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| Section | Weight | Objectives |
|---|---|---|
| Computer Architecture & Organization | 15% | - Memory hierarchy and performance - Instruction sets and execution cycles - CPU, memory, I/O systems - Von Neumann architecture |
| Software Engineering & Programming Basics | 15% | - Programming paradigms - Basic syntax and control structures - Testing and debugging fundamentals - Software development lifecycle |
| Data Structures | 20% | - Trees, graphs, hash tables - Data storage and retrieval principles - Arrays, linked lists, stacks, queues - Primitive and composite data types |
| Discrete Mathematics & Logic | 25% | - Propositional and predicate logic - Proof techniques and mathematical induction - Boolean algebra and digital logic - Set theory, relations, functions |
| Algorithms & Complexity | 25% | - Big O notation, time and space complexity - Sorting and searching algorithms - Recursion and iterative structures - Algorithm design and analysis |
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NEW QUESTION # 46
Which method converts the default smallest-to-largest index order of a list to instead be the opposite?
Answer: B
Explanation:
Python lists maintain an order, and sometimes you need to reverse that order so the last element becomes first and the first becomes last. The standard list method for reversing the elementsin placeis reverse(). For example, if nums = [1, 2, 3, 4], then nums.reverse() mutates the list so it becomes [4, 3, 2, 1]. This is a built-in operation taught in introductory programming texts because it is efficient and conceptually simple: it does not create a new list unless you explicitly copy the data.
It is important to distinguish reversing from sorting. Reversing changes the sequence order as-is, while sorting rearranges elements according to comparisons. The question refers to converting the index order to the opposite, which is reversing. If you wanted descendingsortedorder, you would typically use sort (reverse=True) or sorted(nums, reverse=True). But the direct method that reverses the list's order is reverse().
The other options are not standard Python list methods. sortDescending(), flip(), and invert() are not part of Python's built-in list API. Textbooks emphasize learning the correct method names because Python's standard library provides a consistent, widely used interface across programs. Thus, reverse() is the correct answer for reversing the index order of a list.
NEW QUESTION # 47
What is a key advantage of using NumPy when handling large datasets?
Answer: C
Explanation:
NumPy's key advantage for large datasets isefficient storage and fast computation. Unlike Python lists, which store references to objects and can have per-element overhead, NumPy arrays store data in a compact, homogeneous format (single dtype) in contiguous or strided memory. This reduces memory usage and improves cache locality, which is crucial for performance on large arrays. Additionally, NumPy operations are vectorized: many computations run in optimized compiled code rather than interpreted Python loops. This enables large speedups for arithmetic, linear algebra, statistics, and transformations over entire arrays.
Option A is incorrect because NumPy itself does not provide full machine learning algorithms; those are typically found in libraries like scikit-learn, though they build on NumPy. Option B is incorrect because NumPy does not automatically clean data; data cleaning is usually done with pandas or custom logic. Option D is incorrect because interactive visualizations are typically handled by libraries like matplotlib, seaborn, or plotly, not by NumPy.
Textbooks in scientific computing highlight that NumPy forms the computational foundation of the Python data ecosystem. Its array model supports broadcasting, slicing, and efficient aggregations, all of which are essential when working with millions of numeric values. By combining compact memory layout with compiled numerical kernels, NumPy enables scalable analysis and simulation workloads that would be slow or memory-heavy using pure Python lists.
NEW QUESTION # 48
What is another term for the inputs into a function?
Answer: B
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 # 49
Which type of data structure is the only focus of a binary search?
Answer: B
Explanation:
Binary search is designed for searching in asorted (ordered) sequence. Its efficiency comes from repeatedly comparing the target to the middle element and discarding half of the remaining search space. This halving logic only works when the data is ordered, because the algorithm relies on the guarantee that all elements on one side of the midpoint are smaller (or larger) than the midpoint. In textbooks, this requirement is stated explicitly: binary search assumes the collection is sorted according to the same ordering used for comparisons.
An "ordered list" is therefore the correct focus among the options. Binary search can be implemented on arrays or other random-access structures where you can quickly access the middle element by index. While you can conceptually perform binary search on a linked list, it becomes inefficient because finding the middle requires linear traversal, losing the O(log n) advantage. Stacks and queues are not appropriate because they restrict access to ends only (LIFO for stacks, FIFO for queues), preventing direct access to the midpoint and making the binary search strategy infeasible.
Thus, the central requirement for binary search is a sorted/ordered sequence, typically supporting efficient indexing, which is why the correct choice is an ordered list.
NEW QUESTION # 50
What stores the location of the next node in a linked list?
Answer: A
Explanation:
A linked list is a dynamic data structure made up of nodes, where each node typically contains two components: a data field (the value being stored) and a link field (commonly called a pointer or reference).
The pointer's role is to store the memory address (or reference) of the next node in the sequence, thereby maintaining the logical order of the list even though nodes may be scattered throughout memory. This is a key contrast with arrays, which store elements contiguously and rely on index arithmetic to locate the next element.
Because each node explicitly points to the next node, linked lists support efficient insertion and deletion operations compared with arrays. To insert a node, you allocate it and then adjust pointers so it fits into the chain. To delete a node, you redirect the pointer of the previous node to skip over the removed node.
Traversal is performed by starting at the head node and repeatedly following the pointer until a null reference indicates the end of the list.
The other options do not correctly describe what stores the location of the next node. An index is used in array-like structures, not in a standard linked list node. The value is the payload data, not the link.
The "header" (often called the head pointer) is an external reference to the first node, not the field inside each node that links to the next. Therefore, the correct answer is the pointer.
NEW QUESTION # 51
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