FIT1015 Computer science - Semester 2 , 2007

Unit leader :

Maria Garcia de la Banda

Lecturer(s) :

Clayton

  • Maria Garcia de la Banda

Introduction

Welcome to FIT1015 Computer Science. This is a 6 credit point elective unit. The unit is designed to develop the student’s understanding on how to develop and use the basic data structures and algorithms, and also to explore how simple programs that use these basic components are actually executed by the computer.

Unit synopsis

FIT1015 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; computer systems; and abstract machines.

Learning outcomes

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 the trade-offs regarding simplicity, efficiency and memory usage when designing the architecture of a computer.
  • 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.
students will have the practical skills to be able to:
  • 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.
students will also be able to:
  • Document a program correctly.
  • Produce appropriate documentation for designing and testing a program.
  • Explain how parts of a program work.

Workload

For on campus students, workload commitments are:

  • three one-hour lectures,
  • one one-hour tutorial
  • one 1 and 1/2 hour computer lab prac (requiring advance preparation) followed by an extra 1 and 1/2 hour for prac marking
  • a minimum of 7 hours of personal study per week in order to satisfy the reading and assignment expectations.
  • You will need to allocate up to 5 hours per week, for use of a computer, including time for newsgroups/discussion groups.

Unit relationships

Prerequisites

Before attempting this unit you must have satisfactorily completed FIT1002 Computer Programming or equivalent.

Students beginning FIT1015 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.

Relationships

FIT1015 is a core unit in the Bachelor of Science.

You may not study this unit and CSE1303, CSC1030, FIT1007, FIT1008 in your degree.

Continuous improvement

Monash is committed to ‘Excellence in education' and strives for the highest possible quality in teaching and learning. To monitor how successful we are in providing quality teaching and learning Monash regularly seeks feedback from students, employers and staff. Two of the formal ways that you are invited to provide feedback are through Unit Evaluations and through Monquest Teaching Evaluations.

One of the key formal ways students have to provide feedback is through Unit Evaluation Surveys. It is Monash policy for every unit offered to be evaluated each year. Students are strongly encouraged to complete the surveys as they are an important avenue for students to "have their say". The feedback is anonymous and provides the Faculty with evidence of aspects that students are satisfied and areas for improvement.

Student Evaluations

The Faculty of IT administers the Unit Evaluation surveys online through the my.monash portal, although for some smaller classes there may be alternative evaluations conducted in class.

If you wish to view how previous students rated this unit, please go to http://www.monash.edu.au/unit-evaluation-reports/

Over the past few years the Faculty of Information Technology has made a number of improvements to its courses as a result of unit evaluation feedback. Some of these include systematic analysis and planning of unit improvements, and consistent assignment return guidelines.

Monquest Teaching Evaluation surveys may be used by some of your academic staff this semester. They are administered by the Centre for Higher Education Quality (CHEQ) and may be completed in class with a facilitator or on-line through the my.monash portal. The data provided to lecturers is completely anonymous. Monquest surveys provide academic staff with evidence of the effectiveness of their teaching and identify areas for improvement. Individual Monquest reports are confidential, however, you can see the summary results of Monquest evaluations for 2006 at http://www.adm.monash.edu.au/cheq/evaluations/monquest/profiles/index.html

Improvements to this unit

Two main changes have been made to the unit. The first one relates to the pracs and, in particular, to the work and interaction expected from students while working in pairs. These expectations have now been written down and are available through MUSO to make sure both students and demonstrators are aware of what is expected from a pair working in a prac.

Therefore, this semester we are very interested in receiving feedback regarding the pros and cons of working in pairs for the computer laboratory pracs, both in terms of how it affects student learning, and how it affects communication with lab demonstrators.

The second change relates to pace. The two extra lectures scheduled for this semester (corresponding to the public holidays in first semester) will not be used to give new material. Instead, they will be used to make sure students have a good understanding of the material already given.In particular, I will use them to reinforce understanding of complexity analysis, and experience in the process of algorithm design.

Unit staff - contact details

Unit leader

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

Lecturer(s) :

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

Contact hours : Wednesdays 12noon-2pm

Additional communication information

The preferred communication method for questions regarding the unit's material and/or organisation is throuhg the on-line discussion forum (that way, everyone can benefit from it). For more in-depth help, students can either talk to the lecturer during consultation hours, or through the "Help Room" sessions.

Notices related to the unit during the semester will be placed on the Notices Newsgroup in the Unit MUSO Website. Please, 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

Teaching and learning method

The main teaching mechanisms are through the material covered in lectures, and the questions and discussion promoted during tutorials. Learning is also expected to occur thanks to discussions with the prac partner, interaction with the demonstrator and, importantly, the on-line discussion forum for the unit.

Tutorial allocation

For tutorial allocation please register using Allocate+

Communication, participation and feedback

Monash aims to provide a learning environment in which students receive a range of ongoing feedback throughout their studies. You will receive feedback on your work and progress in this unit. This may take the form of group feedback, individual feedback, peer feedback, self-comparison, verbal and written feedback, discussions (on line and in class) as well as more formal feedback related to assignment marks and grades. You are encouraged to draw on a variety of feedback to enhance your learning.

It is essential that you take action immediately if you realise that you have a problem that is affecting your study. Semesters are 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 Schedule

Week Topic Key dates
1 Revision FIT1002  
2 Sorting & Array Data Structures  
3 Linked Data Structures  
4 Object Oriented Basics  
5 Advanced OO & Programming Languages  
6 Testing+Debugging 24th August Mid Semester Test
7 Recursive Sorts & Trees  
8 Trees + Hash Tables  
9 Computer Architecture  
10 MIPS  
Mid semester break
11 Translating to assembler  
12 Function Call/Return  
13 Revision  

Unit Resources

Prescribed text(s) and readings

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.

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.

Recommended text(s) and readings

(1) Data Structures and Algorithms in Java. Second Edition.Lafore, Robert. SAMS. This book provides a very simple approach tounderstanding data structures and algorithms. While the book uses Javato illustrate the implementation, its focus is on the actual datastructures and algorithms, rather than on Java, which is very usefulfor first year students.

(2) Absolute java. SecondEdition. Walter Savitch. Adison Wesley. This book also contains somedata structures and algorithms, but it used them to illustrate the useof Java. It is useful for students who have questions about the Javalanguage.

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

Required software and/or hardware

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

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

Equipment and consumables required or provided

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 5 hours per week for use of a computer, including time for newsgroups/discussion groups.

Study resources

Study resources we will provide for your study are:

found at the FIT1015 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.

Library access

The Monash University Library site contains details about borrowing rights and catalogue searching. To learn more about the library and the various resources available, please go to http://www.lib.monash.edu.au.  Be sure to obtain a copy of the Library Guide, and if necessary, the instructions for remote access from the library website.

Monash University Studies Online (MUSO)

All unit and lecture materials are available through the MUSO (Monash University Studies Online) site. You can access this site by going to:

  1. a) https://muso.monash.edu.au or
  2. b) via the portal (http://my.monash.edu.au).

Click on the Study and enrolment tab, then the MUSO hyperlink.

In order for your MUSO unit(s) to function correctly, your computer needs to be correctly configured.

For example :

  • MUSO supported browser
  • Supported Java runtime environment

For more information, please visit

http://www.monash.edu.au/muso/support/students/downloadables-student.html

You can contact the MUSO Support by: Phone: (+61 3) 9903 1268

For further contact information including operational hours, please visit

http://www.monash.edu.au/muso/support/students/contact.html

Further information can be obtained from the MUSO support site:

http://www.monash.edu.au/muso/support/index.html

Assessment

Unit 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.

If these four hurdles are met, your score for the unit will be calculated by:

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

Otherwise, the maximum score is 44N

Assignment tasks

  • Assignment Task
    Title :
    Mid Semester Test (1hour)
    Description :
    This test will evaluate your understanding of the material provided during the first five 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.
    Weighting :
    10%
    Criteria for assessment :
    Due date :
  • Assignment Task
    Title :
    Pracs (1 and 1/2 hours each at the computer lab, up to 5 hours prior to that for preparation)
    Description :

    Each week you will need to complete a prac assignment together with another student. Prac assignments are long and are designed to take a significant part of your 7 ``home tudy hours'' (usually, up to 5 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 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 the 1and 1/2 hours scheduled,  you will soon realise that you do not have enough time to complete it.

    Weighting :
    20%
    Criteria for assessment :
    The specific criteria is specified weekly in the prac notes.
    Due date :
    Remarks ( optional - leave blank for none ) :
    There are two hurdles associated to the pracs. First, you must attendat least 7 out of the 11 pracs. Second, you must score at least 50% of the prac mark. A student who does not meet all these hurdles can get a maximum of 44 N for the unit.

Examinations

  • Examination
    Weighting :
    70%
    Length :
    3 hours
    Type ( open/closed book ) :
    closed book
    Remarks ( optional - leave blank for none ) :
    There is a hurdle associated with the exam mark: you must score at least 50% of the exam mark. Furthermore, you must score at least 50% overall (i.e., for the mid semester test, pracs and exam).

Assignment submission

The solution provided by each pair of student for the weekly pracs will be reviewed and marked by a Lab demonstrator at the weekly prac during the last 1 and 1/2 hour of the prac. This is done in front of the student and at the student's computer. Demonstrators are obliged to tell students the mark obtained for each question, and the reasons for such a mark.

Assignment coversheets

University and Faculty policy on assessment

Due dates and extensions

The due dates for the submission of assignments are given in the previous section. Please make every effort to submit work by the due dates. 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. Students are advised to NOT assume that granting of an extension is a matter of course.

Late assignment

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

Return dates

Students can expect assignments to be returned within two weeks of the submission date or after receipt, whichever is later.

Assessment for the unit as a whole is in accordance with the provisions of the Monash University Education Policy at: http://www.adm.monash.edu.au/unisec/academicpolicies/policy/assessment.html

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.

Plagiarism, cheating and collusion

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 (http://www.infotech.monash.edu.au/about/committees-groups/facboard/policies/studrights.html) 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.

Register of counselling about plagiarism

The university requires faculties to keep a simple and confidential register to record counselling to students about plagiarism (e.g. warnings). The register is accessible to Associate Deans Teaching (or nominees) and, where requested, students concerned have access to their own details in the register. The register is to serve as a record of counselling about the nature of plagiarism, not as a record of allegations; and no provision of appeals in relation to the register is necessary or applicable.

Non-discriminatory language

The Faculty of Information Technology is committed to the use of non-discriminatory language in all forms of communication. Discriminatory language is that which refers in abusive terms to gender, race, age, sexual orientation, citizenship or nationality, ethnic or language background, physical or mental ability, or political or religious views, or which stereotypes groups in an adverse manner. This is not meant to preclude or inhibit legitimate academic debate on any issue; however, the language used in such debate should be non-discriminatory and sensitive to these matters. It is important to avoid the use of discriminatory language in your communications and written work. The most common form of discriminatory language in academic work tends to be in the area of gender inclusiveness. You are, therefore, requested to check for this and to ensure your work and communications are non-discriminatory in all respects.

Students with disabilities

Students with disabilities that may disadvantage them in assessment should seek advice from one of the following before completing assessment tasks and examinations:

Deferred assessment and special consideration

Deferred assessment (not to be confused with an extension for submission of an assignment) may be granted in cases of extenuating personal circumstances such as serious personal illness or bereavement. Special consideration in the awarding of grades is also possible in some circumstances. Information and forms for Special Consideration and deferred assessment applications are available at http://www.monash.edu.au/exams/special-consideration.html. Contact the Faculty's Student Services staff at your campus for further information and advice.