Important!

Please note that this page is informational, and does not replace the official Module Information Pack (MIP). All students attending this module must carefully read the MIP which can be accessed online via Blackboard.

Logistics

Module leader:	Nearchos Paspallis
When and where:	Refer to the timetable (requires login)
Syllabus:	Refer to the Blackboard for the syllabus, assignments, etc (requires login)

Module content

In this module students develop problem-solving skills and they are introduced to the basic concepts of algorithms and data structures.

The module builds on abstract concepts first (pseudocode and flow diagrams) and touches programmatic features later on (references, memory allocation and the Collections API in Java).

We cover the following aspects:

• Puzzles and problem solving
• Algorithm design and analysis.
• Data structures (lists, queues, trees).
• Programming language features (references, dynamic memory allocation).

Learning Outcomes

The main objective of this module is to bring students up to speed with basic programming skills. By the end of the course, students are expected to:

• Generate, explain and evaluate potential solutions to a range of problems
• Describe and evaluate common data structures and algorithms
• Analyse the time and space complexity of simple algorithms
• Select, justify and implement an appropriate data structure for a particular problem
• Design algorithms to solve simple problems
• Find, implement, debug and test algorithms and data structures to solve problems

Resources

Indicative bibliography

Zbigniew Michalewicz, Matthew Michalewicz, Puzzle-based Learning, Hybrid Publishers; 1 edition (May 21, 2008)

V. Anton Spraul, Think Like a Programmer, No Starch Press; 1 edition (Aug 8, 2012)

Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein, Introduction to Algorithms, The MIT Press; 2nd edition (September 1, 2001)

Robert Sedgewick, Kevin Wayne , Algorithms, Algorithms, Addison-Wesley Professional; 4 edition (March 9, 2011)

Mark A. Weiss, Data Structures and Algorithm Analysis in Java, Addison-Wesley; 3 edition (November 18, 2011)

Shaffer C.A., A Practical Introduction to Data Structures and Algorithm Analysis: Java Edition, Prentice Hall; 3.2 edition (June 6, 2012)
[available online at: http://people.cs.vt.edu/~shaffer/Book/]

Additional material (including lecture slides and hand-outs) will be available in Blackboard

Collaboration

Students are encouraged to study and learn in groups. However, individual assignments should be the result of their personal effort (unless group work is explicitly asked).

As a principle, you should follow Gilligan's Island Rule: you can discuss assignments with your classmates, but you should not take any notes (electronic or not) from these meetings, in order to be able to fulfil your assignment independently using your own undestanding of the lectures and the group meetings.

General rules

In addition to the general rules of the University, you should also respect the following rules:

• Attending the lectures is mandatory.
• Students should respect the right of their classmates to attend without disruptions or unnecessary interruptions and thus you should not arrive late (or leave early) unless absolutely necessary.
• You are asked to respect the intellectual copyright legislation, concerning copying and using software and books (in electronic or print form).
• Extensions to assignments will not be granted. In exceptional situations, you should consult the Year-1 Tutor.
• Plagiarism is a serious offense. The University uses plagiarism detection software for all assignments and offenders are subject to the University's rules concerning plagiarism. More details about what plagiarism is (and is not) can be found in your MIP, which is available on Blackboard.