new topics

- [Contest Review](https://github.com/15kingben/googleprep/blob/master/README.md): retrospective loop · Learn from failures by reviewing post-contest solutions and extracting unfamiliar techniques. · `README.md`

### Interview Prep

Live interview process and practice set

- [Interview Script](https://github.com/15kingben/googleprep/blob/master/README.md): procedure · Step-by-step interview workflow: clarify, brute force, test, optimize, code, and check edge cases. · `README.md`
- [Practice Interview](https://github.com/15kingben/googleprep/blob/master/README.md): problem bank · Representative interview problems grouped by technique and used to rehearse mastery. · `README.md`
- [Communication](https://github.com/15kingben/googleprep/blob/master/README.md): soft skills · Articulation, avoiding dead air, and asking good questions during interviews. · `README.md`
- [Graph Problems](https://github.com/15kingben/googleprep/blob/master/README.md): graph practice · Traversal and connectivity problems used to reinforce graph reasoning. · `README.md`
- [DP Problems](https://github.com/15kingben/googleprep/blob/master/README.md): dp practice · Dynamic programming and bitmask DP practice cases. · `README.md`
- [Greedy/Search](https://github.com/15kingben/googleprep/blob/master/README.md): technique practice · Monotonic structures, greedy scheduling, reverse reasoning, and binary search. · `README.md`

### External Sources

Outside platforms and reference content

- **Contest Platforms**: external venues · LeetCode, Codeforces, CodeChef, Google Code Jam, and clist.by as practice and evaluation environments.
- **External Content**: knowledge sources · YouTube episodes, blog posts, and problem statements used as the repository's inputs.

### Other components

- [README](https://github.com/15kingben/googleprep/blob/master/README.md): playbook doc · Single-page study guide that organizes the repo's learning and interview workflow. · `README.md`

## Connections

- README → Study Guide: organizes · README acts as the entry point for the learning guide.
- Study Guide → Algorithms Live: defines · The study guide centers on the Algorithms Live syllabus.
- Algorithms Live → Concept Catalog: covers · The syllabus enumerates the key algorithm families.
- Algorithms Live → Problem Practice: leads to · Each concept is intended to be followed by immediate problem solving.
- Problem Practice → Mastery Loop: reinforces · Practice after learning strengthens mastery.
- Contest Review → Concept Catalog: adds topics · Contest retrospectives expand the concept catalog with new techniques.
- Contest Platforms → Contest Review: feeds · Contest platforms provide the environment for learning from failures.
- External Content → Algorithms Live: supports · External learning content supplies the concept curriculum.
- External Content → Contest Review: informs · External editorials and writeups are reviewed after contests.
- Interview Script → Practice Interview: applies to · The interview script is practiced through selected problems.
- Interview Script → Communication: includes · The playbook explicitly treats communication as part of the workflow.
- Practice Interview → Graph Problems: contains · A portion of the problem bank focuses on graph techniques.
- Practice Interview → DP Problems: contains · Another portion focuses on DP-oriented questions.
- Practice Interview → Greedy/Search: contains · The remaining problems emphasize greedy and search-based techniques.
- Mastery Loop → Contest Review: extends via · Contest experience loops back into deeper study.
- Mastery Loop → Interview Script: branches to · The same study base also supports interview rehearsal.