👨‍💻
Cracking-Interview
  • Data Structures and Algorithms
  • Arrays
    • 1. Two Sums
    • 2. Rotate Array
    • 3.Remove Duplicates from sorted array
    • 4.Merge Two Sorted Array
    • 5.Majority Element
    • 6.Rotate Image
    • 7.Merge Intervals
    • 8.Increasing Triplet Subsequence
    • 9.Set Matrix Zeroes
    • 10.Product of Array Except Self
    • 11.Container With Most Water
    • 12.Next Permutation
    • 13.Next Greater Element III
    • 14.Largest Number
    • 15.Candy
    • 16.Shortest Unsorted Continuous Subarray
    • 17.Sort Colors(Sort array of 0, 1, 2)
    • 18.Queue Reconstruction by Height
    • 19.Task Scheduler
    • 20.Trapping Rain Water
    • 21.Search a 2D Matrix II
    • 22. Spiral Matrix
    • 23.Median of Two Sorted Arrays
    • 24.Count inversion of an array
    • 25. Reverse Pairs
    • 26. Count Servers that Communicate
    • 27. 3Sum
    • 28. 4Sum
    • 29. Game of Life
    • 30. Sort the Matrix Diagonally
    • 31. Push Dominoes
    • 32. Corporate Flight Bookings
    • 33. Rotating the Box
    • 34. Interval List Intersections
    • 35. Insert Interval
    • 36. Minimum Moves to Equal Array Elements II
    • 37. Pairs of Songs With Total Durations Divisible by 60
    • 38. Remove Covered Intervals
    • Juggling Algorithm
    • Moore’s Voting Algorithm
    • Two Pointer Method
  • Linked List
    • 1.Odd-Even Linked List
    • 2.Add Two Numbers
    • 3. Insert in a Sorted List
    • 4.Rotate List
    • 5.Palindrome Linked List
    • 6.Point of insertion between two Linked List
    • 7.Delete Node in a Linked List
    • 8.Middle of the Linked List
    • 9.Linked List Cycle
    • 10. Swapping Nodes in a Linked List
    • 11.Swap Nodes in Pairs
    • 12.Merge Two Sorted Lists
    • 13.Reverse a Linked List
    • 14. Reverse Linked List II
    • 15.Copy List with Random Pointer
    • 16.Remove Duplicates from Sorted List
    • 17. Merge k Sorted Lists
    • 18. Remove Nth Node From End of List
    • 19. Sort List
    • 20. Reverse Nodes in k-Group
    • 21. Partition List
    • 22. Flattening a Linked List
    • Basic Implementation of Singly Linked List
    • Basic Implementation of Doubly Linked List
  • Strings
    • 1.Reverse Words in a String
    • 2. Is Subsequence
    • 3.Valid Anagram
    • 4.Add Binary
    • 5.Longest Common Prefix
    • 7.Valid Palindrome
    • 8.Implement strStr()
    • 9.String to Integer (atoi)
    • 10.Count and Say
    • 11.Longest Substring Without Repeating Characters
    • 12. Longest Substring with At Most K Distinct Characters
    • 13. Longest Substring with At Least K Repeating Characters
    • 14. Find All Anagrams in a String
    • 15. Permutation in String
    • 16. Maximum Number of Vowels in a Substring of Given Length
    • 17. Partition Labels
    • 18. Minimum Window Substring
    • 19. Compare Version Numbers
    • 20. Shortest Distance to a Character
    • 21. Count Number of Homogenous Substrings
    • 22. Remove Duplicate Letters
    • 23. Count Sorted Vowel Strings
    • 24. Get Equal Substrings Within Budget
    • 25. Sentence Similarity III
    • 26. Shifting Letters
    • 27. Longest Happy Prefix (imp)
    • 28. Sort Characters By Frequency
    • 29. String Compression
    • 30. Palindrome Pairs
    • 31. Shortest Palindrome(Imp)
    • 32. One Edit Distance
    • 33. Can Make Palindrome from Substring
    • 34. Greatest Common Divisor of Strings
    • KMP Algorithm for Pattern Searching
    • Rabin-Karp Algorithm for Pattern Searching
  • Binary Tree
    • Terminology and Formula
    • N-ary Tree
      • 1. N-ary Tree Preorder Traversal
      • 2. N-ary Tree Postorder Traversal
      • 3. N-ary Tree Level Order Traversal
    • Tree Traversals
      • 1.In-order Traversal
      • 2.Pre-order Traversal
      • 3.Post-order Traversal
      • 4.Level-order Traversal
      • 5.Vertical Order Traversal
      • 6. Binary Tree Level Order Traversal II
    • Problems Related to Binary Trees
      • 1.Maximum/Minimum Depth of Binary Tree
      • 2.Lowest Common Ancestor of a Binary Tree
      • 3.Symmetric Tree
      • 4.Path Sum
      • 5.Tree : Top View
      • 6. Diameter of Binary Tree
      • 7.Populating Next Right Pointers in Each Node
      • 8.Balanced Binary Tree
      • 9.Binary Tree Zigzag Level Order Traversal
      • 10.Invert Binary Tree
      • 11.Binary Tree Right Side View
      • 12.Validate Binary Tree Nodes
      • 13.Merge Two Binary Trees
      • 14.Flatten Binary Tree to Linked List
      • 15. Construct Binary Tree from Preorder and Inorder Traversal
      • 16. Construct Binary Tree from Inorder and Postorder Traversal
      • 17. Binary Tree Maximum Path Sum
      • 18. Sum Root to Leaf Numbers
      • 19. Subtree of Another Tree
      • 20. Even Odd Tree
      • 21. Delete Nodes And Return Forest
      • 22. Maximum Binary Tree
      • 23. Linked List in Binary Tree
      • 24. Longest Univalue Path
      • 25. Sum of Distances in Tree
      • 26. Distribute Coins in Binary Tree
      • 27. Find Duplicate Subtrees
      • 28. Serialize and Deserialize BST
      • 29. Serialize and Deserialize Binary Tree
      • 30. Path Sum III
      • 31. Delete Leaves With a Given Value
      • 32. All Possible Full Binary Trees
      • 33. All Nodes Distance K in Binary Tree
      • 34. Maximum Width of Binary Tree
  • Stack and Queue
    • Problems
      • 1.Min Stack
      • 2. Max Stack
      • 3.Valid Parentheses
      • 4.Evaluate Reverse Polish Notation
      • 5.Infix And Prefix and Postfix Conversions
      • 6.Next Greater Element I
      • 7.Next Greater Element II
      • 8.Sliding Window Maximum
      • 9.Gas Station (Circular Tour Problem)
      • 10.Daily Temperatures
      • 11.Decode String
      • 12. Largest Rectangle in Histogram
      • 13. Maximal Rectangle
      • 14. Minimum Remove to Make Valid Parentheses
      • 15. Map of Highest Peak
      • 16. Longest Valid Parentheses
      • 17. Online Stock Span
      • 18. Score of Parentheses
      • 19. Remove K Digits(imp)
      • 20. Design a Stack With Increment Operation
      • 21. Final Prices With a Special Discount in a Shop
      • 22. Valid Parenthesis String
      • 23. Reveal Cards In Increasing Order
      • 24. Remove All Adjacent Duplicates In String
      • 25. Number of Visible People in a Queue
      • 26.Number following a pattern
    • Implementation
      • Implementation of Queue
      • Implementation of Stack
      • Implementation of Circular Queue
      • Implement Queue using Stacks
      • Implement Stack using Queues
  • Hash Table
    • Designing and Definitions
      • Techniques of hashing and collision resolution
      • Design HashSet
      • Design HashMap
    • Problems
      • 1.Intersection of Two Arrays
      • 2.Happy Number
      • 3.Contains Duplicate
      • 4.Find the Duplicate Number
      • 5. Find All Duplicates in an Array
      • 6. Isomorphic Strings
      • 7. Group Anagrams
      • 8. Single Number
      • 9.Valid Sudoku
      • 10.Jewels and Stones
      • 11.First Missing Positive
      • 12. LRU Cache (V.IMP)
      • 13. Encode and Decode TinyURL
      • 14. Alphabet Board Path
  • Binary Search
    • Template I
      • Basic Binary Search
      • 1.Search in a Sorted Rotated Array
      • 5.Sqrt(x)
    • Template II
      • 2.Find Minimum in Rotated Sorted Array
    • Template III
      • 3.Find Peak Element
      • 4. Find First and Last Position of Element in Sorted Array
  • Binary Search Tree
    • 1.Is This a Binary Search Tree
    • 2.Search in a Binary Search Tree
    • 3.Insert into a Binary Search Tree
    • 4.Delete Node in a BST
    • 5.Lowest Common Ancestor of a Binary Search Tree
    • 6.Construct Binary Search Tree from Preorder Traversal
    • 7.Convert Sorted Array to Binary Search Tree
    • 8. Convert Sorted List to Binary Search Tree
    • 9.Kth Smallest Element in a BST
    • 10.Trim a Binary Search Tree
    • 11.Two Sum IV - Input is a BST
    • 12. Binary Search Tree to Greater Sum Tree / Greater Tree
    • 13. Balance a Binary Search Tree
    • 14. Binary Search Tree Iterator
    • 15. Unique Binary Search Trees
    • 16. Unique Binary Search Trees II
    • 17. Inorder Successor in BST
  • Bit manipulation
    • Bitwise Operations
    • 1.Reverse Bits
    • 2.Counting Bits
    • 3.Number of 1 Bits
    • 4.Hamming Distance
    • 5. Power of Two
    • 6. Complement of Base 10 Integer
  • Graph
    • 1.Maximum number of edges to be removed to contain exactly K connected components in the Graph
    • 2. Social Networking Graph
    • 3.The Flight Plan
    • 4.Is it a tree?
    • 5.Possible Bipartition
    • 6.Longest path in an undirected tree
    • 7.Keys and Rooms
    • 8.Is Graph Bipartite?
    • 9.Number of Islands
    • 10. Number of Provinces
    • 11.Surrounded Regions
    • 12. All Paths From Source to Target
    • 13.Word Ladder
    • 14.Rotting Oranges
    • 15.Course Schedule
    • 16.Course Schedule II
    • 17. Minimum Number of Vertices to Reach All Nodes
    • 18.Network Delay Time
    • 19. 01 Matrix
    • 20. Cheapest Flights Within K Stops
    • 21. Critical Connections in a Network
    • 22.Word Search
    • 23. Minimum Time to Collect All Apples in a Tree
    • 24. Time Needed to Inform All Employees
    • 25. As Far from Land as Possible
    • 26. Clone Graph
    • 27. Min Cost to Connect All Points
    • 28. Find the City With the Smallest Number of Neighbors at a Threshold Distance
    • 29. Number of Operations to Make Network Connected
    • 30. Open the Lock
    • 31. Word Search II
    • 32. Number of Ways to Arrive at Destination
    • 33. Knight On Chess Board
    • 34. Shortest Bridge
    • 35. Pacific Atlantic Water Flow
    • 36. Making A Large Island
    • 37. Path with Maximum Probability
    • Graph Algorithms
      • 1.DFS
      • 2.BFS
      • 3.Prim's MST
      • 4.Kruskal (MST)
      • 5.Dijkstra’s Algorithm(Single Source Shortest Path)
      • 6. Floyd Warshall's Algorithm(All Pair Sortest Path)
      • 7. Topological Sort
      • 8. Find if the given edge is a bridge in graph.
  • Disjoint Sets(Union-Find)
    • 1.Implementation of union find
    • 2.Social Network Community
    • 3. Graph Connectivity With Threshold
    • 4. Redundant Connection
    • 5. Smallest String With Swaps
    • 6. Accounts Merge
  • Heap and Priority Queue
    • Concepts of Heap
      • Building Max Heap
    • 1.Kth Largest Element in an Array
    • 2.Kth Largest Element in a Stream
    • 3.Top K Frequent Elements
    • 4.Kth Smallest Element in a Sorted Matrix
    • 5. Find Kth Largest XOR Coordinate Value
    • 6. Top K Frequent Words
    • 7. Find Median from Data Stream
    • 8. Maximum Average Pass Ratio
    • 9. Longest Happy String
    • 10. K Closest Points to Origin
    • 11. Reorganize String
    • 12. Find the Kth Largest Integer in the Array
    • 13. Smallest range in K lists
  • Trie
    • 1. Implement Trie (Prefix Tree)
    • 2. Replace Words
    • 3.Design Add and Search Words Data Structure
    • 4. Search Suggestions System
  • Dynamic Programming
    • 1.House Robber
    • 2.Climbing Stairs
    • 3.Longest Palindromic Substring
    • 4.Longest Palindromic Subsequence
    • 5.Best Time to Buy and Sell Stock
    • 6.Best Time to Buy and Sell Stock with Cooldown
    • 7.Unique Paths
    • 8.Minimum Path Sum
    • 9.Longest Increasing Subsequence
    • 10.Longest Common Subsequence
    • 11.Longest Consecutive Sequence
    • 12.Coin Change
    • 13.Coin Change 2
    • 14.Target Sum
    • 15.Partition Equal Subset Sum
    • 16. Last Stone Weight II
    • 17.Word Break
    • 18. Word Break II
    • 19.Burst Balloons
    • 20. Uncrossed Lines
    • 21. Wildcard Matching
    • 22. Maximal Square
    • 23. Perfect Squares
    • 24. Decode Ways
    • 25. Minimum Cost For Tickets
    • 26. Number of Dice Rolls With Target Sum
    • 27. Delete Operation for Two Strings
    • 28. Maximum Length of Repeated Subarray
    • 29. Longest String Chain
    • 30. Maximum Length of Pair Chain
    • 31. Minimum Falling Path Sum
    • 32. Predict the Winner
    • 33. Delete and Earn
    • 34. House Robber III
    • 35. Partition to K Equal Sum Subsets
    • 36. Different Ways to Add Parentheses
    • 37. Count Square Submatrices with All Ones
    • 38. 2 Keys Keyboard
    • 39. Palindrome Partitioning II
    • 40. Integer Break
    • 41.Cutting a Rod
    • 42. Number of Longest Increasing Subsequence
    • 43. Russian Doll Envelopes
    • 44. 0-1 Knapsack
    • 45. Interleaving String
    • 46. Edit Distance
    • 47. Minimum Insertion Steps to Make a String Palindrome
    • 48.Jump Game
    • 49. Shortest Common Supersequence
    • 50. Length of Longest Fibonacci Subsequence
    • 51. Maximum Alternating Subsequence Sum
    • 52. Palindromic Substrings
    • 53. Distinct Subsequences
    • 54. Best Team With No Conflicts
    • 55. Partition Array for Maximum Sum
    • 56. Ones and Zeroes
  • Greedy Algorithms
    • 1.Activity Selection
    • 2. N meetings in one room
    • 3.Minimum Platforms
    • 4. Car Pooling
    • 5. Maximum Population Year
    • 6.Meeting Rooms
    • 7. Equal Sum Arrays With Minimum Number of Operations
    • 8. Two City Scheduling
    • 9. Non-overlapping Intervals
    • 10. Minimum Number of Arrows to Burst Balloons
    • 11. Maximum Profit in Job Scheduling{IMP}
    • 12.Huffman Coding
    • 13. Minimum Cost Tree From Leaf Values
    • 14.Maximum Number of Events That Can Be Attended
    • 15. Video Stitching
    • 16. Minimum Number of Taps to Open to Water a Garden
  • Backtracking
    • 1.Subsets and Subset II
    • 2.Combinations
    • 3.Generate Parentheses
    • 4.Letter Combinations of a Phone Number
    • 5.Palindrome Partitioning
    • 6.Combination Sum and Combination Sum II
    • 7.Permutations
    • 8. Permutations II
    • 9. Letter Case Permutation
    • 10. Split a String Into the Max Number of Unique Substrings
    • 11. Path with Maximum Gold
    • 12. N-Queens
    • 13. N-Queens II
    • 14. Sudoku Solver
    • 15. Permutation Sequence
    • 16. Beautiful Arrangement
  • Sub Array and Sliding Window Problems
    • 1.Maximum Subarray Sum
    • 2.Maximum Product Subarray
    • 3.Maximum Sum Circular Subarray
    • 4. Maximum Absolute Sum of Any Subarray
    • 5. K-Concatenation Maximum Sum
    • 6.Subarray Sum Equals K
    • 7. Continuous Subarray Sum
    • 8. Contiguous Array
    • 9.Minimum Size Subarray Sum >=k (positive no)
    • 10. Max Subarray sum of positive no <= k
    • 11. Maximum Number of Non-Overlapping Subarrays With Sum Equals Target
    • 12. Maximum Subarray Sum with One Deletion
    • 13. Shortest Subarray with Sum at Least K (Negative Numbers)
    • 14. Frequency of the Most Frequent Element
    • 15. Count Number of Nice Subarrays
    • 16. Binary Subarrays With Sum
    • 17.Number of Substrings Containing All Three Characters
    • 18. Find Two Non-overlapping Sub-arrays Each With Target Sum
    • 19. Maximum Points You Can Obtain from Cards
    • 20. Longest Repeating Character Replacement
    • 21. Subarrays with K Different Integers
    • 22. Replace the Substring for Balanced String
    • 23. Maximize the Confusion of an Exam / Max Consecutive Ones III
    • 24. Subarray Sums Divisible by K
  • Design
    • 1. Design Twitter
    • 2. Design Browser History
    • 3. Snapshot Array
  • Maths
    • Formula
    • 1.Count Prime
    • 2.Pascal's Triangle
    • 3.Extra Long Factorials
    • 4.Factorial Trailing Zeroes
    • 5.Excel Sheet Column Number
    • 6.HCF and LCM
    • 7. Fizz Buzz
    • 8. Rearrange an array so that arr[i] becomes arr[arr[i]]
    • 9. XOR Queries of a Subarray
    • 10. Find second largest element
  • Sorting-Algorithms
    • Merge Sort
    • Quick Sort
    • Heap Sort
    • Selection Sort
    • Bubble Sort
    • Insertion Sort
  • Expected Interview MCQ and Questions c++
  • Concepts in C++
  • System Design Questions
  • đź’ľDBMS
    • Introduction
    • RBMS
    • JOINS
    • SQL
  • 🖥️OS
    • OS and Its Types
    • Process Concept and Threads
    • Process Synchronization
    • Deadlock in Operating System
    • Memory Management
    • Imp Questions of OS for Interviews
  • đźš™OOPS
    • Introduction and Definitions
  • 📨COMPUTER-NETWORKS
    • OSI | TCP IP Model
    • Topology
    • Network Devices
    • IP Address
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On this page
  • 1. Deadlock
  • 2. Conditions for deadlock
  • 3. Methods for handling deadlock
  • 4. Deadlock Prevention And Avoidance
  • 5. Deadlock Recovery

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  1. OS

Deadlock in Operating System

PreviousProcess SynchronizationNextMemory Management

Last updated 3 years ago

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1. Deadlock

Deadlock is a situation where a set of processes are blocked because each process is holding a resource and waiting for another resource acquired by some other process.

2. Conditions for deadlock

Deadlock can arise if the following four conditions hold simultaneously (Necessary Conditions) Mutual Exclusion: One or more than one resource are non-shareable (Only one process can use at a time) Hold and Wait: A process is holding at least one resource and waiting for resources. No Preemption: A resource cannot be taken from a process unless the process releases the resource. Circular Wait: A set of processes are waiting for each other in circular form.

deadlock

3. Methods for handling deadlock

There are three ways to handle deadlock 1) Deadlock prevention or avoidance: The idea is to not let the system into a deadlock state. One can zoom into each category individually, Prevention is done by negating one of above mentioned necessary conditions for deadlock. Avoidance is kind of futuristic in nature. By using strategy of “Avoidance”, we have to make an assumption. We need to ensure that all information about resources which process will need are known to us prior to execution of the process. We use Banker’s algorithm (Which is in-turn a gift from Dijkstra) in order to avoid deadlock.

2) Deadlock detection and recovery: Let deadlock occur, then do preemption to handle it once occurred.

3) Ignore the problem altogether: If deadlock is very rare, then let it happen and reboot the system. This is the approach that both Windows and UNIX take.

4. Deadlock Prevention And Avoidance

Deadlock Prevention:

Deadlock Characteristics

  1. Mutual Exclusion

  2. Hold and Wait

  3. No preemption

  4. Circular wait

We can prevent Deadlock by eliminating any of the above four conditions.

Eliminate Mutual Exclusion It is not possible to dis-satisfy the mutual exclusion because some resources, such as the tape drive and printer, are inherently non-shareable.

Eliminate Hold and wait

  1. Allocate all required resources to the process before the start of its execution, this way hold and wait condition is eliminated but it will lead to low device utilization. for example, if a process requires printer at a later time and we have allocated printer before the start of its execution printer will remain blocked till it has completed its execution.

  2. The process will make a new request for resources after releasing the current set of resources. This solution may lead to starvation.

Eliminate No Preemption Preempt resources from the process when resources required by other high priority processes.

Eliminate Circular Wait Each resource will be assigned with a numerical number. A process can request the resources increasing/decreasing. order of numbering. For Example, if P1 process is allocated R5 resources, now next time if P1 ask for R4, R3 lesser than R5 such request will not be granted, only request for resources more than R5 will be granted.

Deadlock Avoidance:

Deadlock avoidance can be done with Banker’s Algorithm and Resource allocation graph

Banker’s Algorithm Bankers’s Algorithm is resource allocation and deadlock avoidance algorithm which test all the request made by processes for resources, it checks for the safe state, if after granting request system remains in the safe state it allows the request and if there is no safe state it doesn’t allow the request made by the process.

Inputs to Banker’s Algorithm:

  1. Max need of resources by each process.

  2. Currently, allocated resources by each process.

  3. Max free available resources in the system.

The request will only be granted under the below condition:

  1. If the request made by the process is less than equal to max need to that process.

  2. If the request made by the process is less than equal to the freely available resource in the system.

Example:

Total resources in system:
A B C D
6 5 7 6
Available system resources are:
A B C D
3 1 1 2
Processes (currently allocated resources):
    A B C D
P1  1 2 2 1
P2  1 0 3 3
P3  1 2 1 0
Processes (maximum resources):
    A B C D
P1  3 3 2 2
P2  1 2 3 4
P3  1 3 5 0
Need = maximum resources - currently allocated resources.
Processes (need resources):
    A B C D
P1  2 1 0 1
P2  0 2 0 1
P3  0 1 4 0

Note: Deadlock prevention is more strict than Deadlock Avoidance.

5. Deadlock Recovery

There are two approaches of breaking a Deadlock:

1. Process Termination: To eliminate the deadlock, we can simply kill one or more processes. For this, we use two methods:

  • (a) Abort all the Deadlocked Processes: Aborting all the processes will certainly break the deadlock, but with a great expense. The deadlocked processes may have computed for a long time and the result of those partial computations must be discarded and there is a probability to recalculate them later.

  • (b) Abort one process at a time until deadlock is eliminated: Abort one deadlocked process at a time, until deadlock cycle is eliminated from the system. Due to this method, there may be considerable overhead, because after aborting each process, we have to run deadlock detection algorithm to check whether any processes are still deadlocked.

2. Resource Preemption: To eliminate deadlocks using resource preemption, we preempt some resources from processes and give those resources to other processes. This method will raise three issues –

  • (a) Selecting a victim: We must determine which resources and which processes are to be preempted and also the order to minimize the cost.

  • (b) Rollback: We must determine what should be done with the process from which resources are preempted. One simple idea is total rollback. That means abort the process and restart it.

  • (c) Starvation: In a system, it may happen that same process is always picked as a victim. As a result, that process will never complete its designated task. This situation is called Starvation and must be avoided. One solution is that a process must be picked as a victim only a finite number of times.

holdnwait
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