Course Details

Course Code COMP3121
Course Title Algorithms and Programming Techniques
Convenor Raveen de Silva
Admin Anahita Namvar
Classes Thursday 16:00 - 18:00 and Friday 11:00 - 13:00
Consultations Tuesday 14:00 - 15:00 and Friday 14:00 - 15:00
Units of Credit 6
Course Website Moodle
Handbook Entry http://www.handbook.unsw.edu.au/undergraduate/courses/current/COMP3121.html

Course Information

COMP3121 Algorithms and Programming Techniques (aka COMP9101 Design and Analysis of Algorithms, for postgraduate students) runs in all three terms each year. The extended version (COMP3821/9801) runs in T1 only each year. We recommend that top students take the extended course instead of this one.

  • Extended Algorithms moves at a faster pace and covers more topics and some topics in more depth. It assumes higher autonomy from students and offers a few different perspectives on problem solving. For instance, theory content is pre-recorded and the live lectures are used to solve problems interactively.
  • In terms of course structure, the extended course has 4 individual assignments (same as standard), but also a 4-part group assignment, and a peer marking component. The final exam is only 30%. This means a deadline almost every week.

To ensure that students are not penalised for taking the extended course, we apply scaling to the marks in both courses. We will not scale down any mark below 85 - these are usually scaled up, often considerably so. However, we give relatively few course marks in excess of 90 in the standard course, and it is not guaranteed that full marks in all assessments will translate to a 100 course mark.

Learning Outcomes

  • Be able to design new algorithms for solving new problems, using various design techniques (greedy, dynamic programming, divide and conquer, etc)
  • Be able to estimate efficiency of algorithms and justify their correctness
  • Be able to demonstrate improved problem solving skills

Objectives

The courses COMP3121/9101 are about problem solving. Before you can start programming, you must first solve the problem at hand. Thus, we will not just go over a cookbook of some well-known algorithms to be memorised and implemented. Instead, we will learn how to design “from scratch” new algorithms for solving new problems, using various design techniques (greedy, dynamic programming, divide and conquer, etc), and study the applications of these techniques, such as in graph algorithms and string matching algorithms. We will also learn how to argue the correctness and efficiency of algorithms.

Staff Contact details

Role Name Email Office
Lecturer Raveen de Silva r.desilva@unsw.edu.au K17 202
Course Admin Anahita Namvar cs3121@cse.unsw.edu.au K17 501-04

Student Conduct

The Student Code of Conduct ( Information , Policy ) sets out what the University expects from students as members of the UNSW community. As well as the learning, teaching and research environment, the University aims to provide an environment that enables students to achieve their full potential and to provide an experience consistent with the University's values and guiding principles. A condition of enrolment is that students inform themselves of the University's rules and policies affecting them, and conduct themselves accordingly.

In particular, students have the responsibility to observe standards of equity and respect in dealing with every member of the University community. This applies to all activities on UNSW premises and all external activities related to study and research. This includes behaviour in person as well as behaviour on social media, for example Facebook groups set up for the purpose of discussing UNSW courses or course work. Behaviour that is considered in breach of the Student Code Policy as discriminatory, sexually inappropriate, bullying, harassing, invading another's privacy or causing any person to fear for their personal safety is serious misconduct and can lead to severe penalties, including suspension or exclusion from UNSW.

If you have any concerns, you may raise them with your lecturer, or approach the School Ethics Officer , Grievance Officer , or one of the student representatives.

Plagiarism is defined as using the words or ideas of others and presenting them as your own. UNSW and CSE treat plagiarism as academic misconduct, which means that it carries penalties as severe as being excluded from further study at UNSW. There are several on-line sources to help you understand what plagiarism is and how it is dealt with at UNSW:

Make sure that you read and understand these. Ignorance is not accepted as an excuse for plagiarism. In particular, you are also responsible that your assignment files are not accessible by anyone but you by setting the correct permissions in your CSE directory and code repository, if using. Note also that plagiarism includes paying or asking another person to do a piece of work for you and then submitting it as your own work.

UNSW has an ongoing commitment to fostering a culture of learning informed by academic integrity. All UNSW staff and students have a responsibility to adhere to this principle of academic integrity. Plagiarism undermines academic integrity and is not tolerated at UNSW. Plagiarism at UNSW is defined as using the words or ideas of others and passing them off as your own.

If you haven't done so yet, please take the time to read the full text of

The pages below describe the policies and procedures in more detail:

You should also read the following page which describes your rights and responsibilities in the CSE context:

Course Assessment

You will have four written assignments each worth 15% of your grade. Assignments will be released in weeks 1, 3, 5 and 7 and due in weeks 3, 5, 7 and 9 respectively.

You will also have an online final exam worth 40%.

Here are the weights:

Item Weight
Assignments 60%
Final Exam 40%

Bonus points will be added for forum participation (no more than 5%). Please refer to the welcome announcement for more details.

Lectures

Time Lecturer Link
Thursday 16:00 - 18:00 Raveen https://www.youtube.com/playlist?list=PLVly8g0-6d_fT3YiFeK4TgQzaukR4BC6-
Friday 11:00 - 13:00 Raveen https://www.youtube.com/playlist?list=PLVly8g0-6d_fT3YiFeK4TgQzaukR4BC6-

Consultations

Time Consultant Link
Tuesday 14:00 - 15:00 Raveen https://unsw.zoom.us/j/84869304383
Friday 14:00 - 15:00 Raveen https://unsw.zoom.us/j/84869304383

Help Sessions

Time Tutor Link
Monday 11:00 - 12:00 TBA https://unsw.zoom.us/j/81463936975
Monday 17:00 - 18:00 TBA https://unsw.zoom.us/j/81463936975
Tuesday 11:00 - 12:00 TBA https://unsw.zoom.us/j/81463936975
Tuesday 17:00 - 18:00 TBA https://unsw.zoom.us/j/81463936975
Wednesday 11:00 - 12:00 TBA https://unsw.zoom.us/j/81463936975
Wednesday 17:00 - 18:00 TBA https://unsw.zoom.us/j/81463936975
Thursday 11:00 - 12:00 TBA https://unsw.zoom.us/j/81463936975
Friday 17:00 - 18:00 TBA https://unsw.zoom.us/j/81463936975

Recordings of the lectures and consultations will be published on the UNSW Algorithm Design YouTube channel, in the same playlist .

You can post questions at the Ed forum (join here ) regarding all the material covered in lectures or ask for clarifications on the tutorial problems. In addition to the help session, you will be provided written tutorial exercises with detailed solutions and you can ask for clarifications during office hours which will also be delivered via Zoom.

Course Syllabus

Some of the topics to be covered in COMP3121/9101 include:

Introduction:

Algorithm Analysis:

  • Proving correctness of algorithms
  • Stable Matching Problem

Divide-And-Conquer Method:

  • Asymptotic behavior, recurrences, summations, estimations
  • Weighing coins
  • The Master Theorem
  • Applications of the Master Theorem: median of medians

The Greedy Method:

  • When greed pays off - foundations of the Greedy Method
  • Activity Selection problem
  • Discrete (0–1) Knapsack Problem
  • File compression: Huffman Codes
  • Directed acyclic graphs and topological sorting
  • Dijkstra's algorithm
  • Minimum spanning trees

Dynamic Programming Method:

  • Longest Increasing Subsequence
  • Making change
  • Assembly line scheduling
  • Multiplying chains of matrices
  • Longest Common Subsequence
  • Edit distance
  • Bellman – Ford algorithm
  • Floyd – Warshall algorithm

Network Flow Algorithms:

  • Flow networks
  • Ford – Fulkerson algorithm and more
  • Applications including Maximum Bipartite Matching

String Matching Algorithms:

  • “Naïve” string matching algorithm
  • Rabin – Karp hashing algorithm
  • String matching using finite automata

Linear Programming:

  • Formulating linear programs
  • Linear programming and integer linear programming

Intractable Problems and Approximation Algorithms:

  • Feasibility of algorithms
  • Polynomial Time problems, NP problems, intractable problems
  • NP complete problems and NP hard problems
  • Feasible reductions
  • Approximate solutions using Greedy Method and DP

Practicing problem-solving while having fun:

  • Assorted puzzles

Final Exam

The final exam will be held online using INSPERA. It will be a three hour exam consisting of eight multiple choice questions and four algorithm design problems.

Course Evaluation and Development

This course is evaluated each session using the myExperience system.

In the previous offering of this course, students asked for more clarity in the standard and format expected of assignment submissions.

Based on their comments, we will be devoting more time to the development of tutorial exercises. In particular, we will write the solutions to tutorial exercises to the standard we expect in an assignment, and solutions will be released earlier than they were last term. This is intended to provide a model on which students can base their assignment submissions.

Resource created Wednesday 18 May 2022, 10:28:02 AM, last modified Tuesday 28 June 2022, 03:09:38 PM.


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