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FIT2004 Algorithms and data structures - Semester 1, 2014

This unit introduces students to problem solving concepts and techniques fundamental to the science of programming. In doing this it covers problem specification, algorithmic design, analysis and implementation. Detailed topics include analysis of best, average and worst-case time and space complexity; introduction to numerical algorithms; recursion; advanced data structures such as heaps and B-trees; hashing; sorting algorithms; searching algorithms; graph algorithms; and numerical computing.

Mode of Delivery

  • Clayton (Day)
  • Malaysia (Day)

Workload Requirements

Minimum total expected workload equals 12 hours per week comprising:

(a.) Contact hours for on-campus students:

  • Two hours of lectures
  • One 3-hour laboratory

(b.) Additional requirements (all students):

  • A minimum of 7 hours of independent study per week for lab preparation and reading.

Additional workload requirements

Students will be expected to spend a total of 12 hours per week during semester on this unit as follows:

  • Lectures: 2 hours per week
  • One 3-hour laboratory per week (note, every alternate week starting Week 3, the 3 hour slot will be split into a 1-hour tutorial followed by a 2 hour lab)
  • Reading: 3.5 hours per week
  • Lab Preparation: 3.5 hours per week

Unit Relationships

Prohibitions

CSE2304, FIT2009

Prerequisites

One of FIT1008, FIT1015 or CSE1303 and 6 points of Level 1 mathematics.

Chief Examiner

Campus Lecturer

Clayton

Arun Konagurthu

Consultation hours: TBA in week 1 S1/2014

Malaysia

Anuja Dharmaratne

Your feedback to Us

Monash is committed to excellence in education and regularly seeks feedback from students, employers and staff. One of the key formal ways students have to provide feedback is through the Student Evaluation of Teaching and Units (SETU) survey. The University’s student evaluation policy requires that every unit is evaluated each year. Students are strongly encouraged to complete the surveys. The feedback is anonymous and provides the Faculty with evidence of aspects that students are satisfied and areas for improvement.

For more information on Monash’s educational strategy, see:

www.monash.edu.au/about/monash-directions/ and on student evaluations, see: www.policy.monash.edu/policy-bank/academic/education/quality/student-evaluation-policy.html

Previous Student Evaluations of this Unit

Student feedback has informed a substantive revision to the unit that includes reorienting the content to be supported by a single principal text book and reorganisation to improve the incremental progression of unit content.

If you wish to view how previous students rated this unit, please go to
https://emuapps.monash.edu.au/unitevaluations/index.jsp

Academic Overview

Learning Outcomes

At the completion of this unit students will be able to:
  • analyse general problem solving strategies and algorithmic paradigms, and apply them to solving new problems;
  • prove correctness of programs, analyse their space and time complexities;
  • compare and contrast various abstract data types and use them appropriately;
  • develop and implement algorithms to solve computational problems.

Unit Schedule

Week Activities Assessment
0 Revise concepts learnt in FIT1029 (Dynamic Programming, Divide-Conquer, sorting, Recursion, Invariants, Trees etc.) No formal assessment or activities are undertaken in week 0
1 Introduction Abstract Data Types, Mathematics, Logic, Grammar, Lists and Trees  
2 Verification, Correctness, Logic, Program Termination and Simple sorts Non assessed 3hr lab
3 Introduction to Heaps, priority queues, recursive sorts Non assessed 1hr tute + 2hr lab
4 Dynamic Programming Paradigm, Divide and Conquer paradigm using Edit Distance variants (Hirschberg and Ukkonen) Assignment 1 due (Assessed 3hr lab)
5 Searching, Hashing and Lookup structures Non assessed 1hr tute + 2hr lab
6 Tables, Tries, Radix tree, B-tree etc. Assignment 2 due (Assessed 3hr lab)
7 Searching and pattern matching in strings Non assessed 1hr tute + 2hr lab
8 Graph algorithms and path problems Assignment 3 due (Assessed 3hr lab)
9 Flow Problems and Complexity Non assessed 1hr tute + 2hr lab
10 Suffix trees and Suffix arrays Assignment 4 due (Assessed 3hr lab)
11 Recursion (Linear, binary, n-ary) Non assessed 1hr tute + 2hr lab
12 Summing up design priniciples and useful algorithmic strategies Assignment 5 due (Assessed 3hr lab)
  SWOT VAC No formal assessment is undertaken in SWOT VAC
  Examination period LINK to Assessment Policy: http://policy.monash.edu.au/policy-bank/
academic/education/assessment/
assessment-in-coursework-policy.html

*Unit Schedule details will be maintained and communicated to you via your learning system.

Teaching Approach

Lecture and tutorials or problem classes
This teaching and learning approach provides facilitated learning, practical exploration and peer learning.

Assessment Summary

Examination (3 hours): 70%; In-semester assessment: 30%

Assessment Task Value Due Date
Assignment 1 6% Week 4
Assignment 2 6% Week 6
Assignment 3 6% Week 8
Assignment 4 6% Week 10
Assignment 5 6% Week 12
Examination 1 70% To be advised

Assessment Requirements

Assessment Policy

Assessment Tasks

Participation

  • Assessment task 1
    Title:
    Assignment 1
    Description:
    Practical problems arising from the material covered in lectures and tutorials.
    Weighting:
    6%
    Criteria for assessment:
    • Demonstrate code where applicable
    • Explain your solutions
    Due date:
    Week 4
  • Assessment task 2
    Title:
    Assignment 2
    Description:
    Practical problems arising from the material covered in lectures and tutorials.
    Weighting:
    6%
    Criteria for assessment:
    • Demonstrate code where applicable
    • Explain your solutions
    Due date:
    Week 6
  • Assessment task 3
    Title:
    Assignment 3
    Description:
    Practical problems arising from the material covered in lectures and tutorials.
    Weighting:
    6%
    Criteria for assessment:
    • Demonstrate code where applicable
    • Explain your solutions
    Due date:
    Week 8
  • Assessment task 4
    Title:
    Assignment 4
    Description:
    Practical problems arising from the material covered in lectures and tutorials.
    Weighting:
    6%
    Criteria for assessment:
    • Demonstrate code where applicable
    • Explain your solutions
    Due date:
    Week 10
  • Assessment task 5
    Title:
    Assignment 5
    Description:
    Practical problems arising from the material covered in lectures and tutorials.
    Weighting:
    6%
    Criteria for assessment:
    • Demonstrate code where applicable
    • Explain your solutions
    Due date:
    Week 12

Examinations

  • Examination 1
    Weighting:
    70%
    Length:
    3 hours
    Type (open/closed book):
    Closed book
    Electronic devices allowed in the exam:
    None

Learning resources

Reading list

Main reading:

  • M. A. Weiss. Data Structures and Algorithm Analysis in Java (Relevant to the course plan are  Chapters 1, 2, 3, 4 (not splay trees), 5 (linear, chaining, quadratic), Ch6 (heap and heap sort), Ch7 (relevant sorts), Ch9 (topological sort, paths, spanning Trees, and Ch8 (where relevant), and Ch10.)

 Additional reading (chapters to be specified clearly in the lecture slides as the course progresses):

  • Introduction to Algorithms/ Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein (3rd Edition), McGraw Hill
  • Algorithms on Strings, Trees and Sequences: Computer Science and Computational Biology/ Dan Gusfield , Cambridge University Press
  • The art of computer programming/ Donald E. Knuth Addison-Wesley

Monash Library Unit Reading List (if applicable to the unit)
http://readinglists.lib.monash.edu/index.html

Faculty of Information Technology Style Guide

Feedback to you

Examination/other end-of-semester assessment feedback may take the form of feedback classes, provision of sample answers or other group feedback after official results have been published. Please check with your lecturer on the feedback provided and take advantage of this prior to requesting individual consultations with staff. If your unit has an examination, you may request to view your examination script booklet, see http://intranet.monash.edu.au/infotech/resources/students/procedures/request-to-view-exam-scripts.html

Types of feedback you can expect to receive in this unit are:

  • Informal feedback on progress in labs/tutes
  • Graded assignments without comments
  • Solutions to tutes, labs and assignments

Extensions and penalties

Returning assignments

Assignment submission

It is a University requirement (http://www.policy.monash.edu/policy-bank/academic/education/conduct/student-academic-integrity-managing-plagiarism-collusion-procedures.html) for students to submit an assignment coversheet for each assessment item. Faculty Assignment coversheets can be found at http://www.infotech.monash.edu.au/resources/student/forms/. Please check with your Lecturer on the submission method for your assignment coversheet (e.g. attach a file to the online assignment submission, hand-in a hard copy, or use an online quiz). Please note that it is your responsibility to retain copies of your assessments.

Online submission

If Electronic Submission has been approved for your unit, please submit your work via the learning system for this unit, which you can access via links in the my.monash portal.

Required Resources

Please check with your lecturer before purchasing any Required Resources. Limited copies of prescribed texts are available for you to borrow in the library, and prescribed software is available in student labs.

Java (latest version) installed in the labs, you can download a free copy from Sun Microsystems.

Prescribed text(s)

Limited copies of prescribed texts are available for you to borrow in the library.

Mark Allen Weiss. (2012). Data Structures and Algorithm Analysis in Java. (3rd Edition) Pearson (ISBN: 9780132576277).

Recommended text(s)

Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein. (2009). Introduction to Algorithms. (3rd) MIT Press.

Donald Knuth. (1997). The Art of Computer Programming. () Addison Wesley.

Examination material or equipment

Closed book. No calculators.

Other Information

Policies

Monash has educational policies, procedures and guidelines, which are designed to ensure that staff and students are aware of the University’s academic standards, and to provide advice on how they might uphold them. You can find Monash’s Education Policies at: www.policy.monash.edu.au/policy-bank/academic/education/index.html

Key educational policies include:

Faculty resources and policies

Important student resources including Faculty policies are located at http://intranet.monash.edu.au/infotech/resources/students/

Graduate Attributes Policy

Student Charter

Student services

Monash University Library

Disability Liaison Unit

Students who have a disability or medical condition are welcome to contact the Disability Liaison Unit to discuss academic support services. Disability Liaison Officers (DLOs) visit all Victorian campuses on a regular basis.