The implication and taxonomy of linear and nonlinear data structure
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Date
2015
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UNIVERSITY OF MANAGEMENT AND TECHNOLOGY
Abstract
The Linear and nonlinear Data Structures are core part of computer science or curriculum. Linear data structure covered all types of consecutive indexed and reference wise ordinal data structures. For example, array, linked list and linear collection of abstract data types. We cover binary tree in nonlinear data structure. All these topics were covered in most of CS related core courses and included in data structure text book. Major issue is that what topic is to be covered and what subtopics is to be taught by undergraduate students. This study propose classification of topics and subtopics in linear and nonlinear data structure. Major contribution of this research is to figure out all variants of linear and nonlinear data structure topics and provide standard taxonomies. Each dimension has explained in terms of structured, object oriented, memory diagrams, applications, implementation and complexity and have also discussed its application using design patterns. It will facilitate students to learn and visualize more about linear and nonlinear data structure concepts and for teachers to revise their course outlines, implement standard code and visualize memory diagrams.
Description
Supervised by: Dr. Muhammad Shoaib Farooq
Keywords
MA Thesis, Linear and nonlinear data structures, Taxonomy, Data structures