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FIT1008 Introduction to computer science - Semester 1, 2012

This unit introduces students to core problem-solving, analytical skills, and methodologies useful for developing flexible, robust, and maintainable software. In doing this it covers a range of conceptual levels, from high level algorithms and data-structures, down to abstract machine models and simple assembly language programming. Topics include data structures; algorithms; object-oriented design and programming; and abstract machines.

Mode of Delivery

Clayton (Day)

Contact Hours

3 hrs lectures/wk, 3 hrs laboratories/wk, 1 hr tutorial/wk

Workload

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

  • Lectures: 3 hours per week
  • Tutorial: 1 hour per week
  • Computer Lab Prac: 1 and 1/2 hours per week (requiring advance preparation) followed by an extra 1 and 1/2 hour for prac marking
  • a minimum of 6 hours of personal study per week in order to satisfy the reading, assignment expectations, including time for newsgroups/discussion groups.

Unit Relationships

Prohibitions

CSE1303, CSC1030, FIT1007, FIT1015

Prerequisites

FIT1002 or equivalent and FIT1029 or equivalent

Chief Examiner

Campus Lecturer

Clayton

Maria Garcia De La Banda

Consultation hours: 11am to 1pm on Mondays at the open area of level 1 in building 63, near the lift

Tutors

Clayton

Maria Garcia De La Banda

Academic Overview

Outcomes

At the completion of this unit, students will have

Developed the ability to:
  • understand abstract data types and, in particular, data structures for stacks, queues, lists, and trees, as well as their associated algorithms for creating and manipulating them. Evaluate the appropriateness of different data structures for a given problem;
  • understand basic searching and sorting algorithms and implement them. Understand the concept of algorithmic complexity. Analyse the complexity of these searching and sorting algorithms as well as other basic algorithms. Compare the complexity of different algorithms for solving a given problem;
  • analyse different implementations of abstract data types and determine their implications regarding complexity, functionality, and memory usage;
  • understand the uses of recursive algorithms and data structures, their advantages and disadvantages. Analyse the complexity of simple recursive algorithms, and their relationship with iteration. Understand basic recursive algorithms for lists and trees, and develop new ones;
  • understand the basic concepts in the object-oriented (OO) programming paradigm;
  • understand the basic concepts in testing;
  • understand the requirements for "good programming practice";
  • understand the different compilation targets, including abstract machine code, assembly language, object code, and machine code. Understand the relationship between simple code in a high level imperative language and its low level translation into assembly code;
  • learn the structure and design of a particular processor simulator. Analyse the execution in this simulator of simple iterative algorithms learned before, thus gaining a deeper understanding of the connection between software and hardware, between an algorithm and its execution;
  • understand how the simulator implements function calling, and use it to reinforce the connection between recursion and iteration.

Developed attitudes that enable them to:
  • conform to programming standards when writing software;
  • use good design principles when constructing systems;
  • take a patient and thorough approach to testing;
  • acknowledge any assistance they have received in writing a program;
  • search for information in appropriate places when necessary.

Developed the skills to:
  • implement their own data-structures. Design and implement Java programs using a variety of data structures and algorithms;
  • implement an object-oriented program consisting of several interacting classes requiring not only basic but also advance object-oriented concepts;
  • construct a test harness for testing an object-oriented program;
  • debug and modify an existing program (written by somebody else);
  • use the Java API classes as part of their programs.

Demonstrated the communication skills necessary to:
  • document a program correctly;
  • explain how parts of a program work.

Graduate Attributes

Monash prepares its graduates to be:
  1. responsible and effective global citizens who:
    1. engage in an internationalised world
    2. exhibit cross-cultural competence
    3. demonstrate ethical values
  2. critical and creative scholars who:
    1. produce innovative solutions to problems
    2. apply research skills to a range of challenges
    3. communicate perceptively and effectively

Assessment Summary

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

Assessment Task Value Due Date
Mid Semester Test (1 hour) 10% Monday 2 April 2012
Pracs (1 and 1/2 hours each) 20% Weekly except in Week 7 when the Mid-Semester Test is held
Examination 1 70% To be advised

Teaching Approach

Lecture and tutorials or problem classes
This teaching and learning approach helps students first encounter the information at lectures, discuss and explore them at length during tutorials, and practice them in a hands-on environment during labs.

Feedback

Our feedback to You

Types of feedback you can expect to receive in this unit are:
  • Informal feedback on progress in labs/tutes
  • Graded assignments without comments
  • Test results and feedback
  • Other: Detailed solutions to tutes

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 SETU, Student Evaluation of Teacher and Unit. 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, and on student evaluations, see:
http://www.monash.edu.au/about/monash-directions/directions.html
http://www.policy.monash.edu/policy-bank/academic/education/quality/student-evaluation-policy.html

Previous Student Evaluations of this unit

As a result of student feedback, this semester we will try to add quizes to each week and provide recorded "mini-lectures" for some of the concepts that students seem to have more difficulties understand.

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

Required Resources

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

Eclipse Platform. One of the two recommended platforms. It can be downloaded from http://www.eclipse.org/downloads/

NetBeans IDE. The other recommended platform. It can be downloaded fro http://netbeans.org/downloads/

Java Development Kit, Version j2sdk-1_5_0_06 or later, Sun Microsystems, Inc. You should download the freeware version. You have no need for the fuller facilities provided in JCreatorPro, and would have to pay for it as well.

The MIPS R2000 simulator SPIM S20 (with its new interface QtSpim).

This, and all the other above, are included as part of the Standard Operating Environment used in Faculty computer Labs.

Unit Schedule

Week Activities Assessment
0 Register for tutorials, pracs and lectures No formal assessment or activities are undertaken in week 0
1 Lectures on Revision of BigO and List (arrays). Tute & Prac. Prac 1
2 Lectures on List Sorting & Stacks and Queues (arrays). Tute & Prac. Prac 2
3 Lectures on Lists, Stacks and Queues (linked nodes). Tute & Prac Prac 3
4 Lectures on Object Oriented Basics. Tute & Prac. Prac 4
5 Lectures on Advanced Object Oriented. Tute & Prac. Prac 5
6 Lectures on Recursion and Recursive Sorts. Tute & Prac. Prac 6
7 Lectures on Binary Trees. Tute & Mid Semester Test. No Prac. Mid Semester Test, Monday, 2 April 2012
8 Lectures on Priority Queues and Heaps. Tute & Prac. Prac 7
9 Lectures on Hash Tables & Number representation. Tute & Prac. Prac 8
10 Lectures on Computer Systems & MIPS. Tute & Prac Prac 9
11 Lectures on MIPS execution of selection and iteration. Tute & Prac. Prac 10
12 Lectures on MIPS function call/return. Tute & Prac Prac 11
  SWOT VAC No formal assessment is undertaken 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 MUSO (Blackboard or Moodle) learning system.

Assessment Requirements

Assessment Policy

Faculty Policy - Unit Assessment Hurdles (http://www.infotech.monash.edu.au/resources/staff/edgov/policies/assessment-examinations/unit-assessment-hurdles.html)

Assessment Tasks

Hurdle Requirements

There are four hurdles in this unit:

  • First, students must actively participate in at least 7 out of 12 tutorials. Active participation includes contributing opinions to a discussion, providing an answer to some question/exercise, or posing a unit-related question.
  • Second, students must achieve at least 50% of the total prac marks.
  • Third, students must achieve at least 50% of the exam mark. 
  • Fourth, students must achieve at least 50% of the total marks.

Students who do not meet all these hurdles can get a maximum of 49N for the unit.

Participation

Students must actively participate in at least 7 out of the 12 tutorials. Active participation includes contributing opinions to a discussion, providing an answer to some question/exercise, or posing a unit-related question.

  • Assessment task 1
    Title:
    Mid Semester Test (1 hour)
    Description:
    This test is performed during the class and covers exam-like questions for the first part of the course. It is intended to give students an idea of how they would perform in the final exam, given their current progress. 
    Weighting:
    10%
    Criteria for assessment:

    This test will evaluate your understanding of the material provided during the first few weeks of semester, your capability to code simple algorithms given a clear specification, and to analyse the behaviour and complexity of simple fragments of code.

    Due date:
    Monday 2 April 2012
  • Assessment task 2
    Title:
    Pracs (1 and 1/2 hours each)
    Description:
    Each week you will need to complete a prac assignment (possibly together with another student). Prac assignments are long (they are designed to take about 4 hours). This means that you must have a significant proportion of the prac completed before attending the scheduled computer lab. The aim of the 1 and 1/2 hour computer lab practical is to iron out any bugs, ask any questions about the prac you have not been able to solve on your own, and improve the parts that your demonstrator points out as lacking (including comments, algorithms, etc). If you do nothing before the1 and 1/2 hours scheduled,  you will soon realise that you do not have enough time to complete it. The prac sheets will be released every Thursday morning and made available in the unit's web page.
    Weighting:
    20%
    Criteria for assessment:
    Every prac sheet contains the assessment criteria used to assess that prac. In addition, demonstrators carry with them a marking guide prepared by the lecturer which indicates how exactly to mark each prac question. You can request the demonstrator to show you the marking guide after he/she has marked your prac.
    Due date:
    Weekly except in Week 7 when the Mid-Semester Test is held

Examinations

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

Assignment submission

It is a University requirement (http://www.policy.monash.edu/policy-bank/academic/education/conduct/plagiarism-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).

Online submission

Please submit your work via Moodle at the time in which you are marked (and, thus, before you leave the lab). You can access Moodle via links in the my.monash portal.

Extensions and penalties

Returning assignments

Other Information

Policies

Student services

The University provides many different kinds of support services for you. Contact your tutor if you need advice and see the range of services available at www.monash.edu.au/students. For Sunway see http://www.monash.edu.my/Student-services, and for South Africa see http://www.monash.ac.za/current/

The Monash University Library provides a range of services and resources that enable you to save time and be more effective in your learning and research. Go to http://www.lib.monash.edu.au or the library tab in my.monash portal for more information. At Sunway, visit the Library and Learning Commons at http://www.lib.monash.edu.my/. At South Africa visit http://www.lib.monash.ac.za/.

Academic support services may be available for students who have a disability or medical condition. Registration with the Disability Liaison Unit is required. Further information is available as follows:

  • Website: http://monash.edu/equity-diversity/disability/index.html;
  • Email: dlu@monash.edu
  • Drop In: Equity and Diversity Centre, Level 1 Gallery Building (Building 55), Monash University, Clayton Campus, or Student Community Services Department, Level 2, Building 2, Monash University, Sunway Campus
  • Telephone: 03 9905 5704, or contact the Student Advisor, Student Commuity Services at 03 55146018 at Sunway

Reading list

(1) Data Structures and Algorithms in Java. Robert Lafore, SAMS.  This book provides a very simple approach to understanding data structures and algorithms.  While the book uses Java to illustrate the implementation, its focus is on the actual data structures and algorithms, rather than on Java, which is very useful for first year students. Very basic and simple.

(2) Data Structures and Algorithms in Java.  Adam Drozdek, Brooks/Cole. More advanced but still appropriate for average and high-end students.

(3) Algorithms in Java. Robert Sedgewick. Parts 1-4. This book is a more in-depth book and assumes a strong mathematical background from the reader. It is recommended for advanced students who want to learn more about the complexity of the algorithms and data structures used.

(4) Data Structures and Algorithm Analysis in Java. Third Edition. Mark Allen Weiss. This is one of the books you will also use in FIT2004. It contains very clear discussions of the algorithms and data-structures, but it assumes knowledge of a difficult Java construct (Generics).Very recommended if you can get pass that.

(4) The Java Programming Language. Fourth Edition. Ken Arnold, James Gosling and David Holmes. Prentice Hall. This book is useful for students who have questions about the Java language. The reason for using the fourth edition is because it is the earliest edition that includes parametric polymorphism (called Generics in Java).