# liquidslr/interview-company-wise-problems architecture
> Architecture diagram of the GitHub repository liquidslr/interview-company-wise-problems, 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/liquidslr/interview-company-wise-problems
- Repository: https://github.com/liquidslr/interview-company-wise-problems
## Overview
1. This repository is a curated data catalog, not an application. Its primary purpose is to store LeetCode company-wise question lists as CSV files, organized for direct human browsing or downstream ingestion.
2. The top-level boundary is the company folder. Each folder represents one employer or org (for example, Amazon, Google, Stripe, etc.), and folders are intentionally independent so consumers can pull just the companies they care about.
3. Inside every company folder is the same five-file pattern:
- 1. Thirty Days.csv
- 2. Three Months.csv
- 3. Six Months.csv
- 4. More Than Six Months.csv
- 5. All.csv
4. These files represent time-window slices of the same underlying problem set. The first four are recency-based views, while All.csv is the aggregate or full list for that company.
5. The repeated file structure is the key architectural idea: each company is a self-contained dataset partitioned by recency, which makes the repository easy to scan, compare, and update without needing application logic.
6. The README establishes the content contract: the lists are “curated,” grouped by company, and updated as of 1 June 2025. That date is important because it implies the CSVs are snapshots of a maintained dataset rather than live-synced feeds.
7. There is no backend, UI, API layer, or orchestration code in this repo. The data flow is therefore simple: curated question lists are produced externally, then committed into the corresponding company/time-window CSV files.
8. The main consumers are likely readers, interview-prep workflows, spreadsheet tools, or scripts that parse CSVs. Because the repository is file-based only, the filesystem itself is the query surface and distribution mechanism.
9. The schema boundary is implied by file naming rather than code. Any architecture diagram should show a single standardized dataset format per company, with multiple temporal views under the same namespace.
10. The repo also references an external sibling resource, “system-design-notes,” but that is only linked from the README and is not part of this repository’s internal architecture.
11. In diagram terms, the important model is: one curated content source feeding many company partitions, each partition exposing five time-bucketed CSV views. There are no additional service tiers or runtime dependencies to include.
Main entry points: [`Amazon`](https://github.com/liquidslr/interview-company-wise-problems/tree/main/Amazon) (Amazon), [`Readme.md`](https://github.com/liquidslr/interview-company-wise-problems/blob/main/Readme.md) (README), [`Google`](https://github.com/liquidslr/interview-company-wise-problems/tree/main/Google) (Google), [`Stripe`](https://github.com/liquidslr/interview-company-wise-problems/tree/main/Stripe) (Stripe)
## Diagram (Mermaid)
```mermaid
flowchart TD
subgraph group_metadata["Metadata"]
node_readme["README
contract doc
[Readme.md]"]
node_snapshot_date(("1 Jun 2025
snapshot date
[Readme.md]"))
node_external_notes["System notes
external link
[Readme.md]"]
node_curation_source["Curated lists
content source"]
end
subgraph group_dataset["Dataset Layout"]
node_company_namespace["Company folders
dataset boundary"]
node_amazon_partition["Amazon
company partition"]
node_google_partition["Google
company partition"]
node_stripe_partition["Stripe
company partition"]
node_thirty_days["30 days
recency slice"]
node_three_months["3 months
recency slice"]
node_six_months["6 months
recency slice"]
node_more_than_six[">6 months
recency slice"]
node_all_slice["All
aggregate slice"]
node_csv_schema["CSV format
file format"]
end
subgraph group_consumers["Consumers"]
node_human_browsing(("Human browsing
consumer"))
node_spreadsheet_tools(("Spreadsheets
consumer"))
node_scripts_ingestion(("CSV scripts
consumer"))
end
node_readme -->|"defines"| node_curation_source
node_readme -->|"anchors"| node_snapshot_date
node_readme -->|"organizes"| node_company_namespace
node_readme -.->|"references"| node_external_notes
node_curation_source -->|"feeds"| node_company_namespace
node_company_namespace -->|"example"| node_amazon_partition
node_company_namespace -->|"example"| node_google_partition
node_company_namespace -->|"example"| node_stripe_partition
node_amazon_partition -->|"contains"| node_thirty_days
node_amazon_partition -->|"contains"| node_three_months
node_amazon_partition -->|"contains"| node_six_months
node_amazon_partition -->|"contains"| node_more_than_six
node_amazon_partition -->|"contains"| node_all_slice
node_google_partition -->|"contains"| node_thirty_days
node_stripe_partition -->|"contains"| node_all_slice
node_csv_schema -->|"shapes"| node_thirty_days
node_csv_schema -->|"shapes"| node_all_slice
node_company_namespace -->|"standardizes"| node_csv_schema
node_thirty_days -->|"read by"| node_human_browsing
node_all_slice -->|"read by"| node_spreadsheet_tools
node_csv_schema -->|"parsed by"| node_scripts_ingestion
click node_readme "https://github.com/liquidslr/interview-company-wise-problems/blob/main/Readme.md"
click node_snapshot_date "https://github.com/liquidslr/interview-company-wise-problems/blob/main/Readme.md"
click node_external_notes "https://github.com/liquidslr/interview-company-wise-problems/blob/main/Readme.md"
click node_amazon_partition "https://github.com/liquidslr/interview-company-wise-problems/tree/main/Amazon"
click node_google_partition "https://github.com/liquidslr/interview-company-wise-problems/tree/main/Google"
click node_stripe_partition "https://github.com/liquidslr/interview-company-wise-problems/tree/main/Stripe"
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_readme,node_snapshot_date,node_external_notes,node_curation_source toneBlue
class node_company_namespace,node_amazon_partition,node_google_partition,node_stripe_partition,node_thirty_days,node_three_months,node_six_months,node_more_than_six,node_all_slice,node_csv_schema toneAmber
class node_human_browsing,node_spreadsheet_tools,node_scripts_ingestion toneMint
```
## Components
### Metadata
Repository contract and snapshot context
- [README](https://github.com/liquidslr/interview-company-wise-problems/blob/main/Readme.md): contract doc · Defines the curated, company-grouped dataset and the 1 June 2025 snapshot boundary. · `Readme.md`
- [1 Jun 2025](https://github.com/liquidslr/interview-company-wise-problems/blob/main/Readme.md): snapshot date · Maintained dataset state referenced by the README. · `Readme.md`
- [System notes](https://github.com/liquidslr/interview-company-wise-problems/blob/main/Readme.md): external link · Referenced sibling resource mentioned in the README, but not part of this repository. · `Readme.md`
- **Curated lists**: content source · Externally produced question lists committed into the repo as CSV snapshots.
### Dataset Layout
Company-scoped CSV partitions and repeated time-slice structure
- **Company folders**: dataset boundary · Each top-level folder is an independent employer/org partition that can be browsed or pulled separately.
- [Amazon](https://github.com/liquidslr/interview-company-wise-problems/tree/main/Amazon): company partition · Representative company dataset folder following the standard five-file pattern. · `Amazon`
- [Google](https://github.com/liquidslr/interview-company-wise-problems/tree/main/Google): company partition · Representative company dataset folder following the standard five-file pattern. · `Google`
- [Stripe](https://github.com/liquidslr/interview-company-wise-problems/tree/main/Stripe): company partition · Representative company dataset folder following the standard five-file pattern. · `Stripe`
- **30 days**: recency slice · Most recent company-wise view.
- **3 months**: recency slice · Medium-recency company-wise view.
- **6 months**: recency slice · Longer-recency company-wise view.
- **>6 months**: recency slice · Older company-wise view.
- **All**: aggregate slice · Full company list combining the underlying problem set.
- **CSV format**: file format · Simple file-based schema implied by naming rather than code.
### Consumers
Ways the file-based catalog is read or ingested
- **Human browsing**: consumer · Readers scan folders and CSVs directly.
- **Spreadsheets**: consumer · Spreadsheet workflows open the company CSVs as tabular snapshots.
- **CSV scripts**: consumer · Downstream scripts parse company partitions and time slices for ingestion.
## Connections
- README → Curated lists: defines · The README states the curated content contract.
- README → 1 Jun 2025: anchors · The README fixes the maintained snapshot date.
- README → Company folders: organizes · The README describes company-grouped partitions.
- README → System notes: references · Mentions a sibling notes resource outside this repo.
- Curated lists → Company folders: feeds · Externally curated lists are committed into company folders.
- Company folders → Amazon: example · Representative company partition.
- Company folders → Google: example · Representative company partition.
- Company folders → Stripe: example · Representative company partition.
- Amazon → 30 days: contains · Company folders expose the recency slices.
- Amazon → 3 months: contains · Company folders expose the recency slices.
- Amazon → 6 months: contains · Company folders expose the recency slices.
- Amazon → >6 months: contains · Company folders expose the recency slices.
- Amazon → All: contains · Company folders expose the aggregate list.
- Google → 30 days: contains · Same five-file pattern in every company folder.
- Stripe → All: contains · Same five-file pattern in every company folder.
- CSV format → 30 days: shapes · Shared CSV naming convention represents the first recency slice.
- CSV format → All: shapes · Shared CSV naming convention represents the aggregate slice.
- Company folders → CSV format: standardizes · A repeated file pattern makes the repository scan-friendly.
- 30 days → Human browsing: read by · Users browse the freshest company questions.
- All → Spreadsheets: read by · Spreadsheets open the aggregate company list.
- CSV format → CSV scripts: parsed by · Scripts ingest the file-based catalog.