FIT1015 is a core unit in the Computer Science sequence in the Bachelor of Science (BSc). It was introduced as part of the faculty restructure for 2006. Previously this degree sequence had a core unit CSE1303. FIT1015 is based on the late CSE1303 but has been substantially revised due to changes in the pre-requisite units and other core units in the degrees. In particular, it replaces some Computer Systems material with a new Software Engineering topic and OO material previously in CSE2305.

This unit has been updated as part of a 2009 review and comparison of data with current Handbook, Syllabus + and Callista data.

This is a core unit in the Computer Science sequence in the BSc degree at the Clayton campus. It builds on the introduction to computer programming begun in the faculty core unit FIT1002 Computer Programming.

Its most important role is to introduce some major themes from the discipline of computer science, namely, Algorithms and Data Structures, Computer Systems and Abstract Machines. This selection of topics allows students to understand how problem solving in computer science involves different levels of abstraction, from high-level algorithms and programming down to the machine level. It gives the students practice in various aspects of problem solving, including developing, applying and implementing simple algorithms and data structures. Finally, it uses the Java programming language not only to implement the aforementioned algorithms but also to illustrate more advanced object-oriented (OO) concepts and techniques.

While some of the OO programming aspects may be similar to FIT1007 Computer Programming 2, its treatment of algorithms and data structures is deeper, and its abstract machine topics are not covered in FIT1007. BSc students undertaking a Computer Science sequence need a more advanced level of programming than that provided in the faculty core.

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;
• gain a deeper understanding of basic object-oriented (OO) concepts, and learn 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 what a programming language paradigm is, and learn to distinguish among some of the major paradigms, including imperative, object oriented, functional and logic;
• 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;
• understand the requirements for "good programming practice";
• understand how numbers are represented on a computer;
• 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 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.

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:

• 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 Abstract Machine simulator for executing some of the simple iterative programs learned in this unit;
• determine the time and space requirements of simple algorithms and data structures.

Demonstrated the communication necessary to:

• document a program correctly;
• produce appropriate documentation for designing and testing a program;
• explain how parts of a program work.

020109

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.

On-campus

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

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

FIT

Science Faculty: This unit is taken by BSc students.

FIT1002 or equivalent