Program for Best Fit algorithm in Memory Management
Last Updated :
23 Jul, 2025
Prerequisite : Partition allocation methods
Best fit allocates the process to a partition which is the smallest sufficient partition among the free available partitions.
Example:
Input : blockSize[] = {100, 500, 200, 300, 600};
processSize[] = {212, 417, 112, 426};
Output:
Process No. Process Size Block no.
1 212 4
2 417 2
3 112 3
4 426 5
Implementation:
1- Input memory blocks and processes with sizes.
2- Initialize all memory blocks as free.
3- Start by picking each process and find the
minimum block size that can be assigned to
current process i.e., find min(bockSize[1],
blockSize[2],.....blockSize[n]) >
processSize[current], if found then assign
it to the current process.
5- If not then leave that process and keep checking
the further processes.
Below is implementation.
C++
// C++ implementation of Best - Fit algorithm
#include<iostream>
using namespace std;
// Method to allocate memory to blocks as per Best fit algorithm
void bestFit(int blockSize[], int m, int processSize[], int n)
{
// Stores block id of the block allocated to a process
int allocation[n];
// Initially no block is assigned to any process
for (int i = 0; i < n; i++)
allocation[i] = -1;
// pick each process and find suitable blocks
// according to its size ad assign to it
for (int i = 0; i < n; i++)
{
// Find the best fit block for current process
int bestIdx = -1;
for (int j = 0; j < m; j++)
{
if (blockSize[j] >= processSize[i])
{
if (bestIdx == -1)
bestIdx = j;
else if (blockSize[bestIdx] > blockSize[j])
bestIdx = j;
}
}
// If we could find a block for current process
if (bestIdx != -1)
{
// allocate block j to p[i] process
allocation[i] = bestIdx;
// Reduce available memory in this block.
blockSize[bestIdx] -= processSize[i];
}
}
cout << "\nProcess No.\tProcess Size\tBlock no.\n";
for (int i = 0; i < n; i++)
{
cout << " " << i+1 << "\t\t" << processSize[i] << "\t\t";
if (allocation[i] != -1)
cout << allocation[i] + 1;
else
cout << "Not Allocated";
cout << endl;
}
}
// Driver Method
int main()
{
int blockSize[] = {100, 500, 200, 300, 600};
int processSize[] = {212, 417, 112, 426};
int m = sizeof(blockSize) / sizeof(blockSize[0]);
int n = sizeof(processSize) / sizeof(processSize[0]);
bestFit(blockSize, m, processSize, n);
return 0 ;
}
// Java implementation of Best - Fit algorithm
public class GFG
{
// Method to allocate memory to blocks as per Best fit
// algorithm
static void bestFit(int blockSize[], int m, int processSize[],
int n)
{
// Stores block id of the block allocated to a
// process
int allocation[] = new int[n];
// Initially no block is assigned to any process
for (int i = 0; i < allocation.length; i++)
allocation[i] = -1;
// pick each process and find suitable blocks
// according to its size ad assign to it
for (int i=0; i<n; i++)
{
// Find the best fit block for current process
int bestIdx = -1;
for (int j=0; j<m; j++)
{
if (blockSize[j] >= processSize[i])
{
if (bestIdx == -1)
bestIdx = j;
else if (blockSize[bestIdx] > blockSize[j])
bestIdx = j;
}
}
// If we could find a block for current process
if (bestIdx != -1)
{
// allocate block j to p[i] process
allocation[i] = bestIdx;
// Reduce available memory in this block.
blockSize[bestIdx] -= processSize[i];
}
}
System.out.println("\nProcess No.\tProcess Size\tBlock no.");
for (int i = 0; i < n; i++)
{
System.out.print(" " + (i+1) + "\t\t" + processSize[i] + "\t\t");
if (allocation[i] != -1)
System.out.print(allocation[i] + 1);
else
System.out.print("Not Allocated");
System.out.println();
}
}
// Driver Method
public static void main(String[] args)
{
int blockSize[] = {100, 500, 200, 300, 600};
int processSize[] = {212, 417, 112, 426};
int m = blockSize.length;
int n = processSize.length;
bestFit(blockSize, m, processSize, n);
}
}
# Python3 implementation of Best - Fit algorithm
# Function to allocate memory to blocks
# as per Best fit algorithm
def bestFit(blockSize, m, processSize, n):
# Stores block id of the block
# allocated to a process
allocation = [-1] * n
# pick each process and find suitable
# blocks according to its size ad
# assign to it
for i in range(n):
# Find the best fit block for
# current process
bestIdx = -1
for j in range(m):
if blockSize[j] >= processSize[i]:
if bestIdx == -1:
bestIdx = j
elif blockSize[bestIdx] > blockSize[j]:
bestIdx = j
# If we could find a block for
# current process
if bestIdx != -1:
# allocate block j to p[i] process
allocation[i] = bestIdx
# Reduce available memory in this block.
blockSize[bestIdx] -= processSize[i]
print("Process No. Process Size Block no.")
for i in range(n):
print(i + 1, " ", processSize[i],
end = " ")
if allocation[i] != -1:
print(allocation[i] + 1)
else:
print("Not Allocated")
# Driver code
if __name__ == '__main__':
blockSize = [100, 500, 200, 300, 600]
processSize = [212, 417, 112, 426]
m = len(blockSize)
n = len(processSize)
bestFit(blockSize, m, processSize, n)
# This code is contributed by PranchalK
// C# implementation of Best - Fit algorithm
using System;
public class GFG {
// Method to allocate memory to blocks
// as per Best fit
// algorithm
static void bestFit(int []blockSize, int m,
int []processSize, int n)
{
// Stores block id of the block
// allocated to a process
int []allocation = new int[n];
// Initially no block is assigned to
// any process
for (int i = 0; i < allocation.Length; i++)
allocation[i] = -1;
// pick each process and find suitable
// blocks according to its size ad
// assign to it
for (int i = 0; i < n; i++)
{
// Find the best fit block for
// current process
int bestIdx = -1;
for (int j = 0; j < m; j++)
{
if (blockSize[j] >= processSize[i])
{
if (bestIdx == -1)
bestIdx = j;
else if (blockSize[bestIdx]
> blockSize[j])
bestIdx = j;
}
}
// If we could find a block for
// current process
if (bestIdx != -1)
{
// allocate block j to p[i]
// process
allocation[i] = bestIdx;
// Reduce available memory in
// this block.
blockSize[bestIdx] -= processSize[i];
}
}
Console.WriteLine("\nProcess No.\tProcess"
+ " Size\tBlock no.");
for (int i = 0; i < n; i++)
{
Console.Write(" " + (i+1) + "\t\t"
+ processSize[i] + "\t\t");
if (allocation[i] != -1)
Console.Write(allocation[i] + 1);
else
Console.Write("Not Allocated");
Console.WriteLine();
}
}
// Driver Method
public static void Main()
{
int []blockSize = {100, 500, 200, 300, 600};
int []processSize = {212, 417, 112, 426};
int m = blockSize.Length;
int n = processSize.Length;
bestFit(blockSize, m, processSize, n);
}
}
// This code is contributed by nitin mittal.
function bestFit(blockSize, m, processSize, n) {
// Stores block id of the block allocated to a process
let allocation = new Array(n).fill(-1);
// Pick each process and find suitable blocks according to its size and assign to it
for (let i = 0; i < n; i++) {
// Find the best fit block for current process
let bestIdx = -1;
for (let j = 0; j < m; j++) {
if (blockSize[j] >= processSize[i]) {
if (bestIdx === -1) {
bestIdx = j;
} else if (blockSize[bestIdx] > blockSize[j]) {
bestIdx = j;
}
}
}
// If we could find a block for current process
if (bestIdx !== -1) {
// Allocate block j to p[i] process
allocation[i] = bestIdx;
// Reduce available memory in this block.
blockSize[bestIdx] -= processSize[i];
}
}
console.log("Process No. Process Size Block no.");
for (let i = 0; i < n; i++) {
console.log(`${i + 1} ${processSize[i]} ${allocation[i] !== -1 ? allocation[i] + 1 : "Not Allocated"}`);
}
}
// Driver code
let blockSize = [100, 500, 200, 300, 600];
let processSize = [212, 417, 112, 426];
let m = blockSize.length;
let n = processSize.length;
bestFit(blockSize, m, processSize, n);
Output:
Process No. Process Size Block no.
1 212 4
2 417 2
3 112 3
4 426 5
The time complexity of Best-Fit algorithm is O(n2) as it requires two loops to process the memory blocks and processes. The outer loop is used to iterate through the processes and the inner loop is used to iterate through the blocks.
The space complexity of Best-Fit algorithm is O(n) as it requires an array of size n to store the block allocation for each process.
Is Best-Fit really best?
Although, best fit minimizes the wastage space, it consumes a lot of processor time for searching the block which is close to required size. Also, Best-fit may perform poorer than other algorithms in some cases. For example, see below exercise.
Example: Consider the requests from processes in given order 300K, 25K, 125K and 50K. Let there be two blocks of memory available of size 150K followed by a block size 350K.
Best Fit:
300K is allocated from block of size 350K. 50 is left in the block.
25K is allocated from the remaining 50K block. 25K is left in the block.
125K is allocated from 150 K block. 25K is left in this block also.
50K can’t be allocated even if there is 25K + 25K space available.
First Fit:
300K request is allocated from 350K block, 50K is left out.
25K is be allocated from 150K block, 125K is left out.
Then 125K and 50K are allocated to remaining left out partitions.
So, first fit can handle requests.
First Fit, Best Fit, Next Fit and Worst Fit Algorithms in OS
Visit Course
Similar Reads
Basics & Prerequisites
Data Structures
Array Data StructureIn this article, we introduce array, implementation in different popular languages, its basic operations and commonly seen problems / interview questions. An array stores items (in case of C/C++ and Java Primitive Arrays) or their references (in case of Python, JS, Java Non-Primitive) at contiguous
3 min read
String in Data StructureA string is a sequence of characters. The following facts make string an interesting data structure.Small set of elements. Unlike normal array, strings typically have smaller set of items. For example, lowercase English alphabet has only 26 characters. ASCII has only 256 characters.Strings are immut
2 min read
Hashing in Data StructureHashing is a technique used in data structures that efficiently stores and retrieves data in a way that allows for quick access. Hashing involves mapping data to a specific index in a hash table (an array of items) using a hash function. It enables fast retrieval of information based on its key. The
2 min read
Linked List Data StructureA linked list is a fundamental data structure in computer science. It mainly allows efficient insertion and deletion operations compared to arrays. Like arrays, it is also used to implement other data structures like stack, queue and deque. Here’s the comparison of Linked List vs Arrays Linked List:
2 min read
Stack Data StructureA Stack is a linear data structure that follows a particular order in which the operations are performed. The order may be LIFO(Last In First Out) or FILO(First In Last Out). LIFO implies that the element that is inserted last, comes out first and FILO implies that the element that is inserted first
2 min read
Queue Data StructureA Queue Data Structure is a fundamental concept in computer science used for storing and managing data in a specific order. It follows the principle of "First in, First out" (FIFO), where the first element added to the queue is the first one to be removed. It is used as a buffer in computer systems
2 min read
Tree Data StructureTree Data Structure is a non-linear data structure in which a collection of elements known as nodes are connected to each other via edges such that there exists exactly one path between any two nodes. Types of TreeBinary Tree : Every node has at most two childrenTernary Tree : Every node has at most
4 min read
Graph Data StructureGraph Data Structure is a collection of nodes connected by edges. It's used to represent relationships between different entities. If you are looking for topic-wise list of problems on different topics like DFS, BFS, Topological Sort, Shortest Path, etc., please refer to Graph Algorithms. Basics of
3 min read
Trie Data StructureThe Trie data structure is a tree-like structure used for storing a dynamic set of strings. It allows for efficient retrieval and storage of keys, making it highly effective in handling large datasets. Trie supports operations such as insertion, search, deletion of keys, and prefix searches. In this
15+ min read
Algorithms
Searching AlgorithmsSearching algorithms are essential tools in computer science used to locate specific items within a collection of data. In this tutorial, we are mainly going to focus upon searching in an array. When we search an item in an array, there are two most common algorithms used based on the type of input
2 min read
Sorting AlgorithmsA Sorting Algorithm is used to rearrange a given array or list of elements in an order. For example, a given array [10, 20, 5, 2] becomes [2, 5, 10, 20] after sorting in increasing order and becomes [20, 10, 5, 2] after sorting in decreasing order. There exist different sorting algorithms for differ
3 min read
Introduction to RecursionThe process in which a function calls itself directly or indirectly is called recursion and the corresponding function is called a recursive function. A recursive algorithm takes one step toward solution and then recursively call itself to further move. The algorithm stops once we reach the solution
14 min read
Greedy AlgorithmsGreedy algorithms are a class of algorithms that make locally optimal choices at each step with the hope of finding a global optimum solution. At every step of the algorithm, we make a choice that looks the best at the moment. To make the choice, we sometimes sort the array so that we can always get
3 min read
Graph AlgorithmsGraph is a non-linear data structure like tree data structure. The limitation of tree is, it can only represent hierarchical data. For situations where nodes or vertices are randomly connected with each other other, we use Graph. Example situations where we use graph data structure are, a social net
3 min read
Dynamic Programming or DPDynamic Programming is an algorithmic technique with the following properties.It is mainly an optimization over plain recursion. Wherever we see a recursive solution that has repeated calls for the same inputs, we can optimize it using Dynamic Programming. The idea is to simply store the results of
3 min read
Bitwise AlgorithmsBitwise algorithms in Data Structures and Algorithms (DSA) involve manipulating individual bits of binary representations of numbers to perform operations efficiently. These algorithms utilize bitwise operators like AND, OR, XOR, NOT, Left Shift, and Right Shift.BasicsIntroduction to Bitwise Algorit
4 min read
Advanced
Segment TreeSegment Tree is a data structure that allows efficient querying and updating of intervals or segments of an array. It is particularly useful for problems involving range queries, such as finding the sum, minimum, maximum, or any other operation over a specific range of elements in an array. The tree
3 min read
Pattern SearchingPattern searching algorithms are essential tools in computer science and data processing. These algorithms are designed to efficiently find a particular pattern within a larger set of data. Patten SearchingImportant Pattern Searching Algorithms:Naive String Matching : A Simple Algorithm that works i
2 min read
GeometryGeometry is a branch of mathematics that studies the properties, measurements, and relationships of points, lines, angles, surfaces, and solids. From basic lines and angles to complex structures, it helps us understand the world around us.Geometry for Students and BeginnersThis section covers key br
2 min read
Interview Preparation
Practice Problem