Introduction to Algorithms and its basics in data structures

algorithmsThe algorithm is a word it is derived from the name “Al-Khawarizmi“. Al-Khawarizmi is a 9th century Persian mathematician and author of the book used for calculation by integration and balancing. But in these days the word algorithm is used for step-by-step method to solve a problems. But in algorithms everytime we will not use that step-by-step method because some cases are complicated.

An algorithm can be created in any programming language. Algorithms are not dependent of basic or any languages and algorithms are generally created.

Categories of an Algorithms

algorithmsSearch– Search algorithm is used for searching an item or component in data strcuture.

Sort– Sort algorithm is used for sorting an item or component in ascending or descending(certain) order.

Insert– This is used for inserting an element or an item in a data structure.

Update– This is used to update the actual or current existing element in data structure.

Delete– This is used to delete the current element in data structure.

Features of an Algorithm

Not every process is an algorithm. An algorithm should accept some following six features in data structures:

  1. Definiteness
  2. Finiteness
  3. Input
  4. Output
  5. Feasibleness
  6. Independent

1. Definiteness:  Algorithm must be clear and definite. In this steps are definitely stated or defined(precisely). Each and every steps and their inputs and outputs must be clear and definite.

2. Finiteness: An algorithm breaks after a finite set of instructions or programs when they are carried out that means it aborts after a finite set of programs.

3. Input: Algorithm must have 0 input or more distinct or clear-cut inputs. It collects the input.

4. Output: Algorithm must have 1 output or more distint or clear-cut outputs and it should not match with the applicable or appropriate output. It outcomes or produces the output.

5. Feasibleness: It means it must be suitable with possible or available resources.

6. Independent: An algorithm should have step-by-step directions, which should not be dependent of any programming code. These results are differently or uniquely defined.

How to Create an Algorithm?

What is an Algorithm?There are no clear-cut standards for creating an algorithms. Rather, it is problem and it is not an resource independent. Algorithms are not used for writing an programming code.

We know that every programming languages can have essential code constructs like loops (do, for, while), flow-control (if-else), etc. These are very common instructions will be used to create an algorithm.

Generally an algorithm is used in a step-by-step procedure, but algorithm will not use this procedure every time. Algorithm is a technique and is executed after the issue is clear-cut. That means, an algorithm is used to design a explanation and clarification for the issues in an well-defined way.






Introduction for Data Structures and Algorithms – Overview


Structures and Algorithms

Data Structure is a way of compiling and coordinating data in such a way that we can perform operations on these data in an accurate way.

Interface: Each and every data structure has an interface. It implements the set of operations that a data structure holds. It only implements the list of authorized operations, type of parameters they can acquire and return type of these operations.

DeploymentDeployment provides the internal depiction of a data structure that means the internal representations.

Aspects of a Data Structure:

These are the three main Characteristics of a Data Structures and Algorithms. They are:

1. Definiteness

2.Time Complexity

3.Space Complexity


Definiteness: Data structure arrangement should arrange and implement its interface definitely.

Structures and algorithmsTime Complexity: The Running time and  the execution or achievement time of operations of data structure must be as low as possible.

Space Complexity: The usage of memory should be as little as possible in data structure operations.

Use for Data Structure:

The applications are getting complicated and data rich or heavy, there are three common problems that applications facing now-a-days.

Data Search: Suppose consider an inventory of 1 million components of a store. If the application is to search an component, it has to search an component in 1 million components every time will slow down the search. As data grows up, search will becomes inactive or slow.

Processor speed: Inspite of that Processor speed is being very high, decreases finite if the data grows to billion records.

Multiple requests: The users they can search data concurrently in an internet, at that time even a quick server can get slow when the users are searching the data.

To clairfy the above-mentioned problems, data structures come to recovery. Data can be standardized in a data structure in such a way that all components may not be required to be searched, and the required data can be searched almost directly.

Execution Time Cases:

Structures and AlgorithmsThere are three cases which are consistently used or need to correlate distinct data structure’s execution time in a relative manner.They are three case complexities:

1.Worst Case

2.Average Case

3.Best Case

1.Worst Case:  Where a particular data structure operation takes more time for execution is worst case.

2.Average Case: Illustrating the average execution time of an operations.

3.Best Case: Illustrating the least execution time of an operations.

Basic Terminologies in Data Structures and Algorithms:

Data– These are set of values.

Data Component– These are single unit values.

Group Items– Data items splits into sub items are known as Group items.

Elementary Items– Which Data items that cannot be splits into sub items are known as Elementary Items.

Attribute and Entity– An entity is that which consist of certain attributes or properties, which may be assigned values.

Entity Set– Entities of similar attributes form an entity set.

Field– It is a single elementary unit of instruction defining an attribute of an entity.

Record– It is a collection of field values in a given entity.

File– It is a collection of records of entities in a given entity set.