COMP1100 Introduction to Programming and Algorithms
First Year Course
| Offered By | Department of Computer Science |
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| Academic Career | Undergraduate |
| Course Subject | Computer Science |
| Offered in | First Semester, 2009 and First Semester, 2010 |
| Unit Value | 6 units |
| Course Description |
In general terms, an algorithm is a precise computational process for producing a specific result from some given input data. A program is a formal definition of an algorithm, in a notation that can be mechanically translated and then executed by a modern computer. The core unifying theme of the course is data-directed design. The course introduces fundamental algorithmic structures such as composition (sequence), choice and repetition, predominantly using a functional programming language as the vehicle of expression. The course introduces fundamental data types and structures such as products (tuples), lists, and unions. A key aim is to illustrate the interdependancy of algorithms and data structures - significantly, that data structures largely determine algorithms, for example, that products are processed by projections, unions by alternatives, and that recursive data structures such as lists are processed by recursive algorithms. For all but the simplest programs, some means of abstraction and structuring is required to manage the complexities faced by programmers, as individuals and as groups. The course introduces modularisation techniques such as libraries and abstract data types, as a means of managing such complexity. Good modular design is of fundamental and practical importance for program development - adhering to the theme of data-directed design adopted in this course leads to elegant and maintainable programs. The final section of the course revisits the most important aspects covered in the course, but now in the context of an object-oriented programming language. The aim is to thereby emphasise the concepts, rather than any particular implementation, and to provide a springboard to subsequent programming courses.
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| Learning Outcomes |
Students who succeed in all aspects of this course will be able to:
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| Indicative Assessment |
Continuous Assessment (40%); Examinations (60%) |
| Workload | Thirty one-hour lectures, ten two-hour tutorial/laboratory sessions. |
| Areas of Interest | Information Technology and Software Engineering |
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Assumed Knowledge and Required Skills |
Students are assumed to have achieved a level of knowledge of mathematics comparable to at least ACT Maths Methods major or NSW 2 unit maths or equivalent. |
| Science Group | A |
The information published on the Study at ANU 2009 website applies to the 2009 academic year only. All information provided on this website replaces the information contained in the Study at ANU 2008 website.




