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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Structures | 20% | - Arrays, linked lists, stacks, queues - Primitive and composite data types - Data storage and retrieval principles - Trees, graphs, hash tables |
| Topic 2: Algorithms & Complexity | 25% | - Big O notation, time and space complexity - Algorithm design and analysis - Recursion and iterative structures - Sorting and searching algorithms |
| Topic 3: Computer Architecture & Organization | 15% | - CPU, memory, I/O systems - Von Neumann architecture - Memory hierarchy and performance - Instruction sets and execution cycles |
| Topic 4: Software Engineering & Programming Basics | 15% | - Basic syntax and control structures - Software development lifecycle - Testing and debugging fundamentals - Programming paradigms |
| Topic 5: Discrete Mathematics & Logic | 25% | - Set theory, relations, functions - Boolean algebra and digital logic - Propositional and predicate logic - Proof techniques and mathematical induction |
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NEW QUESTION # 67
What is the only content that will display if the List folder contents permission is not enabled for a particular folder in Windows 11?
Answer: A
Explanation:
In Windows file security (NTFS permissions), "List folder contents" controls whether a user cansee the names of files and subfoldersinside a folder. If a user does not have permission to list a folder, Windows prevents directory enumeration: the user cannot browse the folder and view what is inside. (2BrightSparks) This is a key concept in access control: it separates "being able to traverse to a location" from "being able to see what is stored there." When "List folder contents" is not enabled, the user typically cannot view the list of files regardless of whether individual files might have separate permissions. In standard user-facing behavior, what remains visible in the folder's properties and metadata is limited; among the choices given, the only item that is reliably a folder-level metadata attribute (and not a listing of contents) is the folder'screation date. The
"author" is not a universal, reliably displayed NTFS folder property, and options C and D talk about files (contents), which cannot be listed without the list permission. (2BrightSparks) This reflects a broader textbook principle: operating systems enforce access control both on objects (files/folders) and on operations (read data, write data, list directory). Removing the list operation blocks visibility of contents, even if other permissions exist elsewhere.
NEW QUESTION # 68
How can someone subset the last two rows and columns of a 2D NumPy array?
Answer: B
Explanation:
NumPy slicing uses the same start/stop rules as Python sequences, and it also supports negative indices to count from the end. In a 2D array, slicing is written as array[rows, columns]. To get thelast two rows, you use
-2: in the row position, meaning "start two rows from the end and go to the end." Similarly, to get thelast two columns, you use -2: in the column position. Combining these gives array[-2:, -2:], which selects the bottom- right 2×2 subarray.
Option A, array[-2:, :], selects the last two rows butall columns, so it is not restricted to the last two columns.
Option D, array[:, -2:], selects all rows but only the last two columns. Option B, array[-1:, -1:], selects only the last row and the last column, producing a 1×1 (or 1×1 view) subarray, not a 2×2.
This kind of slicing is widely taught because it is essential for matrix operations, extracting submatrices, working with sliding windows, and manipulating image or time-series data where "take the last k observations/features" is common. Negative indexing reduces errors and makes code clearer, especially compared with computing explicit indices like array[rows-2:rows, cols-2:cols].
NEW QUESTION # 69
What is another term for the inputs into a function?
Answer: A
Explanation:
In programming, a function takes inputs, performs computation, and may return an output. The standard term for a function's inputs isarguments(also commonly discussed alongside the closely related termparameters).
Textbooks typically distinguish the two:parametersare the names listed in the function definition, while argumentsare the actual values supplied when the function is called. For example, in def f(x, y):, x and y are parameters. In the call f(3, 5), 3 and 5 are arguments. Many introductory materials use "arguments" informally to refer to the inputs overall, which matches the wording of this question.
Options A, B, and C do not fit the textbook definition. "Variables" is too broad; inputs can be literals, expressions, or variables, but the conceptual role is "arguments." "Procedures" are callable units of code (often used in some languages to mean functions without return values), not the inputs. "Outputs" refers to returned results, not what you pass in.
Understanding arguments is important because it connects to call semantics, scope, and correctness.
Different languages support positional arguments, keyword arguments, default values, and variadic arguments (e.g., *args, **kwargs in Python). This flexibility shapes API design and influences how programmers structure reusable code.
NEW QUESTION # 70
What statistical measure can be used to detect outliers in a dataset using NumPy?
Answer: C
Explanation:
Outlier detection often relies on measuring how far values deviate from a "typical" center. While variance and standard deviation can be used in simple z-score based methods, they arenot robust: a few extreme outliers can inflate the mean and standard deviation, masking the very outliers you want to find. A widely taught robust alternative is themedian absolute deviation (MAD), which is based on the median rather than the mean and therefore resists distortion by extreme values.
MAD is computed by first taking the median of the data, then computing the absolute deviation of each point from that median, and finally taking the median of those deviations. Because medians are stable under extreme values, MAD provides a strong baseline for identifying unusually distant points. Many textbooks and data analysis references present MAD as a robust scale estimator for outlier detection, often combined with a threshold rule such as flagging points whose deviation exceeds a constant multiple of MAD (with a scaling factor sometimes used to make it comparable to standard deviation under normality assumptions).
In NumPy, you can implement MAD using np.median() and np.abs(). Mode is generally not useful for continuous numeric outlier detection, and variance/standard deviation are more sensitive to outliers than MAD. Thus, among the given options, the best statistical measure for detecting outliers robustly is the median absolute deviation.
NEW QUESTION # 71
What is the correct way to represent a boolean value in Python?
Answer: C
Explanation:
Python has a built-in boolean type named bool, which has exactly two values: True and False. These are language keywords/constants and are case-sensitive. Therefore, the correct representation of a boolean value is True (capital T, lowercase rest) or False (capital F). This is consistently taught in introductory programming textbooks because it affects conditional statements (if, while), logical operations (and, or, not), and comparisons.
Option A, "True", is a string literal, not a boolean. While it visually resembles the boolean constant, it behaves differently: non-empty strings are "truthy" in conditions, but "True" == True is false because they are different types (str vs bool). Option B, "true", is also a string, and it differs in casing as well. Option D, true, is not valid in Python; it will raise a NameError unless a variable named true has been defined.
Textbooks also stress that boolean values often result from comparisons, such as x > 0, and that booleans are a subtype of integers in Python (True behaves like 1 and False like 0 in arithmetic contexts). Still, their primary use is representing logical truth values for control flow and decision- making.
NEW QUESTION # 72
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