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| Section | Weight | Objectives |
|---|---|---|
| Discrete Mathematics & Logic | 25% | - Boolean algebra and digital logic - Propositional and predicate logic - Proof techniques and mathematical induction - Set theory, relations, functions |
| Software Engineering & Programming Basics | 15% | - Programming paradigms - Software development lifecycle - Testing and debugging fundamentals - Basic syntax and control structures |
| Algorithms & Complexity | 25% | - Recursion and iterative structures - Big O notation, time and space complexity - Sorting and searching algorithms - Algorithm design and analysis |
| Computer Architecture & Organization | 15% | - Von Neumann architecture - CPU, memory, I/O systems - Instruction sets and execution cycles - Memory hierarchy and performance |
| Data Structures | 20% | - Primitive and composite data types - Arrays, linked lists, stacks, queues - Trees, graphs, hash tables - Data storage and retrieval principles |
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23. Frage
What Python code would return the value 40 from np_2d, where np_2d = np.array([[1, 2, 3, 4], [10, 20, 30,
40]])?
Antwort: B
Begründung:
In a 2D NumPy array, indexing is written as array[row_index, column_index] using zero-based indices. The array np_2d = np.array([[1, 2, 3, 4], [10, 20, 30, 40]]) has two rows (indices 0 and 1) and four columns (indices 0, 1, 2, 3). The value 40 is located in the second row and the fourth column. Using zero-based indexing, that corresponds to row index 1 and column index 3. Therefore, np_2d[1, 3] returns 40.
Option A attempts to access row 3, which does not exist and would raise an IndexError. Option C attempts to access column 4 in row 0, but valid column indices are only 0 through 3, so it would also error. Option D likewise refers to a non-existent row 4. Only option B uses valid indices and points to the correct location.
Textbooks emphasize multi-dimensional indexing because it underlies matrix operations, dataset manipulation, and feature extraction in data science. Correctly interpreting rows and columns is essential when rows represent observations (like people) and columns represent attributes (like age, weight, height). This question tests precise control over row/column addressing, which prevents subtle bugs in numerical analysis.
24. Frage
What is the method for changing an element in a Python list?
Antwort: D
Begründung:
In Python, a list is a mutable sequence, meaning its elements can be changed after the list is created. The standard textbook method for updating a specific element isindex assignment, which uses square brackets to select the position and the equals sign to assign a new value. For example, if nums = [10, 20, 30], then nums
[1] = 99 changes the element at index 1 from 20 to 99, producing [10, 99, 30]. This works because lists store references to objects and allow those references to be updated in-place.
Option B is incorrect because parentheses are used for function calls and tuples, and the plus sign typically performs concatenation (creating a new list) rather than modifying an existing element by position. Option C is incorrect because curly brackets denote dictionaries or sets, not lists. Option D is incorrect because del removes elements by index or slice (for example, del nums[1]), and it does not delete by "the element's value" unless you first find the index. Deleting is not the same as changing; deletion reduces the list's length and shifts later indices.
Index assignment is fundamental in list manipulation and appears in standard algorithms: updating counters, replacing sentinel values, editing collections, and implementing in-place transformations efficiently without allocating a new list.
25. Frage
What will the expression fam[3:6] return?
Antwort: B
Begründung:
Python slicing follows the rule `sequence[start:stop]`, where the `start` index is **inclusive** and the `stop` index is **exclusive**. This convention is taught widely because it makes many algorithms and boundary cases simpler: the length of the slice is `stop - start` (when step is 1), and adjacent slices can partition a sequence without overlap. For a list named `fam`, the slice `fam[3:6]` starts at index 3 and includes the elements at indices 3, 4, and 5, but it stops before index 6.
This is a frequent source of off-by-one errors for beginners, so textbooks emphasize remembering: "start is included, stop is not." If `fam` had at least 6 elements, then `fam[3:6]` would produce a new list of exactly three elements (positions 3, 4, 5). If `fam` had fewer than 6 elements, Python would still return a valid slice up to the end without raising an error, because slicing is designed to be safe within bounds.
# Option A is incorrect because it skips index 3 and incorrectly includes index 6. Option B is incorrect because it includes index 6, which the stop boundary excludes. Option D is incorrect because slicing returns a sublist, not a single element; a single element would require indexing like `fam[6]`.
26. Frage
What is the purpose of user management and access control in a networked environment?
Antwort: D
Begründung:
In a networked environment, user management and access control exist to ensure that resources are used securely, appropriately, and accountably. The core idea isauthorization: defining what each user (or group of users) is allowed to do-read files, modify data, access applications, administer systems, and so on. This is commonly guided by the principle ofleast privilege, which states that users should receive only the permissions necessary to perform their tasks. Proper access control reduces the damage from mistakes and limits the impact of compromised accounts.
User management also includesauthenticationsupport (ensuring a user is who they claim to be) and administrative functions such as creating accounts, assigning roles, revoking access, and enforcing policies (password rules, multi-factor authentication requirements, session timeouts). In many systems, access control is implemented through models like discretionary access control (DAC), role-based access control (RBAC), or mandatory access control (MAC), each with different security properties.
Option B correctly reflects this: the goal is to establish permissions and to monitor or audit usage (logging access, tracking changes, detecting suspicious behavior). Option A is wrong because equal access is rarely secure or practical. Option C is the opposite of secure practice. Option D is too absolute:
systems typically restrict some users from some confidential resources, not all users from all confidential documents.
27. Frage
How does the data type of a variable get set in Python?
Antwort: D
Begründung:
Python usesdynamic typing, a core concept emphasized in programming language textbooks. In dynamically typed languages, a variable name does not permanently "own" a type. Instead, theobjectcreated by an expression has a type, and the variable becomes a reference to that object. Therefore, the type associated with a variable at any moment is determined by the value assigned to it. For example, after x = 7, x refers to an integer object. After x = "seven", the same name now refers to a string object. The type changes because the binding changes, not because the variable's type declaration was edited.
Option A describesstatic typingsystems (common in languages like Java, C, or C++), where programmers declare types and compilers enforce them. Python does not require such declarations for ordinary variables.
Option B is incorrect because type assignment is deterministic, not random. Option C is incorrect because Python does not default variables to strings; it assigns whatever type results from the right-hand-side expression.
This model is closely tied to Python's runtime behavior: type checks occur during execution, and functions can accept values of different types as long as the operations used are valid (often discussed as
"duck typing"). This flexibility supports rapid development, but also motivates careful testing and, in larger systems, optional type hints for documentation and tool support.
28. Frage
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