Can I Travel After Pass the Interview for Citizenship
To LeetCode or not to LeetCode?
What if yous don't want to practice 100s of coding questions earlier your next coding interview?
At that place is a role of me that dislikes coding interviews, primarily because it requires me to spend a lot of fourth dimension preparing for coding questions. Moreover, during an interview, I have to nowadays a reasonable (if not optimal) solution to someone who is evaluating me, something I don't have to deal with in my everyday life as a software engineer.
Having said that, I do beloved algorithms and solving coding problems. It is a fun activity for me, information technology gives me expert mental exercise, and I love to spend time on information technology. In this postal service, I would similar to share some of my learnings and the techniques that I've developed over time which makes preparing for coding interviews an exciting and fun activity.
A fiddling almost me; my software technology career spans effectually 20 years, in which I've switched jobs five times. I've given around 30 interview loops containing 120+ interviews. I accept some experience sitting on the other side of the table too. I've taken 300+ coding interviews and 200+ system pattern interviews.
Background
If yous are looking to switch jobs and preparing for coding interviews, you will definitely know LeetCode. It is probably the biggest online repository for coding interview questions and also contains a vibrant community to discuss algorithms with other young man engineers. Whenever I'm gratuitous, I honey spending time on LeetCode, trying to solve a new coding question, or learning from other smart solutions that people take adult.
Problems with LeetCode
Ane of the biggest challenges with LeetCode is that it lacks organization; information technology has a huge set of coding issues, and one feels lost on where to kickoff or what to focus on. What is an aplenty amount of questions one should go through earlier because themselves prepared for their coding interview? I would dearest to meet a streamlined procedure that can guide me and teach me enough algorithmic techniques to feel confident for the interview. Being a lazy person myself, I wouldn't say I like to go through 500+ questions.
The Solution
One technique that people often follow is to solve questions related to the same data structure; for example, focusing on questions related to Arrays, so LinkedList, HashMap, Heap, Tree, or Trie, etc. Although this does provide some organization, it still lacks coherence. For case, many questions can exist solved using HashMaps merely nonetheless require different algorithmic techniques. I would love to see question sets that follow not simply the same data structure just also similar algorithmic techniques. The best thing I came across was the problem-solving patterns like Sliding Window, Fast and Slow Pointers, or Topological Sort, etc. Following these patterns helped me nurture my ability to map a new trouble to an already known problem. This not just made this whole coding-interview-preparation process fun but likewise a lot more organized.
I have gathered around 25 of these coding trouble patterns, which I believe can assist anyone acquire these beautiful algorithmic techniques and make a real difference in the coding interviews. The idea behind these patterns is, in one case yous're familiar with a pattern, you'll exist able to solve dozens of issues with it. For a detailed discussion of these patterns and related bug with solutions, take a look at Grokking the Coding Interview.
And so, without further ado, let me list all these patterns:
- Sliding Window
- Two Pointers
- Fast & Slow Pointers
- Merge Intervals
- Cyclic Sort
- In-identify Reversal of a LinkedList
- Tree Breadth-Get-go Search
- Tree Depth Showtime Search
- Two Heaps
- Subsets
- Modified Binary Search
- Bitwise XOR
- Top 'Yard' Elements
- K-way Merge
- 0/1 Knapsack
- Unbounded Knapsack
- Fibonacci Numbers
- Palindromic Subsequence
- Longest Common Substring
- Topological Sort
- Trie Traversal
- Number of Island
- Trial & Error
- Union Find
- Unique Paths
Following is a small-scale intro of each of these patterns with sample issues:
1. Sliding Window
Usage: This algorithmic technique is used when we need to handle the input information in specific window size.
Sample Issues:
- Longest Substring with K Singled-out Characters
- Fruits into Baskets
- Permutation in a String
2. Two Pointers
Usage: In this technique, nosotros use two pointers to iterate the input information. Generally, both pointers move in the opposite direction at a constant interval.
Sample Problems:
- Squaring a Sorted Array
- Dutch National Flag Trouble
- Minimum Window Sort
three. Fast & Slow Pointers
Usage: Also known equally Hare & Tortoise algorithm. In this technique, nosotros use two pointers that traverse the input data at a different speed.
Sample Bug:
- Middle of the LinkedList
- Happy Number
- Cycle in a Circular Assortment
iv. Merge Intervals
Usage: This technique is used to bargain with overlapping intervals. Given two intervals ('a' and 'b'), at that place will be half-dozen dissimilar ways the two intervals tin can relate to each other:
Sample Issues:
- Intervals Intersection
- Conflicting Appointments
- Minimum Meeting Rooms
5. Cyclic Sort
Usage: Use this technique to solve array problems where the input data lies within a fixed range.
Sample Issues:
- Find all Missing Numbers
- Find all Duplicate Numbers
- Discover the Kickoff K Missing Positive Numbers
6. In-place Reversal of a LinkedList
Usage: This technique describes an efficient way to contrary the links between a set of nodes of a LinkedList. Often, the constraint is that nosotros demand to do this in-identify, i.e., using the existing node objects and without using extra memory.
Sample Issues:
- Reverse every K-element Sub-list
- Rotate a LinkedList
7. Tree Latitude-First Search
Usage: Equally the name suggests, this technique is used to solve problems involving traversing trees in a breadth-beginning search manner.
Sample Problems:
- Binary Tree Level Guild Traversal
- Minimum Depth of a Binary Tree
- Connect Level Order Siblings
eight. Tree Depth Start Search
Usage: As the proper name suggests, this technique is used to solve bug involving traversing trees in depth-showtime search style.
Sample Problems:
- Path With Given Sequence
- Count Paths for a Sum
9. 2 Heaps
Usage: In many problems, where we are given a prepare of elements such that we can dissever them into ii parts. We are interested in knowing the smallest element in ane office and the biggest element in the other part. Every bit the proper noun suggests, this technique uses a Min-Heap to find the smallest chemical element and a Max-Heap to find the biggest element.
Sample Problems:
- Find the Median of a Number Stream
- Next Interval
x. Subsets
Usage: Utilize this technique when the trouble asks to deal with permutations or combinations of a set of elements.
Sample Issues:
- String Permutations by changing case
- Unique Generalized Abbreviations
eleven. Modified Binary Search
Usage: Utilize this technique to search a sorted gear up of elements efficiently.
Sample Problems:
- Ceiling of a Number
- Bitonic Array Maximum
12. Bitwise XOR
Usage: This technique uses the XOR operator to manipulate bits to solve problems.
Sample Problems:
- Two Single Numbers
- Flip and Invert an Image
13. Top 'K' Elements
Usage: This technique is used to find peak/smallest/oft occurring 'Chiliad' elements in a set.
Sample Problems:
- 'K' Closest Points to the Origin
- Maximum Distinct Elements
xiv. K-way Merge
Usage: This technique helps us solve problems that involve a list of sorted arrays.
Sample Problems:
- Kth Smallest Number in M Sorted Lists
- Kth Smallest Number in a Sorted Matrix
xv. 0/1 Knapsack
Usage: This technique is used to solve optimization problems. Apply this technique to select elements that give maximum turn a profit from a given set with a limitation on chapters and that each element can merely exist picked once.
Sample Problems:
- Equal Subset Sum Division
- Minimum Subset Sum Difference
16. Unbounded Knapsack
Usage: Use this technique to select elements that give maximum profit from a given ready with a limitation on capacity and that each element can exist picked multiple times.
Sample Issues:
- Rod Cut
- Coin Change
17. Fibonacci Numbers
Usage: Use this technique to solve problems that follow the Fibonacci numbers sequence, i.due east., every subsequent number is calculated from the last few numbers.
Sample Issues:
- Staircase
- Business firm Thief
xviii. Palindromic Subsequence
Usage: This technique is used to solve optimization problems related to palindromic sequences or strings.
Sample Problems:
- Longest Palindromic Subsequence
- Minimum Deletions in a String to make it a Palindrome
nineteen. Longest Common Substring
Usage: Use this technique to notice the optimal office of a string/sequence or set up of strings/sequences.
Sample Issues:
- Maximum Sum Increasing Subsequence
- Edit Distance
xx. Topological Sort
Usage: Utilise this technique to find a linear ordering of elements that have dependencies on each other.
Sample Issues:
- Tasks Scheduling
- Conflicting Dictionary
21. Trie Traversal
Usage: Use this technique that involves creating or traversing of Trie information structure.
Sample Problems:
- Longest Word in Lexicon
- Palindrome Pairs
22. Number of Island
Usage: Use this technique to traverse a two-dimensional array and find a ready of connected elements.
Sample Problems:
- Number of Distinct Islands
- Maximum Area of Island
23. Trial & Error
Usage: Use this technique to traverse an array to detect a required optimal chemical element. The traversal process runs in a trial & error fashion.
Sample Problems:
- Discover Kth Smallest Pair Distance
- Minimize Max Distance to Gas Station
24. Union Find
Usage: Use this technique to solve problems that require maintaining a given gear up of elements partitioned into multiple non-overlapping subsets.
Sample Problems:
- Number of Provinces
- Bipartite Graph
25. Unique Paths
Usage: Apply this technique to find different/optimal means to traverse a multi-dimensional array.
Sample Bug:
- Notice Unique Paths
- Dungeon Game
Conclusion
Similar it or not, LeetCode-type questions are a function of almost every programming interview, so every software developer should do them before an interview.
Their simply option is to ready smartly and learn trouble-solving by focusing on the underlying problem patterns. Learn more than about these patterns and sample problems in Grokking the Coding Interview and Grokking Dynamic Programming for Coding Interviews.
Bank check Design Gurus for some interesting courses on Coding and System Pattern interviews.
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