Category: programming

Leetcode 1052.Grumpy bookstore owner

Posted on by lechuck park

From Claude with some prompting
This image describes a programming problem titled “Grumpy bookstore owner”. Here’s a summary of the key points:

  1. Problem description:
    • A bookstore is open for n minutes.
    • Each minute, a certain number of customers enter the store.
    • The ‘customers’ array represents the number of customers entering each minute.
    • The ‘grumpy’ array indicates the bookstore owner’s mood each minute (1: grumpy, 0: not grumpy).
    • When the owner is grumpy, customers are not satisfied.
    • The owner can use a secret technique once to not be grumpy for m consecutive minutes.
  2. Objective:
    • Calculate the maximum number of customers that can be satisfied throughout the day.
  3. Solution approach:
    • Step 1: Calculate the base sum of satisfied customers (when the owner is not grumpy).
    • Step 2: Use a sliding window of size m to find the maximum additional customers that can be satisfied.
  4. Example:
    • In Example 1, with customers = [1,0,1,2,1,1,7,5], grumpy = [0,1,0,1,0,1,0,1], minutes = 3, the maximum number of satisfied customers is 16.
  5. Constraints:
    • Constraints on array length, time, and number of customers are provided.

This problem appears to be solvable using a sliding window technique for an efficient algorithmic solution.

Leetcode 974.Subarray Sums Divisible by K

Posted on by lechuck park

From Claude with some prompting
Find Subarrays with Same Remainder First, we calculate the prefix sum, which is the cumulative sum up to each element in the array. For example, the prefix sum for [4, 5, 0, -2, -3, 1] is [4, 9, 9, 7, 4, 5]. Then, we find the remainder when each prefix sum is divided by k. In this case, with k=5, the remainders are [4, 4, 4, 2, 4, 0].

Count Subarrays with Same Remainder We count the number of subarrays that have the same remainder. For instance, if the remainder 4 appears 3 times, it means there are 3 subarrays ending with a sum divisible by 5 and leaving a remainder of 4. We store these counts in a remainder_count array.

Calculate Answer For the remainder 0, we assume there is always at least one subarray (the empty subarray), so we initialize remainder_count[0] = 1. Then, we calculate the combinations of subarrays with the same remainder. If there are remainder_count[r] subarrays with the same remainder r, the number of combinations is (remainder_count[r] * (remainder_count[r] – 1)) / 2. We sum up these values for all remainders to get the final answer.

In summary, this algorithm utilizes the remainders of prefix sums to count the number of subarrays with the same remainder, and then combines these counts to find the total number of subarrays whose sum is divisible by k.

Leetcode 234.Palindrome Linked List

Posted on by lechuck park

From DALL-E with some prompting
Scenario:

  • Linked-List: You can only read one element at the same time.
  • Memory Map: Allows direct access to all data.
  • Optimization: There are 2 key points to optimize:
    • Point 1: Find out the center of the list.
    • Point 2: Reverse the ordering of the second half of the list and compare it with the first half.
    The diagram illustrates two examples with nodes that show how you would first read all data (in the Linked-List), then direct access allows you to compare elements starting from the ends towards the center (in the Memory Map). For optimization, the steps include finding the center of the list, reversing the order of the second half of the list, and then comparing the two halves to determine if the list is a palindrome.

Mutual exclusion

Posted on by lechuck park

From DALL-E with some prompting
this image illustrates the concept of ‘Mutex (Mutual exclusion)’ and ‘Critical Section’ which are pivotal in multi-threaded programming. Mutexes are used to control simultaneous data access by multiple threads, maintaining data consistency. A critical section is a part of the code that only one thread can access at a time, and it’s where sensitive data is processed. Threads gain access to this section by acquiring a mutex lock (pthread_mutex_lock), and after completing their work, they release the lock (pthread_mutex_unlock) to allow other threads to enter. This mechanism ensures that all threads view and maintain a consistent state of the data, allowing safe modifications and sustained data integrity.

From the coding

Posted on by lechuck park

From DALL-E with some prompting
This diagram illustrates the journey from the basics of coding to the creation of digital solutions that meet the requirements of the real world. It begins with an understanding of the fundamental syntax of programming, progressing to knowledge of system calls, operating systems and kernels, computer architecture, and the workings of hardware. This technical acumen is combined with the roles of digital experts, programming experts, and system experts who transform client and business requirements into digital solutions. This process involves specific data models, system architecture and design, framework APIs, and database management. Overall, the diagram describes the comprehensive process of developing digital services, starting from coding and extending to advanced technical understanding in network architecture, engineering, and packet management.

Leetcode 1582. Special Positions in a Binary Matrix

Posted on by lechuck park

From ChatGPT4 < image interpretation>
The image presents a problem statement and a solution approach for identifying special positions in a binary matrix from a programming challenge. The task is to find positions in the matrix where the value is ‘1’, and all other values in the same row and column are ‘0’. The solution involves three steps:

  1. Interpretation: It involves identifying the type of ‘1’ cells that are unique in their row and column with no other ‘1’s in any of the four quadrant directions.
  2. Creating ‘1’ count maps: This step counts the number of ‘1’s in each row and column to create horizontal and vertical direction maps.
  3. Final count: It counts the cells that contain a ‘1’ and checks if there are no other ‘1’s in the corresponding horizontal and vertical directions.

The code snippets provided outline the loops and conditions used to implement this logic in a programming language.

leetcode 1464. Maximum Product of Two Elements in an Array

Posted on by lechuck park

From DALL-E with some prompting

The image displays a programming challenge titled “1464. Maximum Product of Two Elements in an Array”. The task is to choose two different indices i and j from an array of integers to maximize the value of (nums[i]-1)*(nums[j]-1).

Example 1 gives the array [3,4,5,2], selecting indices i=1 and j=2 yields the maximum value (4-1)(5-1) = 12. In Example 2, the array [1,5,4,5] yields a maximum value of (5-1)(5-1) = 16 when indices i=1 and j=3 are chosen. For Example 3, with the array [3,7], any selection of indices results in (3-1)*(7-1) = 12.

The suggested solution involves sorting the array in descending order and then selecting the first two numbers. Alternatively, while quicksort could be used, it is noted that a more efficient O(1) method exists for directly finding the first and second largest numbers. Code snippets are provided, demonstrating the iteration over the array to find the largest and second-largest numbers.

The constraints specify that the length of the nums array is between 2 and 500 and each element in the array is less than or equal to 10^3.