II. Read each problem carefully and present an algorithm with the required running-time to solve each problem. 1. In class we discussed that directed acyclic graphs (DAG) can be used to represent dependency/precedence relations. One example is modeling task dependency where tasks are represented as vertices and edges represents direct dependencies between tasks, e.g., if task T; requires task I, then there is an edge from vertex i to vertex j. Arranging tasks with respect to their dependencies can easily be done by performing topological sort to the DAG. a. Describe an algorithm that runs in O(n + m) time that given two tasks, T, and I, determines if task T, can be performed without performing task T₁. Note that I, is not required if it is not a direct or indirect dependency of T. Task I, is an indirect dependency of task T: if there is no edge from T, to T, but I, must appear before 7, in the topological order. b. Describe an algorithm that runs in O(n + m) time that given a task T₁, outputs the minimum possible position of tasks T, in any topological order.

Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
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II. Read each problem carefully and present an algorithm with the required running-time to solve each
problem.
1. In class we discussed that directed acyclic graphs (DAG) can be used to represent
dependency/precedence relations. One example is modeling task dependency where tasks are
represented as vertices and edges represents direct dependencies between tasks, e.g., if task Ti
requires task I, then there is an edge from vertex i to vertex j. Arranging tasks with respect to their
dependencies can easily be done by performing topological sort to the DAG.
a. Describe an algorithm that runs in O(n + m) time that given two tasks, T, and I₁, determines if
task T, can be performed without performing task T₁. Note that I, is not required if it is not a direct
or indirect dependency of T₁. Task I, is an indirect dependency of task I, if there is no edge from
T, to T, but I must appear before 7, in the topological order.
b. Describe an algorithm that runs in O(n + m) time that given a task T₁, outputs the minimum
possible position of tasks T, in any topological order.
Transcribed Image Text:II. Read each problem carefully and present an algorithm with the required running-time to solve each problem. 1. In class we discussed that directed acyclic graphs (DAG) can be used to represent dependency/precedence relations. One example is modeling task dependency where tasks are represented as vertices and edges represents direct dependencies between tasks, e.g., if task Ti requires task I, then there is an edge from vertex i to vertex j. Arranging tasks with respect to their dependencies can easily be done by performing topological sort to the DAG. a. Describe an algorithm that runs in O(n + m) time that given two tasks, T, and I₁, determines if task T, can be performed without performing task T₁. Note that I, is not required if it is not a direct or indirect dependency of T₁. Task I, is an indirect dependency of task I, if there is no edge from T, to T, but I must appear before 7, in the topological order. b. Describe an algorithm that runs in O(n + m) time that given a task T₁, outputs the minimum possible position of tasks T, in any topological order.
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