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30 Terms
1
Asymptotic notation
____ describes the limiting behavior of a function, focusing on its growth rate as the input size approaches infinity
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2
Linear search, O(n)
______ scans each element sequentially to find a target, with a time complexity of ____
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3
Binary search, O(log n)
___ requires a sorted array and divides the search space in half with each iteration, with a time complexity of ____
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4
What is dominant term in running time analysis?
it is the highest order term in the running time expression, which has the most significant impact on scalability.
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5
What are hidden constants and lower-order terms in algorithm analysis?
Hidden constants are factors that can affect performance but are often ignored in Big O notation, while lower-order terms become less significant as input size increases.
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6
sorting, searching, and optimization problems
___ types of problems that are commonly analyzed in algorithm courses.
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7
Algorithm efficiency
____ determines how well an algorithm performs in terms of time and space, impacting overall system performance.
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8
Performance analysis
_____ helps understand how an algorithm scales with larger input sizes, which is crucial for efficiency.
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9
recursive algorithm
____ solves a problem by breaking it down into smaller subproblems of the same type, often using a base case to terminate recursion.
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10
divide and conquer, dynamic programming, and greedy algorithms
_____ are fundamental algorithm design techniques.
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11
dynamic programming
____ is a method for solving complex problems by breaking them down into simpler subproblems and storing the results to avoid redundant calculations.
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12
Greedy algorithm
___ makes the locally optimal choice at each stage with the hope of finding a global optimum.
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13
arrays, linked lists, stacks, queues, trees, and graphs
_____ are common data structures used in algorithms
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14
impacts the efficiency of an algorithm and time complexity for operations like insertion, deletion, and searching.
How does the choice of data structure affect algorithm performance?
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15
helps identify the most efficient solution for a given problem, considering factors like time complexity, space complexity, and ease of implementation.
What is the purpose of analyzing different algorithms for standard problems?
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16
Asymptotic notation
____ describes the limiting behavior of a function, focusing on its growth rate as the input size approaches infinity
New cards
17
Linear search, O(n)
______ scans each element sequentially to find a target, with a time complexity of ____
New cards
18
Binary search, O(log n)
___ requires a sorted array and divides the search space in half with each iteration, with a time complexity of ____
New cards
19
What is dominant term in running time analysis?
it is the highest order term in the running time expression, which has the most significant impact on scalability.
New cards
20
What are hidden constants and lower-order terms in algorithm analysis?
Hidden constants are factors that can affect performance but are often ignored in Big O notation, while lower-order terms become less significant as input size increases.
New cards
21
sorting, searching, and optimization problems
___ types of problems that are commonly analyzed in algorithm courses.
New cards
22
Algorithm efficiency
____ determines how well an algorithm performs in terms of time and space, impacting overall system performance.
New cards
23
Performance analysis
_____ helps understand how an algorithm scales with larger input sizes, which is crucial for efficiency.
New cards
24
recursive algorithm
____ solves a problem by breaking it down into smaller subproblems of the same type, often using a base case to terminate recursion.
New cards
25
divide and conquer, dynamic programming, and greedy algorithms
_____ are fundamental algorithm design techniques.
New cards
26
dynamic programming
____ is a method for solving complex problems by breaking them down into simpler subproblems and storing the results to avoid redundant calculations.
New cards
27
Greedy algorithm
___ makes the locally optimal choice at each stage with the hope of finding a global optimum.
New cards
28
arrays, linked lists, stacks, queues, trees, and graphs
_____ are common data structures used in algorithms
New cards
29
impacts the efficiency of an algorithm and time complexity for operations like insertion, deletion, and searching.
How does the choice of data structure affect algorithm performance?
New cards
30
helps identify the most efficient solution for a given problem, considering factors like time complexity, space complexity, and ease of implementation.
What is the purpose of analyzing different algorithms for standard problems?
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