FIT1008 Computer science - Semester 1 , 2007 unit guide

Chief Examiner

Lecturers

Outline

FIT1008 Computer Science 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; introductory topics from software engineering; and translation from simple high level programs to assembler.

Objectives

At the completion of this unit, students will have knowledge to

• Understand abstract data types and, in particular, data structures for stacks, queues, lists, trees, and hash tables, 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.
• Gain a deeper understanding of basic object-oriented (OO) concepts, and understand more advanced ones such as inheritance, polymorphism, information hiding and encapsulation.
• Understand the design principles for building an object-oriented program, such as identify classes, and determine how and when to use inheritance.
• Understand the differences between the four major programming language paradigms: imperative, object oriented, functional and logic.
  
• Understand the software development life cycle. Analyse the advantages and disadvantages of different life cycle models.
• Understand the basic concepts in testing, including execution vs non-execution based testing, glass box and black box testing, correctness proofs, and test case selection. Analyse different testing approaches such as modular, static, dynamic, and formal.
• 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 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.

students will have attitudes that make them:

• 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.

• Create their own data-structures. Design and implement Java programs using a variety of data structures and algorithms.
• Implement an object-oriented program consisting of many 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.
• Use the processor simulator for executing some of the simple iterative programs learned in this subject.
• Determine the time and space requirements of simple algorithms and data structures.

• Document a program correctly.
• Produce appropriate documentation for designing and testing a program.
• Explain how parts of a program work.

Prerequisites

• FIT1001 Computer Systems or equivalent
• FIT1002 Computer Programming or equivalent

Students beginning FIT1008 Computer Science are assumed to be able to:

• Identify the main components of an algorithm (variables, operators, expressions, etc), and write the algorithm associated to the specification of a simple problem.
• Use software development tools such as compilers, debuggers, editors. In particular, design, implement, compile, debug and execute a Java program containing selection, repetition, simple classes and two dimensional arrays.
• Perform decimal to binary and hexadecimal conversions, represent integers, signed fractional, floating point and character data.
• Perform basic boolean algebra and digital logic, form logic expressions, build truth tables, and understand logic gates.
• Identify the main components of a basic computer architecture and follow the main steps in the fetch-decode-execute cycle.
• Recognise the main types of assembler instructions. Implement a simple assembler program, and execute it using the simulator used in FIT1001.

Unit relationships

FIT1008 is a core unit in the Bachelor of Computer Science and in the Bachelor of Software Engineering.

FIT1008 is a prerequisite for:

• FIT2004 Algorithms and Data Structures
• FIT2008 Net-centric Computing
• FIT2025 Software Engineering Practice

Texts and software

Required text(s)

There are no required texts for this subject. The lecture slides are designed to be self sufficient. However, we strongly encourage students to complement the slides by reading the recommended texts.

Textbook availability

Text books are available from the Monash University Book Shops. Availability from other suppliers cannot be assured. The Bookshop orders texts in specifically for this unit. You are advised to purchase your text book early.

Software requirements

Eclipse Platform. This is the recomended platform (although BlueJ is also allowed). It can be downloaded from http://www.eclipse.org/downloads/

BlueJ, Version 2.1.2 Programming Development Environment. It can be downloaded from
http://www.bluej.org

The MIPS R2000 simulator SPIM S20. This, and all the other above, are included as part of the Standard Operating Environment used in Faculty computer Labs.

Hardware requirements

Students may use the facilities available in the computing labs. Information about computer use for students is available from the ITS Student Resource Guide in the Monash University Handbook.

You will need to allocate up to 6 hours per week for use of a computer, including time for newsgroups/discussion groups.

Recommended reading

(1) Data Structures and Algorithms in Java. Second Edition. Lafore, Robert. 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.

(2) Absolute java. Second Edition. Walter Savitch. Adison Wesley. This book also contains some data structures and algorithms, but it used them to illustrate the use of Java. It is useful for students who have questions about the Java language.

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

Supplementary Reading

Objects First With Java: A Practical Introduction Using BlueJ (2nd Edition). David Barnes and Michael Kolling

Library access

Study resources

Study resources for FIT1008 are:

found at the FIT1008 web site on MUSO, including:

• lecture slides,
• code for the lectures in Java class format,
  
• weekly tutorial exercises,
• weekly assignment specifications,
• weekly tutorial solutions (available after the tutorial), and
• supplementary material.

Unit website

Structure and organisation

Timetable

Assessment

Assessment weighting

Assessment for the unit consists of:

• 1 mid-semester test weighted at 10%.
• 12 practicals weighted at 20% in total.
• a final examination weighted at 70%.

Assessment Policy

To pass this unit you must:

• attend at least 7 out of the 11 pracs;
• score 50% or better in pracs
• score 50% or better in the exam, and
• score at least 50% overall.

Your score for the unit will be calculated by:

0.7*(Total Exam Mark) + 0.2*(Total Prac Mark) + 0.1*(Total Test mark)

if hurdles are met. Otherwise the maximum score is 44N

Assessment Requirements

Assignment specifications will be made available On the FIT1008 MUSO site.

Assignment Submission

The solutions provided by each student for the weekly pracs will be reviewed and marked by a Lab demonstrator at the weekly prac during the third hour of the prac. This is done in front of the student and at the student's computer.

Extensions and late submissions

Late submission of assignments

If you miss a prac you will be marked "Absent" unless:

1. You obtain the approval of the head tutor and you attend another prac during the same week After the prac you must email your admin tutor with the following information:

• NAME:
• ID NUMBER:
• DATE OF REPLACEMENT PRAC:
• REGULAR PRAC: (time and room)
• REPLACEMENT PRAC: (time and room)

1. If you had an illness or emergency, you need to:

• Obtain Medical certificate or Police Accident Report,
• Fill out Absentee Form, and
• Submit the form and documentation to the General Office

Then your mark will be changed from ABSENT to SICK. At the end of the semester, SICK marks are changed to the average of your marks in the pracs you attended, provided you attended at least 75% of the pracs

This policy is strict because comments or guidance will be given on assignments as they are returned, and sample solutions may also be published and distributed, after assignment marking or with the returned assignment. 

Extensions

It is your responsibility to structure your study program around assignment deadlines, family, work and other commitments. Factors such as normal work pressures, vacations, etc. are seldom regarded as appropriate reasons for granting extensions. 

Not applicable.

Grading of assessment

Assignments, and the unit, will be marked and allocated a grade according to the following scale:

Assignment return

Since the pracs are marked weekly during the lab session, feedback will be provided immediately during the marking.

The mid semester test will be returned within two weeks of the test date.

Feedback

Feedback to you

You will receive feedback on your work and progress in this unit. This feedback may be provided through your participation in tutorials and class discussions, as well as through your assignment submissions. It may come in the form of individual advice, marks and comments, or it may be provided as comment or reflection targeted at the group. It may be provided through personal interactions, such as interviews and on-line forums, or through other mechanisms such as on-line self-tests and publication of grade distributions.

Feedback from you

You will be asked to provide feedback to the Faculty through a Unit Evaluation survey at the end of the semester. You may also be asked to complete surveys to help teaching staff improve the unit and unit delivery. Your input to such surveys is very important to the faculty and the teaching staff in maintaining relevant and high quality learning experiences for our students.

And if you are having problems

It is essential that you take action immediately if you realise that you have a problem with your study. The semester is short, so we can help you best if you let us know as soon as problems arise. Regardless of whether the problem is related directly to your progress in the unit, if it is likely to interfere with your progress you should discuss it with your lecturer or a Community Service counsellor as soon as possible.

Unit improvements

The code corresponding to lectures will now be provided in advance, and following expected programming practices for readability, testability, and reusability.

Two new lectures combining expected commenting, testing, and debugging practices have been developed and will be given in week s one and five. The aims are (a) to provide many more examples and (b) to do it early enough to be of better use for pracs.

The two lectures on hash tables have been moved earlier to be more in sequence with the data structures and algorithms part of the subject

Plagiarism and cheating

Plagiarism and cheating are regarded as very serious offences. In cases where cheating  has been confirmed, students have been severely penalised, from losing all marks for an assignment, to facing disciplinary action at the Faculty level. While we would wish that all our students adhere to sound ethical conduct and honesty, I will ask you to acquaint yourself with Student Rights and Responsibilities and the Faculty regulations that apply to students detected cheating as these will be applied in all detected cases.

In this University, cheating means seeking to obtain an unfair advantage in any examination or any other written or practical work to be submitted or completed by a student for assessment. It includes the use, or attempted use, of any means to gain an unfair advantage for any assessable work in the unit, where the means is contrary to the instructions for such work. 

When you submit an individual assessment item, such as a program, a report, an essay, assignment or other piece of work, under your name you are understood to be stating that this is your own work. If a submission is identical with, or similar to, someone else's work, an assumption of cheating may arise. If you are planning on working with another student, it is acceptable to undertake research together, and discuss problems, but it is not acceptable to jointly develop or share solutions unless this is specified by your lecturer. 

Intentionally providing students with your solutions to assignments is classified as "assisting to cheat" and students who do this may be subject to disciplinary action. You should take reasonable care that your solution is not accidentally or deliberately obtained by other students. For example, do not leave copies of your work in progress on the hard drives of shared computers, and do not show your work to other students. If you believe this may have happened, please be sure to contact your lecturer as soon as possible.

Cheating also includes taking into an examination any material contrary to the regulations, including any bilingual dictionary, whether or not with the intention of using it to obtain an advantage.

Plagiarism involves the false representation of another person's ideas, or findings, as your own by either copying material or paraphrasing without citing sources. It is both professional and ethical to reference clearly the ideas and information that you have used from another writer. If the source is not identified, then you have plagiarised work of the other author. Plagiarism is a form of dishonesty that is insulting to the reader and grossly unfair to your student colleagues.

Communication

Communication methods

The preferred communication method is either with the lecturer during consultation hours, or through the "Help Room" sessions.

Notices

Notices related to the unit during the semester will be placed on the Notices Newsgroup in the Unit MUSO Website. Check this regularly. Failure to read the Notices newsgroup is not regarded as grounds for special consideration.

IMPORTANT: please remember to forward MUSO's e-mail to your regular account

Consultation Times

• Thursdays 10am-11am
• Fridays 11am-12noon

If direct communication with your unit adviser/lecturer or tutor outside of consultation periods is needed you may contact the lecturer and/or tutors at:

Associate Professor Maria Garcia De La Banda
Associate Professor
Phone +61 3 990 55777
Fax +61 3 990 55157

Ms Robyn Mcnamara

This person's profile is not available.

Mr Fabian Bohnert

All email communication to you from your lecturer will occur through your Monash student email address. Please ensure that you read it regularly, or forward your email to your main address. Also check that your contact information registered with the University is up to date in My.Monash.