SSST Subjects

Data Structures

Computer Science


Information Systems


Programme(s) where module is offered

  • BSc Computer Science with Electrical Engineering
  • BSc Computer Science with Economics
  • BSc Computer Science with Management
  • BSc Computer Science with International Relations
  • BSc Computer Science with Political Science
  • BSc Information Systems with Electrical Engineering
  • BSc Information Systems with Economics
  • BSc Information Systems with Management
  • BSc Information Systems with International Relations
  • BSc Information Systems with Political Science;

Status (core, option, free choice)



FHEQ Level



Unit Value



Semester taught



Pre-Requisite Modules or Qualifications

MATH180, CSIS120


Module Code



Module coordinator

Dr. Dzejla Medjedovic


Applicable From



Educational Aims of the Module

  • This module introduces students to fundamental data structures and basic performance measures for these data structures.
  • The module teaches both the theoretical and programming underpinnings of the data structures as well as main applications and usage scenarios.
  • The module emphasizes the connections between the mathematical analysis and programming aspects of data structures and how they together affect the performance.
  • For each data structure, students learn to distinguish their performance with respect to the search/insert/delete performance as well as the space requirements and the implementation complexity.
  • The main expected outcome of the class is when presented with a computational problem, students are able to suggest the right data structure to use to solve it.
  • Throughout their assignments, students learn to use data structures in different scenarios.
  • The online judge tool LeetCode is used for students to submit their programming exercise in the programming language of their choice.

Module Outline/Syllabus

  • Introduction to data structures, Asymptotic notation
  • Arrays, Resizing arrays, Matrices
  • Basic sorts: Bubble sort, Selection sort, Insertion sort
  • Stacks, Queues
  • Linked Lists
  • Recursion
  • Trees: Introduction
  • Binary search trees
  • Red-black trees
  • AVL trees
  • Splaytrees
  • Heaps, Priority queues
  • Hashing
  • Cuckoo hashing
  • Bloom filters
  • Graphs
  • String data structures

Student Engagement Hours

Type Number per Term Duration Total Time
Lectures 30 2 hours 60 hours
Tutorials 15 2 hours 30 hours
Total Guided/Independent Learning Hours 110
Total Contact Hours 90
Total Engagement Hours 200

Assessment Method Summary

Type Number Required Duration / Length Weighting Timing / Submission Deadline
Final exam 1 180 minutes 50% End of semester
Mid-term exam 1 90 minutes 15% Week 9
Programming challenge 1 3,000 words 20% Semester-long
Assignment 3 800 words 15% Weeks 4, 8, 12

Module Outcomes

Teaching and Learning Strategy:

  • Laboratory sessions 
  • Lectures delivered containing the material from themodule outline 
  • Regular presentation of solutions with peer feedback and discussion are encouraged both during lecture time and especially during lab time 
  • Programming challenge
  • Assignment 
  • Programming challenge
  • Reading and in class practice 
  • In-class communication
  • Reading and exercises during tutorial sessions 
  • Reading and in class practice 

Assessment Strategy

  • Programming Challenge 
  • Mid-term exam 
  • Final exam 
  • Assignment 

Key Texts and/or other learning materials

Set text

  • Karumanchi, N., 2011, Data Structures and Algorithms Made Easy: Data Structure and Algorithmic Puzzles, 2nd Edition

Supplementary Materials

  • Lafore, R., 2002, Data Structures and Algorithms in Java, 2nd Edition, SAMS
  • Goodrich & Tamassia, 2014, Data Structures and Algorithms in Java , 6th Edition, John Wiley & sons
  • Mark Allen Weiss, 1996, Data Structures and Algorithm Analysis in C, 2nd Edition, Addison -Wesley
  • Mark Allen Weiss, 2012, Data Structures and Algorithm Analysis in Java 3rd Edition, Edition, Addison-Wesley.
  • David Flanagan, 2014, Java in a Nutshell, 6th Edition, O'Reilly
  • Bruce Eckel, 2006,Thinking in Java, Prentice-Hall PTR.
  • Kathy Sierra and Bert Bates, 2005, Head First Java, 2nd Edition, O'Reilly
  • Bruno Preiss, 1999, Data structures and Algorithms with Object Oriented Design Patterns in Java, JohnWiley& Sons.
  • Clifford Shaffer, 2011, Data Structures and Algorithm Analysis,3rd Edition, Dover Publications
  • Sartaj Sahni, 2004, Data Structures, Algorithms, and Applications in Java, 2nd Edition, Silicon Press Alfred Aho, 1983, John Hopcroft, and Jeffrey Ullman, Data Structures and Algorithms, Addison-Wesley
  • MIT Algorithms and Data Structures Podcasts [online], 6th June 2016).

Please note

This specification provides a concise summary of the main features of the module and the learning outcomes that a typical student might reasonably be expected to achieve and demonstrate if he/she takes full advantage of the learning opportunities that are provided.  More detailed information on the learning outcomes, content and teaching, learning and assessment methods of each module and programme can be found in the departmental or programme handbook.  The accuracy of the information contained in this document is reviewed annually by the University of Buckingham and may be checked by the Quality Assurance Agency.

Date of Production : Autumn 2016

Date approved by School Learning and Teaching Committee: 28th September 2016

Date approved by School Board of Study : 12th October 2016

Date approved by University Learning and Teaching Committee: 2nd November 2016

Date of Annual Review: December 2017


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