The hottest Data Structures Substack posts right now

And their main takeaways
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Top Technology Topics

Memory Management Every Programmer Should Know

Web Dev Explorer • 3 HN points • 29 Apr 24
🕹 Technology Programming Memory management Data Structures Web Development
  1. Data stored on the stack is static, fixed in size, with a fixed lifecycle, and cannot be referenced across different stack frames.
  2. Data stored on the heap is dynamic, not fixed in size, has a flexible lifecycle, and can be referenced across different stack frames.
  3. Various programming languages use different memory management approaches, like manual management in C, garbage collection in Java, ARC in Objective-C and Swift, and ownership mechanism in Rust.

The Sliding Window Technique[Technique Tuesdays]

Technology Made Simple • 279 implied HN points • 28 Feb 24
🕹 Technology Algorithms Problem Solving Software Engineering Artificial Intelligence Data Structures
  1. The sliding window technique is a powerful algorithmic model used for problem-solving in coding interviews and software engineering, offering efficiency and practicality.
  2. Benefits of using the sliding window technique include reducing duplicate work, maintaining consistent linear time complexity, and its utility in AI feature extraction processes.
  3. Spotting the sliding window technique involves identifying keywords like maximum, minimum, longest, or shortest, dealing with continuous elements, and converting brute-force approaches into efficient solutions.

Why Graphs are great for Fraud Detection [Math Mondays]

Technology Made Simple • 639 implied HN points • 01 Jan 24
🕹 Technology Graphs Neural Networks Machine Learning Data Structures
  1. Graphs are efficient at encoding and representing relationships between entities, making them useful for fraud detection tasks.
  2. Graph Neural Networks excel at fraud detection due to their ability to visualize strong correlations among fraudulent activities that share common properties, adapt to new fraud patterns, and offer transparency in AI systems.
  3. Graph Neural Networks require less labeled data and feature engineering compared to other techniques, have better explainability, and work well with semi-supervised learning, making them a powerful tool for fraud detection.

Controlling Rate-Limited Events - Implementation

Low Latency Trading Insights • 117 implied HN points • 11 Feb 24
🕹 Technology Algorithms Data Structures Coding Performance
  1. The requirements for a rate-limiting algorithm include precise event counting, fast performance especially during market turbulence, and minimal impact on cache memory.
  2. Creating a rate-limiting algorithm using a multimap for counting events has inefficiencies; a better solution involves enhancements for optimal performance.
  3. A bounded approximation approach for rate limiting achieves memory efficiency by assuming a minimum time precision and implementing a clever advance-and-clear mechanism.

A deeper than average look into Stacks [Math Mondays]

Technology Made Simple • 99 implied HN points • 21 Nov 23
🕹 Technology Programming Data Structures Algorithms Computer Science Software Engineering
  1. Stacks are powerful data structures in software engineering and can be modified extensively to suit different use cases.
  2. Implementing Stacks using a Singly Linked List can be beneficial for dynamic resizing, though Arrays are often preferred due to memory considerations.
  3. Exploring variations like Persistent Stacks, Limiting Stack Size, Ensuring Type Safety, Thread Safety, Tracking Min/Max, and Undo Operations can enhance the functionality and efficiency of Stacks in various scenarios.
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Looking at the Datastructures- Trees [Math Mondays]

Technology Made Simple • 179 implied HN points • 18 Jul 23
🕹 Technology Data Structures Software Engineering Machine Learning AI Recursion
  1. Trees are powerful data structures that are great for efficient organization and retrieval of data in software engineering.
  2. Recursion works well with trees due to their recursive substructure, making implementation of recursive functions easier.
  3. Decision trees in AI excel at discerning complex patterns, providing interpretable results, and are versatile in various domains such as finance, healthcare, and marketing.

Power of Redis: A Deep Dive into Caching Systems

The ZenMode • 15 HN points • 10 Feb 24
🕹 Technology Caching Data Structures Performance Limitations Deployment
  1. Caching like Redis stores frequently used data for faster retrieval, improving response times, reducing database load, and leading to cost-effectiveness in running high-traffic applications.
  2. Redis is fast due to in-memory storage, optimized data structures, reduced I/O operations, single-threaded architecture, and event-driven design, but has limitations like limited capacity and issues with data persistence.
  3. Choosing the right caching system, like Redis, requires considering factors like data size, access patterns, consistency requirements, and fault tolerance for high availability and durability.

How to Learn Data Structures and Algorithms [Storytime Saturdays]

Technology Made Simple • 299 implied HN points • 22 Jan 23
🚌 Education Data Structures Algorithms Learning
  1. Understanding Data Structures and Algorithms is crucial for success in technical fields like software development.
  2. Many resources focus on DSA for coding interviews, but it's important to go beyond that to deepen your knowledge.
  3. Learning DSA effectively doesn't have to involve answering countless questions or watching numerous tutorials; there are better approaches available.

DSA For The Rest Of Us - Part 1

Data Engineering Central • 157 implied HN points • 13 Mar 23
🕹 Technology Data Engineering Data Structures Software Development Rust Programming
  1. Understanding Data Structures and Algorithms is important for becoming a better engineer, even if you may not use them daily.
  2. Linked Lists are a linear data structure where elements are not stored contiguously in memory but are linked using pointers.
  3. Creating a simple Linked List in Rust involves defining nodes with values and pointers to other nodes, creating a LinkedList to hold these nodes, and then linking them to form a chain.

#48

The Nibble • 7 implied HN points • 24 Feb 24
🕹 Technology AI Crypto Web Development Software Development Data Structures
  1. Feedback is being sought for the newsletter content to better cater to readers' interests.
  2. Interesting developments in the tech world include potential $7 trillion AI chip funding, Reddit IPO unique share distribution, and US Tech getting into the Indian market.
  3. Noteworthy advancements in AI technologies, such as new models like LLM streaming and fast inference engines, are shaping diverse industries.

Why and How Does Python Use Bloom Filters in String Processing?

Confessions of a Code Addict • 46 HN points • 14 Sep 23
🕹 Technology Programming Data Structures Implementation Python
  1. Python uses Bloom filters in its string data structure to speed up certain string processing functions like strip and splitlines.
  2. The unique Bloom filter implementation in CPython uses an unsigned long type to represent the bit vector, making storing and querying items more efficient.
  3. CPython determines the position in the bit vector for adding and querying characters by using the lower n-bits of the character, avoiding costly hash computations.

Problem 85: Count Complete Tree Nodes [Amazon]

Technology Made Simple • 99 implied HN points • 04 May 23
🕹 Technology Coding Data Structures Algorithms Tech industry
  1. The post discusses Problem 85: Count Complete Tree Nodes [Amazon], focusing on recursion, trees, and data structures.
  2. It is about solving a problem related to counting the number of nodes in a complete binary tree efficiently.
  3. The post mentions the importance of community engagement in choosing problems to discuss and the growth of the author's newsletter.

[Solution]Problem 85: Count Complete Tree Nodes [Amazon]

Technology Made Simple • 59 implied HN points • 05 May 23
🕹 Technology Coding Data Structures Algorithm Software Engineering
  1. The post discusses a problem related to counting the number of nodes in a complete binary tree, emphasizing the importance of understanding recursion, trees, and data structures.
  2. It mentions starting with a brute force solution to count nodes but highlights the need for optimization to achieve time complexity better than O(n).
  3. The approach for solving the problem involves using a recursive template to count nodes efficiently by considering the root and the number of nodes in the left and right subtrees.

[Solution]Problem 72: Permutation in String [Amazon]

Technology Made Simple • 39 implied HN points • 27 Jan 23
🕹 Technology Algorithms Binary Trees Graphs Coding Data Structures
  1. The problem discussed is about validating a binary search tree, ensuring the left subtree contains smaller values, the right subtree contains greater values, and both are valid binary search trees.
  2. Examples are provided to illustrate the concept, showing a valid and an invalid binary search tree.
  3. Constraints include the number of nodes and the value ranges in the tree.

Using Sentinel Nodes to improve your Doubly Linked Lists[Technique Tuesdays]

Technology Made Simple • 59 implied HN points • 28 Sep 22
🕹 Technology Programming Data Structures Performance Memory management Coding
  1. Using sentinel nodes in Doubly Linked Lists can improve performance and make code easier to read and implement
  2. Implementing sentinel nodes removes special cases in DLL implementations, simplifies code, and makes it more provably correct
  3. Although using sentinel nodes may require some extra memory, the simplification it brings to the code is often worth the tradeoff

How to Study Data Structures and Algorithms [Technique Tuesday]

Technology Made Simple • 79 implied HN points • 06 Apr 22
🕹 Technology Coding Data Structures Algorithms
  1. Experts often give bad advice for studying Data Structures and Algorithms, like relying solely on Leetcode.
  2. To effectively learn DSA, take time to understand the history and purpose of each data structure beyond just learning the mechanics.
  3. Don't rush through learning Data Structures and Algorithms; taking it slow and grasping the fundamentals thoroughly will lead to better mastery and understanding.

How to Figure out the correct distance finding algorithm [Technique Tuesday]

Technology Made Simple • 79 implied HN points • 30 Mar 22
🕹 Technology Algorithm Graphs Coding Interviews Data Structures
  1. BFS and DFS algorithms are foundational and crucial for various graph traversal problems, forming the basis for more complicated algorithms.
  2. Topological Sort, Djikstra's Algorithm, and A* are important graph traversal algorithms to master, especially for weighted graphs and AI applications like self-driving cars.
  3. For determining the correct graph traversal algorithm, identify if you need to find the shortest path (use BFS or A* for unweighted/weighted graphs), or if you need to visit the complete graph (use DFS for problems involving the entire graph).

Bloom Filter [Systems Design Sundays]

Technology Made Simple • 59 implied HN points • 10 Jul 22
🕹 Technology Data Structures Algorithms Systems Design Interview Preparation
  1. Bloom Filters are probabilistic data structures used to efficiently test for membership.
  2. Bloom Filters work by having a bit array of size m with k hash functions mapping values to indices, setting the indices to 1 for a given input.
  3. Bloom Filters are great for reducing unnecessary disk access, but they can result in false positives and need regeneration as more values are added.

[Solution]Problem 58:Kth Largest Element in a Stream [Amazon]

Technology Made Simple • 39 implied HN points • 30 Sep 22
🕹 Technology Coding Data Structures Object Oriented Programming
  1. The problem focuses on designing a class to find the kth largest element in a stream, emphasizing it's the kth largest in sorted order, not distinct element.
  2. The implementation includes initializing the class with k and a set of numbers, then appending values to the stream to return the kth largest element.
  3. The constraints for the problem include specific limitations on the range of values and number of calls that can be made.

All about the graphs [Math Monday]

Technology Made Simple • 59 implied HN points • 29 Mar 22
🕹 Technology Data Structures Algorithms Graphs Coding Interviews
  1. Graphs can be seen from various perspectives: charts and plots (stats), maps with complex algorithms (graph theory), and adjacency lists for coding. Understanding these perspectives is crucial for effective use of graphs.
  2. Identifying whether a problem could be a graph problem involves recognizing the entities (nodes), relationships (edges), and weights in the context of a system. This spotting framework helps in solving graph-related problems efficiently.
  3. Practicing graph spotting as a skill involves starting with easy problems to identify graph components quickly. Familiarity with graphs and the ability to spot them easily is crucial for solving graph problems in interviews.

Reduce memory of graph traversal by marking spot as visited instead of using a set[Technique Tuesdays]

Technology Made Simple • 39 implied HN points • 02 Aug 22
🕹 Technology Coding Optimization Algorithms Data Structures Tech Education
  1. In graph traversal, reducing memory usage by marking spots as visited instead of using a set can optimize your code and help you move from O(n) space complexity to O(1) complexity.
  2. This technique is straightforward to implement, takes no extra space, and can be a significant improvement in graph traversal algorithms.
  3. When implementing this technique, be cautious about the value used to mark visited cells and always confirm with your interviewer about input data type to avoid conflicts.

[Solution]Problem 41: Create your own Datastructure with O(1) Time complexity (Dropbox)

Technology Made Simple • 39 implied HN points • 11 Jun 22
🕹 Technology Data Structures Logic Programming Algorithms Software Engineering
  1. Creating a data structure with O(1) time complexity involves implementing functions like plus, minus, get_max, and get_min efficiently.
  2. Utilizing a Doubly Linked List allows for maintaining a sorted collection of keys, enabling quick access to elements with the lowest and highest values.
  3. Developing algorithms to handle key count increments and decrements while preserving the sorted order of the linked list is crucial for a functional solution.

Using Bits as a way to Encode Preference[Technique Tuesdays]

Technology Made Simple • 39 implied HN points • 01 Jun 22
🕹 Technology Coding Data Structures Algorithms Math
  1. Using bit fields can significantly reduce storage requirements for tracking user preferences. A technique by Vimeo engineers allowed O(1) space compared to the traditional O(k) method, making the solution far more efficient.
  2. Bit fields utilize bitwise operators to represent content filters, enabling quick comparisons in constant time. This approach is memory and time-efficient.
  3. Implementing bit fields for tracking user preferences allows for efficient filtering of content by performing a bitwise AND operation between the user's and video's bit fields. This results in a quick eligibility check for the user.

Bloom Filters and Beyond: An Illustrated Introduction and Implementation

Confessions of a Code Addict • 5 HN points • 05 Sep 23
🕹 Technology Data Structures Programming Algorithms Python Applications
  1. Bloom filters are efficient data structures for quick searches in large datasets and minimize memory usage, with a probabilistic approach to determining membership
  2. Bloom filters use hash functions and bit vectors to store data item membership information while conserving memory by not storing actual items
  3. Counting Bloom Filters are an extension that allow item deletion but come with weaknesses such as handling hash collisions and counter overflow, providing an advanced data handling tool

[Solution]Problem 44: Longest Substring Without Repeating Characters (Meta / Facebook)

Technology Made Simple • 19 implied HN points • 01 Jul 22
🕹 Technology Programming Algorithms Data Structures Web Development
  1. The problem discussed is about finding the length of the longest substring without repeating characters.
  2. Approaching a coding problem by carefully considering the data structures to use, like dictionaries and sets, can be crucial in developing an efficient solution.
  3. Building a clear path to figure out the start and end points of the substring can lead to a more organized and effective algorithm implementation.

[Solution]Problem 42: Length of the longest subarray where all its elements are distinct (Microsoft)

Technology Made Simple • 19 implied HN points • 17 Jun 22
🕹 Technology Math Combinatorics Data Structures Algorithms
  1. When faced with a problem involving combinatorics, taking the time to read and analyze the question can provide crucial insights for a more efficient solving approach
  2. In the context of building max heaps from a list of integers, understanding the structure of heaps as complete binary trees allows for simplification of the problem into calculating combinations and values for left and right subtrees
  3. Calculating the values for the left subtree, such as height and number of nodes, can lead to a shift in the coding task complexity from generating heaps to conducting combinatorics

Problem 41: Create your own Datastructure with O(1) Time complexity (Dropbox)

Technology Made Simple • 19 implied HN points • 09 Jun 22
🕹 Technology Data Structures
  1. Creating a data structure with O(1) time complexity involves operations like adding, decrementing, and finding maximum and minimum values efficiently.
  2. Special requests can help boost newsletter visibility by encouraging readers to engage or provide feedback.
  3. Engaging with readers and asking for their input on future topics can lead to more interactive content creation.

A Nibble of Quadtrees in Rust

Get Code • 7 implied HN points • 22 Feb 23
🕹 Technology Data Structures WebAssembly Image Processing
  1. Quadtrees are data structures where each non-leaf node has exactly four children and are used to represent properties of two-dimensional space.
  2. Quadtrees are used for performance reasons, like optimizing collision detection in simulations with many moving objects.
  3. Implementing region quadtrees in Rust involves subdividing the tree based on error thresholds and region lengths to efficiently represent images.

Why Math Mondays

Technology Made Simple • 19 implied HN points • 14 Mar 22
🚌 Education Math Interview Preparation Knowledge Data Structures Algorithms
  1. Understanding the importance of Math in preparation can help with solving problems better.
  2. Knowledge about subjects, problem interpretation, and connections between topics are crucial in problem-solving.
  3. Math Mondays aim to show how mathematical knowledge can enhance problem-solving skills and help make connections between different concepts.