Memento Design Pattern explained with simple example

The Memento design pattern basically stores the various states of the system and provides the ability to restore the system in some previous state. This design pattern allows software to storing store various state which can be used for retracing or can be used to go back to some previous state in case something goes wrong. Also, auditing related procedures also can be done using this design pattern.

Before going ahead have a look at Design pattern simplified version.

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Mediator Design Pattern explained with simple example

Mediator design pattern basically defines an interface class which provides a mechanism for providing communication between various modules/components of the software. Since, mediator needs to access each component of the software, which means it should be added as a reference in each component. Using this mediator class components becomes less dependent on each other which means coupling is reduced.

Before going ahead have a look at Design pattern simplified version.

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Iterator Design Pattern explained with simple example

An iterator is an object which allows a developer to easily traverse through a container class. The Iterator design pattern is relatively simple and easy to implement kind of design pattern in which an iterator is used to traverse through a complex container in order to access the elements of the container. This design pattern tries to decouple container classes from the other modules in order to achieve low coupling.

Before going ahead, have a look at Design pattern simplified version.

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Print longest common subsequence string of two string

The longest subsequence problem (LCS) is the problem in which we need to find the longest subsequence present in two sequences. In this case, characters doesn’t require to be in consecutive places.

For eg:

LCS for sequence “ABCDFG” and “ABCGDFG” is “ABCDFG” and its length is 6.

For calculating longest common subsequence length we can use recursion or dynamic programming, here we are going to see how to find the longest common subsequence string.

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Longest common subsequence problem using dynamic programming

This problem can be solved using multiple approaches but here we will solve this problem using Dynamic Programming and showcase how dynamic programming will make the execution super-fast.

We will go through with the same steps as mentioned in Dynamic Programming post to tackle this problem step by step for better understanding.

Let’s explain the problem,

The longest subsequence problem (LCS) is the problem in which we need to find the longest subsequence present in two sequences. In this case, characters doesn’t require to be in consecutive places.

For eg:

LCS for sequence “ABCDFG” and “ABCGDFG” is “ABCDFG” and its length is 6.

Let’s apply the 3 Steps rule (Dynamic Programming) to tackle this problem.

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Converting Roman number to Decimal using Interpreter design pattern

Interpreter design pattern is mainly used in compiler and other language processing programs. This design pattern used to identify various language mainly textual such as numbers, regular expression etc. This design pattern interprets every language syntax and assign a class accordingly, to do further processing.

Before going ahead have a look at Design pattern simplified version.

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Interpreter Design Pattern explained with simple example

Interpreter design pattern is mainly used in compiler and other language processing programs. This design pattern used to identify various language mainly textual such as numbers, regular expression etc. This design pattern interprets every language syntax and assign a class accordingly, to do further processing.

Before going ahead have a look at Design pattern simplified version.

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Monostate Design Pattern explained with simple example

Monostate design pattern is a singleton design pattern variation in which a class will act like a singleton but this class will look like a normal class. This design pattern states that all data member of monostate classes are static but any number of instances can be created in the program.

Before going ahead have a look at Design pattern simplified version and Singleton design pattern.

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Dependency Inversion Principle explained with simple example

Dependency Inversion Principle (DIP) is a software design principle which states that “High-level modules should not depend on low-level modules. Both should depend on abstractions And Abstractions should not depend on details. Details should depend on abstractions“. This design principle ensures a lower coupling between different classes.

Before going ahead we should know why do we need software design principle and what is software design principle.

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