⚡ Quick Start

Get started with AlgoChronicle in 5 minutes

What is AlgoChronicle?

AlgoChronicle is a personal DSA (Data Structures & Algorithms) practice tracker that automatically syncs with your GitHub repository. Every time you solve a problem and push to GitHub, it appears on your AlgoChronicle dashboard.

🔄

Auto-Sync

GitHub → AlgoChronicle

📊

Track Progress

Stats & Streaks

🔁

Spaced Repetition

Smart Revisions

🔄The Workflow

Solve a Problem

Pick a problem from LeetCode, HackerRank, or any platform. Solve it in your favorite language(s).

Create a Folder

In your dsa-problems repo, create a folder like 001-two-sum/

001-two-sum/
├── README.md          # Problem metadata
├── solution.py        # Python solution
├── solution.java      # Java solution
└── solution.cpp       # C++ solution

Write README with Metadata

Add a README.md with YAML frontmatter:

---
dayNumber: 1
title: Two Sum
platform: LeetCode
link: https://leetcode.com/problems/two-sum/
difficulty: Easy
pattern: Hash Table
approach: Use hash map to store complements
optimized: O(n)
bruteforce: O(n²)
space: O(n)
date: 2025-10-23
---

## Notes
Your notes here...

Commit & Push

$ git add .
$ git commit -m "Solve Two Sum problem"
$ git push origin main

The GitHub webhook automatically sends your problem to AlgoChronicle!

✓

See it on AlgoChronicle

Refresh your AlgoChronicle dashboard - your problem card appears with all metadata, complexity analysis, and language badges!

✨Key Features

📊

Statistics Dashboard

Track your progress with detailed stats: total problems solved, current streak, platform breakdown, and complexity distribution.

🔥

Consistency Tracker

Visualize your daily activity with a GitHub-style heatmap. Maintain your streak and build coding consistency.

🔄

Spaced Repetition

Smart revision scheduling based on spaced repetition algorithm. Review problems at optimal intervals for long-term retention.

🎨

Rich Problem Cards

Beautiful cards showing difficulty, pattern, approach, complexity analysis, and language badges for all your solutions.

📡

RSS Feed

Subscribe to your problem feed using any RSS reader. Get notified instantly when you add new problems.

🔗

Direct Links

Every problem card links to the original problem and your GitHub solution. Easy reference during interviews.

📝README Fields Explained

dayNumber

Sequential day number (1, 2, 3, ...) - used for ordering problems

title

Problem name (e.g., "Two Sum", "Reverse Linked List")

platform

Where you solved it (LeetCode, HackerRank, CodeChef, etc.)

difficulty

Easy, Medium, or Hard - shows color-coded badge

pattern

Algorithm pattern (Two Pointers, Sliding Window, Dynamic Programming, etc.)

approach

One-line summary of your solution approach

optimized

Time complexity of optimized solution (O(n), O(n log n), etc.)

bruteforce

Time complexity of brute force approach

space

Space complexity (O(1), O(n), etc.)

date

Date solved (YYYY-MM-DD format)

💡Pro Tips

•Name folders clearly: Use format like 001-two-sum for easy sorting
•Write detailed approaches: Your future self will thank you during interview prep
•Solve in multiple languages: AlgoChronicle shows badges for Python 🐍, Java ☕, and C++ ⚡
•Track patterns: Grouping problems by pattern helps you recognize similar problems
•Use spaced repetition: Review problems at increasing intervals for better retention

🚀Next Steps

📖 Complete Setup Guide

Detailed Firebase and GitHub webhook configuration

🧠 Learn Spaced Repetition

Understand how to optimize your revision schedule

🏠 Go to Dashboard

Start tracking your DSA journey

What is AlgoChronicle?

🔄

Auto-Sync

GitHub → AlgoChronicle

📊

Track Progress

Stats & Streaks

🔁

Spaced Repetition

Smart Revisions

🔄The Workflow

Solve a Problem

Pick a problem from LeetCode, HackerRank, or any platform. Solve it in your favorite language(s).

Create a Folder

In your dsa-problems repo, create a folder like 001-two-sum/

001-two-sum/
├── README.md          # Problem metadata
├── solution.py        # Python solution
├── solution.java      # Java solution
└── solution.cpp       # C++ solution

Write README with Metadata

Add a README.md with YAML frontmatter:

---
dayNumber: 1
title: Two Sum
platform: LeetCode
link: https://leetcode.com/problems/two-sum/
difficulty: Easy
pattern: Hash Table
approach: Use hash map to store complements
optimized: O(n)
bruteforce: O(n²)
space: O(n)
date: 2025-10-23
---

## Notes
Your notes here...

Commit & Push

$ git add .
$ git commit -m "Solve Two Sum problem"
$ git push origin main

The GitHub webhook automatically sends your problem to AlgoChronicle!

✓

See it on AlgoChronicle

Refresh your AlgoChronicle dashboard - your problem card appears with all metadata, complexity analysis, and language badges!

✨Key Features

📊

Statistics Dashboard

Track your progress with detailed stats: total problems solved, current streak, platform breakdown, and complexity distribution.

🔥

Consistency Tracker

Visualize your daily activity with a GitHub-style heatmap. Maintain your streak and build coding consistency.

🔄

Spaced Repetition

Smart revision scheduling based on spaced repetition algorithm. Review problems at optimal intervals for long-term retention.

🎨

Rich Problem Cards

Beautiful cards showing difficulty, pattern, approach, complexity analysis, and language badges for all your solutions.

📡

RSS Feed

Subscribe to your problem feed using any RSS reader. Get notified instantly when you add new problems.

🔗

Direct Links

Every problem card links to the original problem and your GitHub solution. Easy reference during interviews.

📝README Fields Explained

dayNumber

Sequential day number (1, 2, 3, ...) - used for ordering problems

title

Problem name (e.g., "Two Sum", "Reverse Linked List")

platform

Where you solved it (LeetCode, HackerRank, CodeChef, etc.)

difficulty

Easy, Medium, or Hard - shows color-coded badge

pattern

Algorithm pattern (Two Pointers, Sliding Window, Dynamic Programming, etc.)

approach

One-line summary of your solution approach

optimized

Time complexity of optimized solution (O(n), O(n log n), etc.)

bruteforce

Time complexity of brute force approach

space

Space complexity (O(1), O(n), etc.)

date

Date solved (YYYY-MM-DD format)

💡Pro Tips

•Name folders clearly: Use format like 001-two-sum for easy sorting

•Write detailed approaches: Your future self will thank you during interview prep

•Solve in multiple languages: AlgoChronicle shows badges for Python 🐍, Java ☕, and C++ ⚡

•Track patterns: Grouping problems by pattern helps you recognize similar problems

•Use spaced repetition: Review problems at increasing intervals for better retention