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How to find common elements in two unsorted arrays with sizes n and m avoiding double for loop?
Programmers, software engineers, coders, IT professionals, and software architects all face the common challenge of needing to find common elements in two unsorted arrays with sizes n and m. This can be a difficult task, especially if you don’t want to use a double for loop.
In this blog post, we will be discussing how to find common elements in two unsorted arrays with sizes n and m avoiding double for loop. We will be discussing various methods that can be used to solve this problem and comparing the time complexity of each method.
There are several ways that you can find common elements in two unsorted arrays with sizes n and m avoiding double for loop. One way is by using the hashing technique. With this technique, you can create a hash table for one of the arrays. Then, you can traverse through the second array and check if the element is present in the hash table or not. If the element is present in the hash table, then it is a common element. Another way that you can find common elements in two unsorted arrays with sizes n and m avoiding double for loop is by using the sorting technique. With this technique, you can sort both of the arrays first. Then, you can traverse through both of the arrays simultaneously and compare the elements. If the elements are equal, then it is a common element.
Method 1: Linear Search
The first method we will discuss is linear search. This method involves iterating through both arrays and comparing each element. If the element is found in both arrays, it is added to the result array. The time complexity of this method is O(nm), where n is the size of the first array and m is the size of the second array.
Method 2: HashMap Method
The second method we will discuss is the HashMap method. This method involves creating a HashMap of all the elements in the first array. Then, we iterate through the second array and check if the elements are present in the HashMap. If they are, we add them to the result array. The time complexity of this method is O(n+m), where n is the size of the first array and m is the size of the second array.
Method 3: Sort and Compare Method
The third method we will discuss is the Sort and Compare Method. This method involves sorting both arrays using any sorting algorithm like merge sort or quick sort. Once both arrays are sorted, we compare each element of both arrays one by one until we find a match. If a match is found, we add it to our result array. The time complexity of this method is O(nlogn+mlogm), where n is the size of the first array and m is the size of the second array.
The naïve algorithm for finding common elements in two unsorted arrays with sizes nn and mm is O(nm)O(nm), i.e. quadratic.
The algorithm for sorting an array is O(nlogn)O(nlogn), and you can find common elements in two sorted arrays in O(n+m)O(n+m). In other words, for large enough arrays, it is significantly faster to first sort them, then look for the common elements, because the sorting algorithm will dominate the complexity, so your final algorithm ends up at O(nlogn)O(nlogn) as well.

Conclusion:
In this blog post, we discussed how to find common elements in two unsorted arrays with sizes n and m avoiding double for loop. We discussed three different methods that can be used to solve this problem and compared their time complexities. We hope that this blog post was helpful in understanding how to solve this problem.
There are many different ways to find common elements in two unsorted arrays with sizes n and m avoiding double for loop. The most straight forward way is by using a double for loop but this approach is not very efficient. A more efficient way is by using a hash table which has a time complexity of O(n+m). This algorithm is faster because we only need to loop through one of the arrays. We can then use the values from that array to check if there are any duplicates in the second array. This approach also uses less memory because we are not creating a new list to store the common elements.


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List of Freely available programming books - What is the single most influential book every Programmers should read
- Bjarne Stroustrup - The C++ Programming Language
- Brian W. Kernighan, Rob Pike - The Practice of Programming
- Donald Knuth - The Art of Computer Programming
- Ellen Ullman - Close to the Machine
- Ellis Horowitz - Fundamentals of Computer Algorithms
- Eric Raymond - The Art of Unix Programming
- Gerald M. Weinberg - The Psychology of Computer Programming
- James Gosling - The Java Programming Language
- Joel Spolsky - The Best Software Writing I
- Keith Curtis - After the Software Wars
- Richard M. Stallman - Free Software, Free Society
- Richard P. Gabriel - Patterns of Software
- Richard P. Gabriel - Innovation Happens Elsewhere
- Code Complete (2nd edition) by Steve McConnell
- The Pragmatic Programmer
- Structure and Interpretation of Computer Programs
- The C Programming Language by Kernighan and Ritchie
- Introduction to Algorithms by Cormen, Leiserson, Rivest & Stein
- Design Patterns by the Gang of Four
- Refactoring: Improving the Design of Existing Code
- The Mythical Man Month
- The Art of Computer Programming by Donald Knuth
- Compilers: Principles, Techniques and Tools by Alfred V. Aho, Ravi Sethi and Jeffrey D. Ullman
- Gödel, Escher, Bach by Douglas Hofstadter
- Clean Code: A Handbook of Agile Software Craftsmanship by Robert C. Martin
- Effective C++
- More Effective C++
- CODE by Charles Petzold
- Programming Pearls by Jon Bentley
- Working Effectively with Legacy Code by Michael C. Feathers
- Peopleware by Demarco and Lister
- Coders at Work by Peter Seibel
- Surely You're Joking, Mr. Feynman!
- Effective Java 2nd edition
- Patterns of Enterprise Application Architecture by Martin Fowler
- The Little Schemer
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- Why's (Poignant) Guide to Ruby
- The Inmates Are Running The Asylum: Why High Tech Products Drive Us Crazy and How to Restore the Sanity
- The Art of Unix Programming
- Test-Driven Development: By Example by Kent Beck
- Practices of an Agile Developer
- Don't Make Me Think
- Agile Software Development, Principles, Patterns, and Practices by Robert C. Martin
- Domain Driven Designs by Eric Evans
- The Design of Everyday Things by Donald Norman
- Modern C++ Design by Andrei Alexandrescu
- Best Software Writing I by Joel Spolsky
- The Practice of Programming by Kernighan and Pike
- Pragmatic Thinking and Learning: Refactor Your Wetware by Andy Hunt
- Software Estimation: Demystifying the Black Art by Steve McConnel
- The Passionate Programmer (My Job Went To India) by Chad Fowler
- Hackers: Heroes of the Computer Revolution
- Algorithms + Data Structures = Programs
- Writing Solid Code
- JavaScript - The Good Parts
- Getting Real by 37 Signals
- Foundations of Programming by Karl Seguin
- Computer Graphics: Principles and Practice in C (2nd Edition)
- Thinking in Java by Bruce Eckel
- The Elements of Computing Systems
- Refactoring to Patterns by Joshua Kerievsky
- Modern Operating Systems by Andrew S. Tanenbaum
- The Annotated Turing
- Things That Make Us Smart by Donald Norman
- The Timeless Way of Building by Christopher Alexander
- The Deadline: A Novel About Project Management by Tom DeMarco
- The C++ Programming Language (3rd edition) by Stroustrup
- Patterns of Enterprise Application Architecture
- Computer Systems - A Programmer's Perspective
- Agile Principles, Patterns, and Practices in C# by Robert C. Martin
- Growing Object-Oriented Software, Guided by Tests
- Framework Design Guidelines by Brad Abrams
- Object Thinking by Dr. David West
- Advanced Programming in the UNIX Environment by W. Richard Stevens
- Hackers and Painters: Big Ideas from the Computer Age
- The Soul of a New Machine by Tracy Kidder
- CLR via C# by Jeffrey Richter
- The Timeless Way of Building by Christopher Alexander
- Design Patterns in C# by Steve Metsker
- Alice in Wonderland by Lewis Carol
- Zen and the Art of Motorcycle Maintenance by Robert M. Pirsig
- About Face - The Essentials of Interaction Design
- Here Comes Everybody: The Power of Organizing Without Organizations by Clay Shirky
- The Tao of Programming
- Computational Beauty of Nature
- Writing Solid Code by Steve Maguire
- Philip and Alex's Guide to Web Publishing
- Object-Oriented Analysis and Design with Applications by Grady Booch
- Effective Java by Joshua Bloch
- Computability by N. J. Cutland
- Masterminds of Programming
- The Tao Te Ching
- The Productive Programmer
- The Art of Deception by Kevin Mitnick
- The Career Programmer: Guerilla Tactics for an Imperfect World by Christopher Duncan
- Paradigms of Artificial Intelligence Programming: Case studies in Common Lisp
- Masters of Doom
- Pragmatic Unit Testing in C# with NUnit by Andy Hunt and Dave Thomas with Matt Hargett
- How To Solve It by George Polya
- The Alchemist by Paulo Coelho
- Smalltalk-80: The Language and its Implementation
- Writing Secure Code (2nd Edition) by Michael Howard
- Introduction to Functional Programming by Philip Wadler and Richard Bird
- No Bugs! by David Thielen
- Rework by Jason Freid and DHH
- JUnit in Action
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