Csci 231 (now 2200): Introduction to Algorithms

Fall 2013: T, Th 10:00-11:25 in Searles 223

This course is an introduction to the design and analysis of algorithms.

• It introduces the RAM model, asymptotic notation, worst-case analysis, and analysing the running time of recursive algorithms with recurrence relations.
• It introduces fundamental topics such as searching, sorting and selection, graphs, string matching, network flow, optimization and NP-completeness.
• It discusses solutions to these problems, while illustrating design techniques such as divide-and-conquer, dynamic programming and greedy.
• It discusses correctness and analyses the efficiency of these solutions.

The class is purely theoretical and involves no programming.

Prerequisites: In this incarnation, the class does not require any pre-requisites, and is intended as another entry point (the theory way) into Computer Science besides 101 (the programming way). Generally speaking, a good mathematical background and good QR skills are a plus.

Instructor: Laura Toma
Office: 219 Searles Hall
Email: ltoma at bowdoin
My office hours are Tue, Thu 2:30 to 4pm in my office. For quick questions you can drop by any time the door is open. If you cannot come during office hours and if you have longer questions, send me an email to make an appointment.

TAs and QR-TAs:

• Noam Terman (Sun 7-9pm) (QR-TA)
• Andrew Daniels (Mon 6-8pm) (QR-TA)
• Isaac May (Mon 8-10pm)
• [when necessary: Gabby Grandin (Tue 8-10pm, shared with 101/intro)]

Study groups/Office hours:

• Sun: 7-9pm (Noam in Searles 224)
• Mon: 6-10pm (Andrew 6-8, Ike 8-10 in Searles 224)
• Tue: 2:30-4 (Laura in Searles 219)
• Thu: 2:30-4pm (Laura in Searles 219)

Class webpage: http://www.bowdoin.edu/~ltoma/teaching/cs231/fall13/. Note that this is a link from my personal website at Bowdoin. This site will contain all class-related material along the semester. The class does not have a Blackboard site.

Textbook (required):

• Michael Goodrich and Roberto Tamassia, Algorithm Design: Foundations, Analysis and Internet Examples, John Wiley, 2002.

Grading policy

• Homework assignments (40%).
• 3 exams (3x 20% = 60%).
• Class participation (tie breaker)

Topics:

• Mathematical foundation (growth of functions, summations, recurrences, induction)
• Sorting algorithms (insertion sort, selection sort, mergesort, quicksort, heapsort, sorting lower bounds, bucket sort, radix sort)
• Priority queues (binary heap)
• Selection
• Paradigms (divide-and-conquer, greedy, dynamic programming)
• Graph Algorithms (traversal, minimum spanning tree, shortest paths)
• Network algorithms (network flow)
• String matching algorithms
• NP-completeness

Class meetings: The class meets twice per week. If for some reason you miss a class, you are responsible for studying the material covered in class using the book and the materials posted online.

Exams: There will be three exams, the first two during the semester, and the last one during the final exam period. The first two will be in-class exams. The last exam will be a take home. The exams will be non-cumulative. All exams will be open book and open notes.

Homework: Homework assignments will be announced in class and by email, and will be available online as the semester progresses. They are due at the beginning of class on the due date. Late assignments are not accepted.

Homework collaboration policy: Collaboration is allowed and encouraged, provided that it helps you study better. Do not overdo it, and remember that exams are individual! Even if you collaborate with others, you must write up the solutions individually, and list the names of the collaborators. Limit your collaborators to three or less.

Academic Integrity: You are expected to follow Bowdoin's academic honor code. Collaboration on homeworks is encouraged, however you are responsible to write the solutions on your own, and list the names of all your collaborators. Any violation will be severely punished.