How To Get Started With Competitive Programming - Scaler Academy
What is Competitive Programming?
Competitive Programming is a mental sport that involves designing efficient algorithms to solve theoretical problems posed to a programmer. Although these problems usually do not have any real-life significance, they are used to test the skills of a programmer.
A programmer is given multiple problems to solve within defined time and space constraints and is judged on the basis of efficiency and complexity of the code. Most of the technical recruiters hold tests involving programming problems to compare and filter the candidates with the best problem-solving skills.
Apart from the enormous career benefits, competitive programming acts like brain food and helps you to improve your mental strengths. Solving a wide variety of questions within strict time limits improves your focus, optimizes your thought process, and teaches you to handle stressful situations calmly. You get to know the art of concentrating on a task for long and produce the results quickly and accurately.
To communicate their solutions, competitive programmers use computer languages like C, C++, Python, Java, etc. Multiple online testing platforms have come up in recent years that allow a seamless assessment experience. On top of it, these languages provide the programmer with small tools that help in writing and presenting the code of a solution with an easier approach.
Apart from the enormous career benefits, competitive programming acts like brain food and helps you to improve your mental strengths. Solving a wide variety of questions within strict time limits improves your focus, optimizes your thought process, and teaches you to handle stressful situations calmly. You get to know the art of concentrating on a task for long and produce the results quickly and accurately.
To communicate their solutions, competitive programmers use computer languages like C, C++, Python, Java, etc. Multiple online testing platforms have come up in recent years that allow a seamless assessment experience. On top of it, these languages provide the programmer with small tools that help in writing and presenting the code of a solution with an easier approach.
Which Programming Language Should Be Preferred?
There are multiple parameters that define the quality of the solution, including efficiency, the time taken to design the solution, time and space complexity of the solution, etc. As a competitive programmer, one should choose a language that s/he feels would be suitable to get the best combination of these parameters.
Here are some essential things that you need to know about each major language while choosing one-
C/C++
C++ is one of the world’s first coding languages and is taught as a primary computer language in most of the curriculum's. Owing to its simplicity, it’s much faster than the other competitors in the competitive space. For some of the problems designed to be solved in limited time complexity, many times the same solution successfully executes in C++ and not in other higher-level languages.
On top of this, C++ has an excellent set of predefined tools that helps the programmer in efficiently interacting with standard algorithms, data structures, functions, and iterators for solving a problem. This collection of tools is called Standard Template Library (STL), which somehow fits into the demands of a programmer in competitive space.
Java
Java is the most popular programming language by Sun Microsystems. Like STL in C++, Java also has these assisting tools in the form of “Containers”. Although STL is tailor-made for competitive programmers, some programmers prefer containers over STL because in some cases STL doesn’t provide direct solutions.
Comparing the syntax, Java usually takes more lines of code to design the same solution as compared to C++. Hence, Java is preferred if the programmer has prior experience of working in Java.
Java is widely used by developers across multiple domains because of its excellent exception handling techniques. Most of the exceptions can be easily identified, which is not the case in C++. Additionally, Java also enables the programmers to deal with Big Integers and Regular Expressions which helps them to deal with complicated problems.
Python
Python is a high-level language focused on the ease of use and readability of the programmers. Compared to Java and C++, Python usually takes way fewer lines of code to solve a particular problem. Python’s vast range of inbuilt functions makes it easier for programmers to visualize and write the code faster.
Although the time taken to write a code in Python is very less, the compilation time for even a simple program is way too high. Since compilation time is usually considered to be a judging parameter, most of the programmers refrain from Python in those cases.
Python’s syntax is indentation sensitive, which helps fellow programmers to understand the code better. It is used in various applications including Machine Learning, Backend Development, Data Analysis, etc.
The Verdict
The choice of programming language may vary according to the question, the platform, and the experience of the programmer. Experienced Java developers can easily be as good as C++ programmers in the competitive space. But, for beginners, C++ still remains the first choice. Python, on the other hand, can be used in small problems posed by platforms that do not consider the execution time as a judging criterion.
C/C++
C++ is one of the world’s first coding languages and is taught as a primary computer language in most of the curriculum's. Owing to its simplicity, it’s much faster than the other competitors in the competitive space. For some of the problems designed to be solved in limited time complexity, many times the same solution successfully executes in C++ and not in other higher-level languages.
On top of this, C++ has an excellent set of predefined tools that helps the programmer in efficiently interacting with standard algorithms, data structures, functions, and iterators for solving a problem. This collection of tools is called Standard Template Library (STL), which somehow fits into the demands of a programmer in competitive space.
Java
Java is the most popular programming language by Sun Microsystems. Like STL in C++, Java also has these assisting tools in the form of “Containers”. Although STL is tailor-made for competitive programmers, some programmers prefer containers over STL because in some cases STL doesn’t provide direct solutions.
Comparing the syntax, Java usually takes more lines of code to design the same solution as compared to C++. Hence, Java is preferred if the programmer has prior experience of working in Java.
Java is widely used by developers across multiple domains because of its excellent exception handling techniques. Most of the exceptions can be easily identified, which is not the case in C++. Additionally, Java also enables the programmers to deal with Big Integers and Regular Expressions which helps them to deal with complicated problems.
Python
Python is a high-level language focused on the ease of use and readability of the programmers. Compared to Java and C++, Python usually takes way fewer lines of code to solve a particular problem. Python’s vast range of inbuilt functions makes it easier for programmers to visualize and write the code faster.
Although the time taken to write a code in Python is very less, the compilation time for even a simple program is way too high. Since compilation time is usually considered to be a judging parameter, most of the programmers refrain from Python in those cases.
Python’s syntax is indentation sensitive, which helps fellow programmers to understand the code better. It is used in various applications including Machine Learning, Backend Development, Data Analysis, etc.
The Verdict
The choice of programming language may vary according to the question, the platform, and the experience of the programmer. Experienced Java developers can easily be as good as C++ programmers in the competitive space. But, for beginners, C++ still remains the first choice. Python, on the other hand, can be used in small problems posed by platforms that do not consider the execution time as a judging criterion.
Mastering The Art Of Competitive Programming
The journey starts with mastering the basics of the syntax, data types, and operators of the language of your choice. It is highly recommended that a beginner should develop his/her own style of coding, which helps in the debugging process.
Since the problems posed to a programmer includes a considerable variety of approaches that a programmer needs to follow, programmers use commonly defined techniques and structures to solve these problems. This helps the programmer to manage the data in the problem efficiently, and approach the problem in a structured way.
The major ones are-
Data Structures: Data structures are techniques/methods used to store and organize the data efficiently for the ease of access.
Most of the problems require the use of commonly used data structures of different forms listed below-
Arrays: These are the type of data structures which can contain multiple items of the same data type. The length of an array is fixed, and different data points are indexed for random access. Arrays act as the building block for many other data structures and are most commonly used in problems. For mastering the arrays, one should play along with the different operations and functions involving arrays like sorting, searching, etc.
Linked Lists: A linked list is a continuous linear structure in which the consequent elements are linked to the previous element. Due to this dependency, one has to access a data point by going in a sequential method as random access is not possible. One can easily get proficient with the use of linked lists by practicing various possible operations over different types.
Stacks: As the name suggests, these are stacks of datapoints packed in such a way that the element placed at last can be accessed at first. These are majorly used for expression validations and during recursion.
Queues: Queues are, in a sense, the exact opposite of stack, i.e., the element placed at first can be accessed at first, just like a real-life queue of people. These are used to manage threads in multithreading and design a queuing system.
Hashtables: This type of data structure locks the values in storage units that have keys associated with each of them. The keys are either designed by addressing directly or using the hash function, which allows random key values to the data points. They are mostly used to set database indices and sets.
Trees: Trees are used to store the data in hierarchical form, with each data point linked to another. Trees are similar to linked lists, the difference being the non- linearity that they possess.
Various types of trees have been used, and some major ones are- binary search tree, B tree, treap, AVL tree, red-black tree, splay tree, and n-ary tree.
Heap: It is a special type of tree in which the elements are arranged by comparing the parent nodes to their children. Interestingly, they can also be represented in the form of an array.
Implementing a solution using heaps reduces the complexity of many problems and algorithms. Ex- Heapsort.
Graphs: These consist of a defined set of vertices and edges corresponding to them. If all the edges of a graph have a direction indicating what the start vertex is and what is the end vertex, it is said to be a directed graph. And a unidirectional graph if all its edges have no direction.
Apart from these, there are several advanced forms of data structures optimized out of these that are used in some complex problems.
To master the use of data structures, one should practice questions about different operations and functions involving these, and try to think of use cases defined by the limitations of each of the data structures. GeeksForGeeks has an excellent set of articles explaining all of these data structures in detail.
Algorithms
Algorithms are a well-defined set of techniques used to solve various types of problems, involving data structures. Data structures act as a playground for the algorithms and assist in solving complex problems.
There are multiple types of commonly used algorithms like- Sorting, Searching, Recursion,
Dynamic programming, Backtracking, Divide and Conquer, Greedy algorithm, Brute Force, Randomized algorithm, etc.
Unlike data structures, algorithms act as a boost to the problem-solving skills and assist the programmer in structuring his/her thought process in a defined way.
An Informative Webinar by an Ex-Googler, former Google HashCode Country #1 on getting started with Competitive Programming
The journey starts with mastering the basics of the syntax, data types, and operators of the language of your choice. It is highly recommended that a beginner should develop his/her own style of coding, which helps in the debugging process.
Since the problems posed to a programmer includes a considerable variety of approaches that a programmer needs to follow, programmers use commonly defined techniques and structures to solve these problems. This helps the programmer to manage the data in the problem efficiently, and approach the problem in a structured way.
The major ones are-
Data Structures: Data structures are techniques/methods used to store and organize the data efficiently for the ease of access.
Most of the problems require the use of commonly used data structures of different forms listed below-
Linked Lists: A linked list is a continuous linear structure in which the consequent elements are linked to the previous element. Due to this dependency, one has to access a data point by going in a sequential method as random access is not possible. One can easily get proficient with the use of linked lists by practicing various possible operations over different types.
Stacks: As the name suggests, these are stacks of datapoints packed in such a way that the element placed at last can be accessed at first. These are majorly used for expression validations and during recursion.
Queues: Queues are, in a sense, the exact opposite of stack, i.e., the element placed at first can be accessed at first, just like a real-life queue of people. These are used to manage threads in multithreading and design a queuing system.
Hashtables: This type of data structure locks the values in storage units that have keys associated with each of them. The keys are either designed by addressing directly or using the hash function, which allows random key values to the data points. They are mostly used to set database indices and sets.
Trees: Trees are used to store the data in hierarchical form, with each data point linked to another. Trees are similar to linked lists, the difference being the non- linearity that they possess.
Various types of trees have been used, and some major ones are- binary search tree, B tree, treap, AVL tree, red-black tree, splay tree, and n-ary tree.
Heap: It is a special type of tree in which the elements are arranged by comparing the parent nodes to their children. Interestingly, they can also be represented in the form of an array.
Implementing a solution using heaps reduces the complexity of many problems and algorithms. Ex- Heapsort.
Graphs: These consist of a defined set of vertices and edges corresponding to them. If all the edges of a graph have a direction indicating what the start vertex is and what is the end vertex, it is said to be a directed graph. And a unidirectional graph if all its edges have no direction.
Apart from these, there are several advanced forms of data structures optimized out of these that are used in some complex problems.
To master the use of data structures, one should practice questions about different operations and functions involving these, and try to think of use cases defined by the limitations of each of the data structures. GeeksForGeeks has an excellent set of articles explaining all of these data structures in detail.
Algorithms
Algorithms are a well-defined set of techniques used to solve various types of problems, involving data structures. Data structures act as a playground for the algorithms and assist in solving complex problems.
There are multiple types of commonly used algorithms like- Sorting, Searching, Recursion,
Dynamic programming, Backtracking, Divide and Conquer, Greedy algorithm, Brute Force, Randomized algorithm, etc.
Unlike data structures, algorithms act as a boost to the problem-solving skills and assist the programmer in structuring his/her thought process in a defined way.
An Informative Webinar by an Ex-Googler, former Google HashCode Country #1 on getting started with Competitive Programming
Resources for Excelling in Competitive Programming
For theoretical knowledge of the concepts of competitive programming, there are multiple courses, tutorial series, articles, etc. available online.
Books
Books
- Competitive Programmer’s Handbook by Antti Laaksonen: This book teaches the concepts of competitive programming in a seamless way, right from the basics. The reader is able to swiftly solve the assignments while learning new concepts.
- The Algorithm Design Manual by Steven Skiena: This book focuses on techniques that are used while designing solutions based on different data structures.
- Competitive Programmer’s Handbook by Antti Laaksonen: This book teaches the concepts of competitive programming in a seamless way, right from the basics. The reader is able to swiftly solve the assignments while learning new concepts.
- The Algorithm Design Manual by Steven Skiena: This book focuses on techniques that are used while designing solutions based on different data structures.
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