3-days-masterclass

badges

c-code

chaquopy-matplotlib

Chaquopy Matplotlib example

cpp

cupid-react

do101-apps

educate

email_classification

events-and-hackathons

Collection of Events and Hackathons. Add you contribution by just opening an issue or PR. No Code Repo for Hacktoberfest.

gradio_ml_careercompass

healthcare

healthweb1.0

healthweb1.1

healthweb2.0

hello-nodejs

ieducate

java_programming

javascript-5thsem

learn-git

learning git and its functionalities

leetcode

my-calculatorapp-demo

First app developement using Android Studio

node

os-memory-allocation-algorithms-simulation

The two programs included in this repository simulate the Buddy System, First Fit, Next Fit, Best Fit and Worst Fit memory allocation algorithms used in numerous operating systems. Tree data structure was used for the implementation of buddy system where as two separate doubly link lists have been used to keep the record of the holes and the memory allocated to the processes in case of First Fit, Next Fit, Best Fit and Worst Fit algorithms simulation. The buddy system is a memory allocation and management algorithm that manages memory in power of two increments. In the first fit, the approach is to allocate the first free partition or hole large enough which can accommodate the request. It finishes after finding the first suitable free partition. The best fit deals with allocating the smallest free partition which meets the requirement. This algorithm first searches the entire list of free partitions and considers the smallest hole that is adequate. Next fit is a modified version of first fit. It begins as first fit to find a free partition. When called the next time it starts searching from where it left off instead of the beginning. In case of worst fit, the approach is to locate largest available free partition so that the left over portion will be big enough to be useful again.

pankaj-sadhukhan

programming-c-cpp-sem1

python

scaler-september-open-source-challenge

Scaler September Open Source Challenge

webdev