School: Science

This unit information may be updated and amended immediately prior to semester. To ensure you have the correct outline, please check it again at the beginning of semester.

  • Unit Title

    Data Structures
  • Unit Code

    CSP2348
  • Year

    2017
  • Enrolment Period

    1
  • Version

    1
  • Credit Points

    15
  • Full Year Unit

    N
  • Mode of Delivery

    On Campus
    Online
  • Unit Co-ordinator

    Dr Jitian XIAO

Description

This unit focuses on data abstraction and the realisation of abstract data types as re-usable and generic modules using Java as the vehicular programming language. Basic algorithmic analysis is also introduced.

Prerequisite Rule

Students must pass 1 units from CSP1150

Equivalent Rule

Unit was previously coded CSP1243, CSP1250

Learning Outcomes

On completion of this unit students should be able to:

  1. Analyse complexity and performance of their associated algorisms.
  2. Apply abstract data types to programming practices.
  3. Describe the concept, application, and specification of an abstract data type and employ Java classes to encapsulate abstract data types.
  4. Describe the general principles of algorithm complexity and performance.
  5. Outline the role of abstract data types in software reusability.

Unit Content

  1. Algorithms: fundamental principles of algorithms; analysis of algorithms to determine their time and space efficiency; the notion of complexity of algorithms; recursive algorithms and their complexity.
  2. Commonly used ADTs (Stacks, Queues, Lists, Sets, Maps): their concepts and applications; their design requirements; their implementation using alternative data structures; existing implementation in the Java classes.
  3. Data structures (arrays, linked lists, binary trees, and hash tables): their general properties; their specific properties in Java; their algorithms in insertion, deletion, searching, merging, and sorting.
  4. Fundamentals of abstract data types (ADTs): distinction between data types and abstract data types; design considerations of ADTs; ADTs and software reusability; ADTs in Java Collection.

Teaching and Learning Processes

Knowledge and skills will be developed by a combination of lecture-based material and practical workshop/tutorial sessions. A modern programming language will be the vehicle to illustrate lecture material and to complete workshop tasks.

Assessment

GS1 GRADING SCHEMA 1 Used for standard coursework units

Students please note: The marks and grades received by students on assessments may be subject to further moderation. All marks and grades are to be considered provisional until endorsed by the relevant Board of Examiners.

ON CAMPUS
TypeDescriptionValue
WorkshopWorkshop activities20%
AssignmentPaired programming assignment20%
Examination ^End of semester examination60%
ONLINE
TypeDescriptionValue
WorkshopWorkshop activities20%
AssignmentPaired programming assignment20%
Examination ^End of semester examination60%

^ Mandatory to Pass

Core Reading(s)

  • Goodrich M. T., T. R., & H., G. M. (2013). Data Structures and Algorithms in Python. USA: Wiley.

Disability Standards for Education (Commonwealth 2005)

For the purposes of considering a request for Reasonable Adjustments under the Disability Standards for Education (Commonwealth 2005), inherent requirements for this subject are articulated in the Unit Description, Learning Outcomes and Assessment Requirements of this entry. The University is dedicated to provide support to those with special requirements. Further details on the support for students with disabilities or medical conditions can be found at the Student Equity, Diversity and Disability Service website.

Academic Misconduct

Edith Cowan University has firm rules governing academic misconduct and there are substantial penalties that can be applied to students who are found in breach of these rules. Academic misconduct includes, but is not limited to:

  • plagiarism;
  • unauthorised collaboration;
  • cheating in examinations;
  • theft of other students’ work;

Additionally, any material submitted for assessment purposes must be work that has not been submitted previously, by any person, for any other unit at ECU or elsewhere.

The ECU rules and policies governing all academic activities, including misconduct, can be accessed through the ECU website.

CSP2348|1|1

School: Science

This unit information may be updated and amended immediately prior to semester. To ensure you have the correct outline, please check it again at the beginning of semester.

  • Unit Title

    Data Structures
  • Unit Code

    CSP2348
  • Year

    2017
  • Enrolment Period

    2
  • Version

    1
  • Credit Points

    15
  • Full Year Unit

    N
  • Mode of Delivery

    On Campus
    Online
  • Unit Co-ordinator

    Dr Jitian XIAO

Description

This unit focuses on data abstraction and the realisation of abstract data types as re-usable and generic modules using Java as the vehicular programming language. Basic algorithmic analysis is also introduced.

Prerequisite Rule

Students must pass 1 units from CSP1150

Equivalent Rule

Unit was previously coded CSP1243, CSP1250

Learning Outcomes

On completion of this unit students should be able to:

  1. Analyse complexity and performance of their associated algorisms.
  2. Apply abstract data types to programming practices.
  3. Describe the concept, application, and specification of an abstract data type and employ Java classes to encapsulate abstract data types.
  4. Describe the general principles of algorithm complexity and performance.
  5. Outline the role of abstract data types in software reusability.

Unit Content

  1. Algorithms: fundamental principles of algorithms; analysis of algorithms to determine their time and space efficiency; the notion of complexity of algorithms; recursive algorithms and their complexity.
  2. Commonly used ADTs (Stacks, Queues, Lists, Sets, Maps): their concepts and applications; their design requirements; their implementation using alternative data structures; existing implementation in the Java classes.
  3. Data structures (arrays, linked lists, binary trees, and hash tables): their general properties; their specific properties in Java; their algorithms in insertion, deletion, searching, merging, and sorting.
  4. Fundamentals of abstract data types (ADTs): distinction between data types and abstract data types; design considerations of ADTs; ADTs and software reusability; ADTs in Java Collection.

Teaching and Learning Processes

Knowledge and skills will be developed by a combination of lecture-based material and practical workshop/tutorial sessions. A modern programming language will be the vehicle to illustrate lecture material and to complete workshop tasks.

Assessment

GS1 GRADING SCHEMA 1 Used for standard coursework units

Students please note: The marks and grades received by students on assessments may be subject to further moderation. All marks and grades are to be considered provisional until endorsed by the relevant Board of Examiners.

ON CAMPUS
TypeDescriptionValue
WorkshopWorkshop activities20%
AssignmentPaired programming assignment20%
Examination ^End of semester examination60%
ONLINE
TypeDescriptionValue
WorkshopWorkshop activities20%
AssignmentPaired programming assignment20%
Examination ^End of semester examination60%

^ Mandatory to Pass


Disability Standards for Education (Commonwealth 2005)

For the purposes of considering a request for Reasonable Adjustments under the Disability Standards for Education (Commonwealth 2005), inherent requirements for this subject are articulated in the Unit Description, Learning Outcomes and Assessment Requirements of this entry. The University is dedicated to provide support to those with special requirements. Further details on the support for students with disabilities or medical conditions can be found at the Student Equity, Diversity and Disability Service website.

Academic Misconduct

Edith Cowan University has firm rules governing academic misconduct and there are substantial penalties that can be applied to students who are found in breach of these rules. Academic misconduct includes, but is not limited to:

  • plagiarism;
  • unauthorised collaboration;
  • cheating in examinations;
  • theft of other students’ work;

Additionally, any material submitted for assessment purposes must be work that has not been submitted previously, by any person, for any other unit at ECU or elsewhere.

The ECU rules and policies governing all academic activities, including misconduct, can be accessed through the ECU website.

CSP2348|1|2