# Best Data Structures and Algorithms Notes for Placement – 2021

Data Structures and Algorithms Notes for Placement

## Data Structures

Please check the tutorial section on the various data structures for more information. Data structures represent an efficient way of managing data in a computer system in order to enable efficient operations. The pages present instructions on data structures in detail.

There are questions related to:

## Data Structures – Asymptotic Analysis

Asymptotic analysis is the process of calculating the running time of an algorithm in mathematical units to find the program’s limitations, or “run-time performance.” The goal is to determine the best case, worst case and average case time required to execute a given task. While not a method of deep learning training, Asymptotic analysis is a crucial diagnostic tool for programmers to evaluate an algorithm’s efficiency, rather than just its accuracy.

## Space Complexity

The space complexity of an algorithm or a computer program is the amount of memory space required to solve an instance of the computational problem as a function of characteristics of the input. It is the memory required by an algorithm until it executes completely.

## Algorithm analysis

Analysis of algorithms is the determination of the amount of time and space resources required to execute it.

## Need for Data Structure

The need of Data Structure includes efficiency and reusability. Data structure provides a way of organizing, managing, and storing data efficiently. With the help of data structure, the data items can be traversed easily.

## Execution Time Cases

The time spent by the job actively using processor resources is its execution time. The execution time of each job instance from the same task is likely to differ. Execution times are of interest to real-time systems designers usually in the context of worst-case execution times.

• Unambiguous
• Input
• Output
• Finiteness
• Feasibility
• Independent

## Tell me the best way to write algorithms?

• Obtaining a description of the problem.
• Analyzing the problem.
• Developing a high-level algorithm.
• Refining the algorithm by adding more detail.
• Reviewing the algorithm.

## Algorithm Complexity

Algorithmic complexity is a measure of how long an algorithm would take to complete given an input of size n.

## Time Complexity

Time required to analyze the given problem of particular size is known as the time complexity

## Installation on UNIX/Linux

1. sudo apt install GCC.
2. GCC — version.
3. cd Desktop.
4. Key takeaway: Commands are case sensitive.
5. touch program.c.
6. GCC program.c -o program.
7. Key takeaway: The executable file name can be different from the source file name.
8. ./program.

## Characteristics of a Data Structure

• Linear
• Non-Linear
• Static
• Homogenous
• Non-Homogenous
• Dynamic
• Time Complexity
• Space Complexity

## Tell me the use of data structure?

• Data Structures allow programmers to manage the data in the most efficient manner that enhances the algorithm’s performance.
• They allow the implementation of a scientific approach as against traditional methodologies. When it comes to aspects such as processing speed, handling or multiple requests and searching through numerous records, data structures prove handy.
• They allow efficient use of memory. Data structures optimize memory usage. This makes an impact usually in situations that involve the processing of huge datasets.
• Data structures are reusable. They can be integrated as a package into a library. These libraries can be used in various situations by various stakeholders as needed.
• They allow multiple solutions for a particular problem, allowing the user to select the data structure to solve the problem in the best way.