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Data Structures & Algorithms: A Comprehensive Guide for Computing Students, Summaries of Computer Science

Mandalay Technological UniversityComputer Science

data structure and algorithm assignment

Typology: Summaries

2022/2023

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Pearson BTEC Levels 4 and 5 Higher Nationals in Computing
Specification – Issue 2 – March 2022 © Pearson Education Limited 2022
228
Unit 19: Data Structures & Algorithms
Unit code T/618/7430
Unit level 5
Credit value 15
Introduction
Knowing how to implement algorithms and data structures that solve real problems,
and knowing the purpose, complexity and use of algorithms is part of an essential
toolkit for software engineers. An algorithm is a sequence of instructions used to
manipulate data held in a structured form and together with data structures
constitute design patterns for solving a diverse range of computer problems,
including network analysis, cryptography, data compression and process control.
This unit introduces students to data structures and how they are used in algorithms,
enabling them to design and implement data structures. Students are introduced to
the specification of abstract data types and will explore their use in concrete data
structures. Using this knowledge, students should be able to develop solutions by
specifying, designing and implementing data structures and algorithms in a variety of
programming paradigms for an identified need.
Among the topics included in this unit are abstract data types specification, formal
data notations, data encapsulation, complex data structures, programming language
implementations using handles, pointers, classes and methods, algorithm types, data
structure libraries, algorithm complexity, asymptotic testing and benchmarking.
On completion of this unit, students should be able to identify program data
requirements, specify abstract data types using a formal notation, translate into
concrete data structures and be able to develop, using a programming paradigm,
different sorting, searching and navigational algorithms that implement complex data
structures and evaluate their effectiveness. As a result, students will have developed
skills such as communication literacy, critical thinking, analysis, synthesis, reasoning
and interpretation, which are crucial for gaining employment and developing
academic competence.
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Pearson BTEC Levels 4 and 5 Higher Nationals in Computing

Unit 19: Data Structures & Algorithms

Unit code T/618/

Unit level 5

Credit value 15

Introduction

Knowing how to implement algorithms and data structures that solve real problems,

and knowing the purpose, complexity and use of algorithms is part of an essential

toolkit for software engineers. An algorithm is a sequence of instructions used to

manipulate data held in a structured form and together with data structures

constitute design patterns for solving a diverse range of computer problems,

including network analysis, cryptography, data compression and process control.

This unit introduces students to data structures and how they are used in algorithms,

enabling them to design and implement data structures. Students are introduced to

the specification of abstract data types and will explore their use in concrete data

structures. Using this knowledge, students should be able to develop solutions by

specifying, designing and implementing data structures and algorithms in a variety of

programming paradigms for an identified need.

Among the topics included in this unit are abstract data types specification, formal

data notations, data encapsulation, complex data structures, programming language

implementations using handles, pointers, classes and methods, algorithm types, data

structure libraries, algorithm complexity, asymptotic testing and benchmarking.

On completion of this unit, students should be able to identify program data

requirements, specify abstract data types using a formal notation, translate into

concrete data structures and be able to develop, using a programming paradigm,

different sorting, searching and navigational algorithms that implement complex data

structures and evaluate their effectiveness. As a result, students will have developed

skills such as communication literacy, critical thinking, analysis, synthesis, reasoning

and interpretation, which are crucial for gaining employment and developing

academic competence.

Pearson BTEC Levels 4 and 5 Higher Nationals in Computing

Learning Outcomes

By the end of the unit students will be able to:

LO1 Examine abstract data types, concrete data structures and algorithms

LO2 Specify abstract data types and algorithms in a formal notation

LO3 Implement complex data structures and algorithms

LO4 Assess the effectiveness of data structures and algorithms.

Pearson BTEC Levels 4 and 5 Higher Nationals in Computing

Testing and debugging:

Testing code to ensure it is secure and can handle user errors, identifying and

creating test scenarios, applying structured techniques to problem solving,

debugging code, understanding the structure of programmes to identify and

resolve issues.

LO4 Assess the effectiveness of data structures and algorithms

Use of data structure libraries (DSL):

Limitations of DSL, manual selection of data structures, theoretical analysis,

asymptotic analysis, size of N, Big O notation.

Algorithm effectiveness:

Run time benchmark, compiler/interpreter dependencies, resource usage,

degree of parallelism, time, space, power performance, efficiency of garbage

collection.

Pearson BTEC Levels 4 and 5 Higher Nationals in Computing

Learning Outcomes and Assessment Criteria

Pass Merit Distinction LO1 Examine abstract data types, concrete data structures and algorithms P1 Create a design specification for data structures, explaining the valid operations that can be carried out on the structures. P2 Determine the operations of a memory stack and how it is used to implement function calls in a computer.

M1 Illustrate, with an example, a concrete data structure for a First in First out (FIFO) queue. M2 Compare the performance of two sorting algorithms.

D1 Analyse the operation, using illustrations, of two network shortest path algorithms, providing an example of each.

LO2 Specify abstract data types and algorithms in a formal notation P3 Specify the abstract data type for a software stack using an imperative definition.

M3 Examine the advantages of encapsulation and information hiding when using an ADT.

D2 Discuss the view that imperative ADTs are a basis for object orientation offering a justification for the view.

Pearson BTEC Levels 4 and 5 Higher Nationals in Computing

Recommended Resources

Textbooks

Cormen, T. et al (1990) Introduction to Algorithms. MIT Press.

Cormen, T. et al (2002 ) Instructor’s Manual: Introduction to Algorithms.

MIT Press.

Heineman, G. et al (2009) Algorithms in a Nutshell. O’Reilly Publishing.

Larmouth, J. (1999) ASN.1 Complete. Kaufman Publishing.

Leiss, E. (2007) A Programmer’s Companion to Algorithm Analysis. Chapman & Hall.

Sedgewick, R. (1983) Algorithms. Addison-Wesley.

Wirth, N. (2004) Algorithms and Data Structures. Oberon.

Links

This unit links to the following related units:

Unit 1: Programming

Unit 20: Applied Programming and Design Principles

Unit 30: Applied Cryptography in the Cloud.