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| Section | Objectives |
|---|---|
| Topic 1: Algorithm Efficiency | - Choose an appropriate algorithm searching method based on a given scenario - Choose an appropriate sorting algorithm method based on a given scenario - Describe the relationships between algorithm complexity and data structures |
| Topic 2: Basic Program Design | - Identify variables and data types within a programming language - Use functions, methods, and packages to leverage programming language - Explain how to store, access, and manipulate data in lists |
| Topic 3: OS Fundamentals | - Demonstrate various techniques and tools to manage operating systems - Identify common privacy and security concepts that could be implemented in operating systems - Describe fundamental principles and core concepts of operating systems |
| Topic 4: Data Profiling | - Utilize a programming language to manipulate arrays and discover insights - Apply fundamental concepts and subsetting techniques to a dataset |
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NEW QUESTION # 68
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 # 69
What will the expression fam[3:6] return?
Answer: B
Explanation:
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]`.
NEW QUESTION # 70
What is a correct call to the linear search defined as def linear_search(customersList, search_value): ?
Answer: D
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 # 71
What is the time complexity of a binary search algorithm?