Foundations-of-Computer-Science Latest Questions & Foundations-of-Computer-Science Latest Test Questions

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WGU Foundations-of-Computer-Science Exam Syllabus Topics:

SectionObjectives
Basic Program Design- Use functions, methods, and packages to leverage programming language
- Explain how to store, access, and manipulate data in lists
- Identify variables and data types within a programming language
OS Fundamentals- Describe fundamental principles and core concepts of operating systems
- Identify common privacy and security concepts that could be implemented in operating systems
- Demonstrate various techniques and tools to manage operating systems
Algorithm Efficiency- Describe the relationships between algorithm complexity and data structures
- Choose an appropriate sorting algorithm method based on a given scenario
- Choose an appropriate algorithm searching method based on a given scenario
Data Profiling- Apply fundamental concepts and subsetting techniques to a dataset
- Utilize a programming language to manipulate arrays and discover insights

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WGU Foundations of Computer Science Sample Questions (Q12-Q17):

NEW QUESTION # 12
What is the expected result of running the following code: list1[0] = "California"?

Answer: D

Explanation:
Python lists are mutable sequences, which means elements can be changed in place after the list has been created. The expression list1[0] = "California" uses indexing to target the element at position 0 (the first element, because Python uses zero-based indexing) and assignment (=) to replace that element with a new value. As a result, the list keeps the same length, but its first entry becomes "California".
This operation does not create a new list (so option A is incorrect); it modifies the existing list object referenced by list1. It also does not append to the end of the list (so option C is incorrect). Appending would use methods like list1.append("California"). Option D is not meaningful in Python list semantics; assignment to a single index replaces exactly one element rather than "adding a second element to the line." Textbooks highlight this difference between mutable and immutable sequence types. For example, strings are immutable, so you cannot assign to some_string[0]. Lists, however, are designed for collections that change over time, supporting updates, insertions, deletions, and reordering. Index assignment is fundamental for many algorithms: updating an array-like buffer, modifying a dataset row, replacing incorrect values, or implementing in-place transformations efficiently.


NEW QUESTION # 13
What is a correct call to the linear search defined as def linear_search(customersList, search_value): ?

Answer: C

Explanation:
A function definition in Python specifies a function name and a list of parameters. Here, def linear_search (customersList, search_value): defines a function named linear_search that requirestwo argumentswhen called: a list (or sequence) of customer items and the value being searched for. A correct call must therefore supply both arguments in the same order: linear_search(customersList, search_value). Option B is correct because it calls the function properly and then prints the returned result.
Textbooks describe linear search as scanning the list from the beginning to the end, comparing each element to search_value until a match is found or the list ends. The function typically returns an index (e.g., position of the match) or a Boolean, or possibly -1/None if not found. Wrapping the call in print(...) is a standard way to display the returned value for testing or demonstration.
Option A is incorrect because it calls a different function name, not linear_search. Option C is incorrect because linear_search() would attempt to call the function with zero arguments, which would raise a TypeError, and then it tries to call the result as if it were another function. Option D uses a different function name (search_linear) and also contains a spelling mismatch compared to the given definition.


NEW QUESTION # 14
The np_2d array stores information about multiple family members. Each row represents a different person, and the columns store family member attributes in the following order:
Age (years)
Weight (pounds)
Height (inches)
How is the weight of all family members selected from the np_2d array?

Answer: A

Explanation:
In a 2D NumPy array, rows and columns represent different dimensions of the data. The indexing form array
[row_selection, column_selection] allows you to select entire rows, entire columns, or submatrices. The slice :
means "all indices along this dimension." Since each row corresponds to a family member (a person), selecting weights forallfamily members means selectingall rowsfor the weight column.
The problem states the columns are ordered as: Age (column 0), Weight (column 1), Height (column 2).
Therefore, the weight column has index 1. The expression np_2d[:, 1] uses : to take every row and 1 to take the second column, producing a 1D array (or a column view) containing the weight values for all people.
Option A, np_2d[:, 2], would select the height column, not weight. Option C, np_2d[2, :], selects the third row (the third person) and all columns-age, weight, and height for just that one person. Option D, np_2d[1, :], selects the second person's entire row.
This column selection technique is fundamental in data analysis because datasets are often stored as
"rows = observations, columns = features," and extracting a feature vector is a frequent operation before computing statistics or building models.


NEW QUESTION # 15
What is the layer of programming between the operating system and the hardware that allows the operating system to interact with it in a more independent and generalized manner?

Answer: A

Explanation:
TheHardware Abstraction Layer (HAL)is a software layer that sits between the operating system kernel and the physical hardware. Its purpose is to hide hardware-specific details behind a consistent interface, allowing the OS to be more portable and easier to maintain across different hardware platforms. Textbooks explain that without abstraction, the OS would need extensive device- and architecture-specific code scattered throughout the kernel, making updates and cross-platform support far more difficult.
The HAL typically provides standardized functions for interacting with low-level components such as interrupts, timers, memory mapping, and device I/O. With a HAL, the OS can call general routines (for example, to configure an interrupt controller) while the HAL handles the platform-specific implementation.
This supports a key systems principle: separate policy (what the OS wants to do) from mechanism (how hardware accomplishes it).
The other options are not correct. A boot loader runs at startup to load the operating system into memory; it is not the general interface layer during normal operation. The task scheduler is a kernel subsystem that manages CPU time among processes, not a hardware-independence layer. The file system layer manages storage organization and access semantics; it is not the general abstraction for all hardware interactions.
Therefore, the programming layer that enables generalized OS interaction with hardware is the hardware abstraction layer.


NEW QUESTION # 16
What is the name of the tool that can allow a device to run more than one operating system at a time as virtual machines?

Answer: A


NEW QUESTION # 17
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