📘 algorithms
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Max Subarray F95Ed0
1. **Problem Statement:** We are given an array of integers, including both positive and negative numbers. We need to find the contiguous subarray within this array that has the ma
Medtrace Algorithms 8764F0
1. **Problem a: Time Complexity Analysis of CleanAndNormalize**
The pseudo-code has nested loops: outer loop runs $n$ times, inner loop runs from $i$ to $n$, averaging about $\frac
Tree Encoding F19Ecc
1. The problem is to analyze the time complexity of the canonical encoding algorithm for a tree with $n$ nodes.
2. The given complexity is $O(n \log n)$, derived from sorting the c
Knapsack Variant Ac2D11
1. **Problem Statement:** We have a variant of the 0-1 knapsack problem where each item $a_i$ can be rejected, fully accepted, or half-accepted. The capacity is $S$, and $V(T,m)$ i
Knapsack Variant D5Dad4
1. **Problem Statement:** We have a variant of the 0-1 knapsack problem with capacity $S$ and $n$ items. Each item $a_i$ can be accepted fully, rejected, or half-accepted. Half-acc
Max Sum Decreasing Subsequence 3A012D
1. **Problem Statement:** We want to find the maximum sum of a decreasing subsequence ending at each index $i$ in an array $A$ of distinct positive integers.
2. **Definition:** Let
Bucket Sort Time Bd962D
1. **Problem Statement:** We have $n$ items to sort using BucketSort with $k = \frac{n}{\log \log n}$ buckets. The input distribution is non-uniform: half the items are uniformly d
Bucket Sort Time F7A3F9
1. **Problem Statement:** We have $n$ items to sort using BucketSort with $k = \frac{n}{\log \log n}$ buckets. The input distribution is non-uniform: half the items are uniformly d
Dp Runtime Deff23
1. **Problem statement:** We want to analyze the running time of a dynamic programming algorithm Alg that fills a table of size $n^2$ for an input array of size $n$.
2. **Understan
Dp Runtime F8D067
1. **Problem Statement:** We want to analyze the running time of a dynamic programming algorithm Alg that fills a table of size $n^2$ for an input array of size $n$.
2. **Understan
Stability Algorithm A 9Dc425
1. **Problem Statement:** Determine if the sorting algorithm A described is stable.
2. **Recall the definition of stability in sorting:** A sorting algorithm is stable if it preser
Dfs Maze
1. **Problem Statement:**
Traverse the given 6x6 maze from the start cell S at (0,2) to the goal cell G at (5,5) using Depth-First Search (DFS). Walls are blocked cells and cannot
Recurrence T N Minus 2
1. **Problem statement:** Solve the recurrence relation $T(n) = T(n - 2) + n^2$ using the Master Theorem step-by-step.
2. **Note:** The Master Theorem applies to recurrences of the
Time Comparison
1. **Problem Statement:** Compare the time complexities of BottomUpSort (Merge Sort) and SelectionSort for $n = 32,768$.
2. **Formulas and Rules:**
Bottova Tree
1. The problem is to solve the "tree from Bottova," which likely refers to a specific mathematical or algorithmic problem involving a tree structure named Bottova.
2. Since the exa
Bubble Down Time
1. Let's define Bubble-Down time for a node of height $h$ as the number of comparisons or swaps needed until the node reaches a leaf.
2. Since at each step in Bubble-Down the node
Bubble Down Complexity
1. The Bubble-Down operation (also known as Sift-Down) for a node of height $h$ in a heap involves comparing and possibly swapping the node with its children down the tree until th
Max Sum Subarray
1. **Problem Statement:** We want to find a contiguous subarray of length $\log n$ in an array of $n$ numbers (where $n$ is a power of 2) that has the maximum sum.
2. **Naive Appro
Median Of Three
1. **Stating the problem:** We analyze a variant of the Median-of-Five algorithm where the input of size $n$ is partitioned into $\frac{n}{3}$ blocks of size 3, instead of $\frac{n
Median Three Time
1. **Problem statement:** We have a variant of the Median-of-Five algorithm using $n/3$ blocks of size 3 instead of $n/5$ blocks of size 5. Our goals are:
- a) Derive a recursive t
Median Of Three
1. **Problem statement:** We consider a Median-of-Five variant where the input of size $n$ is partitioned into $\frac{n}{3}$ blocks of size 3 instead of 5.
2. **Part (a) - Deriving