| Instructor(s) | Dr. Reza Samavi [Coordinator] Office: ENG457 Phone: (416) 979-5000 x 554903 Email: samavi@torontomu.ca Office Hours: TBA Dr. Reza Sedaghat Office: ENG431 Phone: (416) 979-5000 x 556083 Email: rsedagha@torontomu.ca Office Hours: TBA | ||||||||||||
| Calendar Description | The main topics covered in this course include basic data structures (arrays, pointers), abstract data structures (trees, lists, heaps), searching, sorting, hashing, recursive algorithms, parsing, space-time complexity, NP-complete problems, software engineering and project management, object-oriented data structures. Case studies and lab exercises will be implemented using a high level programming language. (Formerly ELE 428.) | ||||||||||||
| Prerequisites | COE 318 | ||||||||||||
| Antirequisites | None | ||||||||||||
| Corerequisites | MTH 314 | ||||||||||||
| Compulsory Text(s): |
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| Reference Text(s): |
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| Learning Objectives (Indicators) | At the end of this course, the successful student will be able to:
NOTE:Numbers in parentheses refer to the graduate attributes required by the Canadian Engineering Accreditation Board (CEAB). | ||||||||||||
| Course Organization | 3.0 hours of lecture per week for 13 weeks | ||||||||||||
| Teaching Assistants | TBA | ||||||||||||
| Course Evaluation |
Note: In order for a student to pass a course, a minimum overall course mark of 50% must be obtained. In addition, for courses that have both "Theory and Laboratory" components, the student must pass the Laboratory and Theory portions separately by achieving a minimum of 50% in the combined Laboratory components and 50% in the combined Theory components. Please refer to the "Course Evaluation" section above for details on the Theory and Laboratory components (if applicable). | ||||||||||||
| Examinations | Midterm exam in Week 7, two hours, problems, closed book (covers Weeks 1-6). Final exam, during exam period, 2-3 hours, closed-book (covers Weeks 1-13). | ||||||||||||
| Other Evaluation Information | In order to achieve a passing grade in this course, the student must achieve an average of at least 50% in both theoretical and laboratory components. | ||||||||||||
| Teaching Methods | 1. Lectures will be delivered during the scheduled class hours. 2. Notes/slides from the class lectures will be posted on D2L. 3. Laptops/computer systems are mandatory requirement for the course lectures and labs. | ||||||||||||
| Other Information | All the labs have to be performed individually by each student. Each lab has its own weight as specified in the lab manuals. In case any two students have the same code, it will automatically be considered as plagiarized, therefore it is strongly advisable to write your own code and do the submission. Any late submission of the lab deliverable will be deducted 10% per day up to 8 days, whereby the lab will not be accepted. Generative AI Course Policy Expectations around appropriate and inappropriate use of Generative Artificial Intelligence (sample syllabus statements). https://docs.google.com/document/d/1xk7hP2Ihh7WL3AViKxJJpLAM_Jy9IvZoaoNnxBbngjU/edit?usp=sharing Include the Academic Integrity Office's student facing resource: FAQs: Academic Integrity and AI Use at TMU. https://docs.google.com/document/d/1HVre0-YflnPA5WPAYR6Ecjv_OwqDP0TMcOePCQQYIaU/preview?tab=t.0#heading=h.qcfhdt6b496b | ||||||||||||
Week | Hours | Chapters / | Topic, description |
|---|---|---|---|
1 | 3 | Ch. 1 | Introduction: Course overview. Introduction to algorithms. |
2 | 3 | Ch. 2 | Analyzing and designing algorithms |
3 | 3 | Ch. 3 Appendix A (A.1) | Complexity analysis |
4 | 3 | Ch.4: 4.3, 4.4, 4.5 | Recurrence equations |
5 | 3 | Ch. 6, Ch. 10: 10.1, 10.2, 10.3 Appendix B: B.5 | Elementary Data Structures |
6 | 3 | Ch. 11: 11.1, 11.2, 11.3 (11.3.1, 11.3.2) 11.4 | Hash Tables |
7-9 | 9 | Ch. 12: 12.1, 12.2, 12.3 Ch. 13 | Trees |
10 | 3 | Ch. 20: 20.1, 20.2, 20.3 Appendix B (B.4) | Graphs |
11-12 | 6 | Ch. 21, Ch. 21 and 22 and 23.1 | Elementary Graph Algorithms |
13 | 3 | Ch. 24 and 34 (pp 1042-1048) | Flow Networks, Introduction to NP-Completeness, Course Review |
Week | L/T/A | Description |
|---|---|---|
2 | Lab 1 | Introduction |
3 | Lab 2 | Recursion |
4 | Lab1-2 review | Lab 1 and 2 review |
5-6 | Lab 3 | Sorting |
7-8 | Lab 4 | State machines |
9-10 | Lab 5 | Use of Stacks and XML-based HEAP |
11 | Lab5 review | Lab 5 review |
Students are reminded that they are required to adhere to all relevant university policies found in their online course shell in D2L and/or on the Senate website
Refer to the Departmental FAQ page for furhter information on common questions.
The University Libraries provide research workshops and individual consultation appointments. There is a drop-in Research Help desk on the second floor of the library, and students can use the Library's virtual research help service to speak with a librarian, or book an appointment to meet in person or online.
You can submit an Academic Consideration Request when an extenuating circumstance has occurred that has significantly impacted your ability to fulfill an academic requirement. You may always visit the Senate website and select the blue radio button on the top right hand side entitled: Academic Consideration Request (ACR) to submit this request.
For Extenuating Circumstances, Policy 167: Academic Consideration allows for a once per semester ACR request without supporting documentation if the absence is less than 3 days in duration and is not for a final exam/final assessment. Absences more than 3 days in duration and those that involve a final exam/final assessment, always require documentation. Students must notify their faculty/contract lecturer once a request for academic consideration is submitted. See Senate Policy 167: Academic Consideration.
Longer absences are not addressed through Policy 167 and should be discussed with your Chair/Director/Program to be advised on next steps.
Students are to strictly adhere and follow:
During the lab sessions, to avoid tripping hazards, the area around the lab stations should not be surrounded by bags, backpacks etc, students should place their bags, backpacks etc against the walls of the labs and/or away from their lab stations in such a way that it avoids tripping hazards.
Academic Accommodation Support (AAS) is the university's disability services office. AAS works directly with incoming and returning students looking for help with their academic accommodations. AAS works with any student who requires academic accommodation regardless of program or course load.
Academic Accommodations (for students with disabilities) and Academic Consideration (for students faced with extenuating circumstances that can include short-term health issues) are governed by two different university policies. Learn more about Academic Accommodations versus Academic Consideration and how to access each.
At Toronto Metropolitan University, we recognize that things can come up throughout the term that may interfere with a student’s ability to succeed in their coursework. These circumstances are outside of one’s control and can have a serious impact on physical and mental well-being. Seeking help can be a challenge, especially in those times of crisis.
If you are experiencing a mental health crisis, please call 911 and go to the nearest hospital emergency room. You can also access these outside resources at anytime:
If non-crisis support is needed, you can access these campus resources:
We encourage all Toronto Metropolitan University community members to access available resources to ensure support is reachable. You can find more resources available through the Toronto Metropolitan University Mental Health and Wellbeing website.