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**Subject Computer Science Data Structures and Algorithms**

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One of the measurements for the achieved performance is represented by the actual running time of the program. However, since the test of the Kruskalâ€™s implementation was done (according the requirements) only on a provided graph, this timing is not very relevant compared with the situation when the tests were performed on more input graphs.

Kruskalâ€™s algorithm considers the edges for adding to the MST by taking one by one in increasing order. The sorting can be performed in many ways by using different data structures. In this case it was preferred an easy implementation based on selection sort....

Kruskalâ€™s algorithm considers the edges for adding to the MST by taking one by one in increasing order. The sorting can be performed in many ways by using different data structures. In this case it was preferred an easy implementation based on selection sort....

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Two Problems with Partition Sum and Undirected & Unweighted Graph Properties

$15.00

Partition

Problem

Sum

Equal

Solution

Largest

Independent

Set

Undirected

Unweighted

Euler

Cycle

Hamilton

Graph

Dynamic Programming Model for A Version of Job Scheduling Problem

$30.00

Knapsack

Reduction

Algorithm

Complexity

Problem

Job

Scheduling

Dynamic

Programming

OPT

Optimal

Swapping

Exchange

Argument

Playful

Subset

Deadline

Value

Size

Profit

Function

Solution

Set

Array

Two

Dimensional

Selection

Reorder

M

Knapsack

Reduction

Algorithm

Complexity

Problem

Job

Scheduling

Dynamic

Programming

OPT

Optimal

Swapping

Exchange

Argument

Playful

Subset

Deadline

Value

Size

Profit

Function

Solution

Set

Array

Two

Dimensional

Selection

Reorder

M

Research Proposal - Applications of Graph Theory in the Study of Community Structures (750 words)

$13.00

Computer Science

Data

Graph

Theory

Community

Structure

Research

Proposal

Objective

Result

Scope

Questions

Social

Network

Algorithm

Dynamic

Node

Edge

NP-Hard

NP-Complete

NP

P

Problem

Approximation

Complexity

Analysis

Topology

Computer Science

Data

Graph

Theory

Community

Structure

Research

Proposal

Objective

Result

Scope

Questions

Social

Network

Algorithm

Dynamic

Node

Edge

NP-Hard

NP-Complete

NP

P

Problem

Approximation

Complexity

Analysis

Topology

Algorithm Design about Linear Time Median, BFS with Loop Invariant, and Sorting Post Order Numbers

$20.00

Linear

Time

Median

Find

Algorithm

Group

Element

List

Post

Order

Traversal

Without

Sorting

BFS

Breadth

First

Search

Loop

Invariant

Layer

Graph

Proof

Complexity

Left

Right

Root

Node

Sorted

Linear

Time

Median

Find

Algorithm

Group

Element

List

Post

Order

Traversal

Without

Sorting

BFS

Breadth

First

Search

Loop

Invariant

Layer

Graph

Proof

Complexity

Left

Right

Root

Node

Sorted