CS502

Fundamentals of Algorithms

GDB Details & Solutions

GDB Information

Total Marks:

5

Start Date:

January 2, 2025 333 Days Passed

End Date:

January 3, 2025 Expired

Status:

Closed

GDB Question

A bank processes a list of customer transactions at the end of each day. The transactions need to be sorted based on the following criteria:



  1. Transaction Amounts: For reporting, transactions are sorted in ascending order by amount.

  2. Transaction Timestamps: For audit purposes, transactions are sorted chronologically.

  3. Account IDs: For batching transactions by accounts, they are sorted by account numbers.


The transaction dataset has the following characteristics:



  • The list is large (e.g., millions of transactions daily).

  • The data is mostly unsorted but contains some pre-ordered segments (e.g., transactions for certain accounts).

  • The transaction amounts are bounded (e.g., between US dollar 1 and 1,000,000).

  • Each transaction record includes multiple attributes, making sorting based on keys complex.


Based on the analysis of the given scenario, you need to choose the most suitable sorting algorithm from the following options: Selection Sort, Merge Sort, Quick Sort, Heap Sort, Radix Sort, and Bucket Sort. Identify which algorithm performs best overall and provide reasons to justify your choice.


 


NOTE:  Your answer should be in the following format:


Your choice: ________.


Reason 1:
         write explanation/detail of this reason in 2-3 lines.
   Reason 2:
         write explanation/detail of this reason in 2-3 lines.

GDB Solutions

Approved: 4 Pending: 0
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Solution 1
Type: Inline Solution Uploaded: January 3, 2025 User Approved
GDB Answer:

Choice: Merge Sort.

Reason 1:
Merge Sort efficiently handles large datasets with its O(nlog⁡n)O(n \log n)O(nlogn) time complexity, making it suitable for processing millions of transactions daily without significant delays.

Reason 2:
Being a stable sorting algorithm, Merge Sort maintains the relative order of transactions with identical keys, which is critical for accurate reporting and audit purposes.

Solution 2
Type: Inline Solution Uploaded: January 3, 2025 User Approved
GDB Answer:

choice: Merge Sort.

Reason 1:
Due to its O(nlog⁡n)O(n \log n)O(nlogn) time complexity, Merge Sort can sort extensive transaction datasets efficiently, making it ideal for large-scale banking operations.

Reason 2:
Its stability ensures that transactions with the same keys, such as timestamps or amounts, retain their sequence, preserving consistency in audits and reports.

Solution 3
Type: Inline Solution Uploaded: January 3, 2025 User Approved
GDB Answer:

choice: Merge Sort.

Reason 1:
Merge Sort is a highly efficient algorithm for sorting massive datasets, as its O(nlog⁡n)O(n \log n)O(nlogn) complexity allows quick processing of millions of records daily.

Reason 2:
The stability of Merge Sort is crucial for maintaining the original order of transactions with identical keys, ensuring the accuracy of financial reports and audit trails.

Solution 4
Type: Inline Solution Uploaded: January 3, 2025 User Approved
GDB Answer:

choice: Merge Sort.

Reason 1:
Merge Sort’s O(nlog⁡n)O(n \log n)O(nlogn) performance makes it well-suited for handling the scale of millions of transactions efficiently, ensuring smooth bank operations.

Reason 2:
As a stable sorting algorithm, it preserves the relative order of records with matching keys, which is vital for reliable audits and compliance requirements.