Question

Assume an array of structures is in order by the customerID field of the record, where customer IDs go from 101 to 500 . A) Write the most efficient pseudocode algorithm you can to find the record with a specific customerID if every single customer ID from 101 to 500 is used and the array has 400 elements. B) Write the most efficient pseudocode algorithm you can to find a record with a customer ID near the end of the IDs, say \(494,\) if not every single customer ID in the range of 101 to 500 is used and the array size is only 300 .

Short answer

Question: Explain the process for finding a specific customer record in an array of 400 elements containing customer IDs from 101 to 500. Answer: To find a specific customer record in an array of 400 elements containing customer IDs from 101 to 500, we can directly access the record using the customer ID. Calculate the index by subtracting the starting customer ID (101) from the target customer ID, then access the record at that index within the array.

Step-by-step solution

Accessing the record using customerID

Let the array of structures be called 'records'. To access the record with a specific customerID, directly access the index by subtracting the starting customerID (101) from the target customerID. The pseudocode will be as follows: - Determine the target customerID (let's call it 'targetID') - Calculate the index by using the formula index = targetID - 101 - Access the record by using records[index] B) Pseudocode for finding a record with a customerID near the end of the IDs using Binary Search:

Initialize variables

Initialize the variables 'left', 'right', and 'middle' to 0, len(records) - 1, and 0 respectively. Let the target ID be 'targetID'.

Binary Search

While 'left' is less than or equal to 'right': - Calculate the middle by using the formula middle = (left + right) // 2 - If the customerID at the middle index (records[middle].customerID) is equal to targetID, return the record at index middle (records[middle]). - If the customerID at the middle index is less than targetID, update the left boundary by setting left = middle + 1. - Else, update the right boundary by setting right = middle - 1.

Record not found

If the Binary Search completes without finding the target customerID, return that the record was not found.

Key concepts

Array of Structures

Structures in programming are a way of grouping several pieces of related data together. When it comes to storing multiple structures, an array of structures is an excellent tool for organizing such data. In the context of the given exercise, an array of structures is used to keep records of customers, where each structure represents an individual record holding information about a customer.

Each structure in the array might contain a customerID, along with other details such as name, address, or transaction history. The array is indexed in a way that allows for efficient data retrieval, which is particularly useful when the records are sorted by a key field, like the customerID in our example. When the array is sorted, searching operations become faster, and determining the location of a specific piece of data is simplified. As a result, if a student wants to access the record for a customer with a specific ID, it can be done directly using simple arithmetic, avoiding the need for a loop to traverse the entire array.

Pseudocode

Pseudocode is a way to describe algorithms using plain language. It's a critical step for understanding the logic behind a program before coding it in a specific programming language. Pseudocode is not bound by the syntax rules of any one language and it doesn't include details that are unnecessary for understanding the problem.

In our exercise, the pseudocode provides a clear and understandable way to convey the steps needed to find a customer's record based on their customerID. It outlines the logic without getting bogged down by technical details. This helps students to grasp the concept of the algorithm without the additional complexity of syntax, and serves as a blueprint that can be adapted to any programming language. For example, the pseudocode for directly accessing a customer's record based on ID is concise and shows the calculation needed to find the position of that record in the array.

Searching Algorithms

Searching algorithms are designed to retrieve information stored within a data structure. They're fundamental for locating specific elements within a dataset efficiently. There are many types of searching algorithms, and choosing the right one depends on the characteristics of the data and the problem at hand.

In cases where data is sorted and evenly distributed, like a complete range of customer IDs, a simple direct access is possible and efficient. However, when dealing with a more complex dataset, where not all elements are present or the distribution is uneven, more sophisticated methods are necessary. The binary search algorithm, mentioned in the exercise's solution, is a perfect example.

Understanding Binary Search

Binary search is a 'divide and conquer' algorithm that rapidly narrows down the search area by repeatedly dividing the array in half. This is an effective method when the array is sorted but not complete, as in our second example where the customer IDs are not all present. By comparing the middle element to the target element, binary search can discard half of the possible places where the target could be, significantly speeding up the search process. When implemented correctly, binary search greatly reduces the number of comparisons required, resulting in a more efficient search than linearly scanning the entire array.