COMPSCI 531 Algorithm Paradigms

Lectures  Teaching Assistant - Resources


This course is an introductory graduate course on the design and analysis of algorithms. The course builds on an undergraduate-level study of the analysis and implementation of data structures and algorithms (COMPSCI 201). The goal is to introduce a number of important algorithm design techniques as well as basic algorithms that are interesting both from a theoretical and also practical point of view. We will cover basic algorithm design techniques such as divide-and-conquer, dynamic programming, and greedy techniques for optimization. We will cover techniques for proof of the correctness of algorithms and also asymptotic analysis of algorithm time bounds by the solution of recurrence equations. We will apply these design and analysis techniques to derived algorithms for a variety of tasks such as sorting, searching, and graph problems. Some specific algorithm topics include: deterministic and randomized sorting and searching algorithms, depth and breadth first search graph algorithms for finding paths and matchings, and algebraic algorithms for fast multiplication and linear system solving.


An undergraduate-level course on the analysis and implementation of data structures and algorithms (COMPSCI 201 or equivalent) and also four semesters of college mathematics. This course requires a certain amount of mathematical sophistication (e.g., as required to solve recurrence equations). A quiz on recurrence equations early in the course will provide you with some feedback on whether your mathematics training will suffice. If you feel that you may not have sufficient background, please talk with the instructor John Reif.




Times: Tues & Thurs 1:25 PM – 2:40 PM Room: North 311


Professor John Reif



D223 LSRC Building






reif at

Web page:

Office hours:


Tues, Thurs: 2:40 - 3:40 PM


TA: Brandon Fain





Email: btfain at



Web page

Office hours: Tuesday & Wednesday 12:00-1:00 PM



Course material:

       Table of Contents

       Solutions to Selected exercises and problems in CLRS

       Bug Reports in CLRS

Optional auxiliary reading (other good reference books):

Course synopsis:


Summary of topics covered and lecture notes:

Consult the schedule of Lectures for a list of topics and a copy of lecture notes for the lectures to date. Other handouts can be found in the handouts directory. See resources page for additional information.

Homework assignments:

Homeworks are due roughly every second week and must be turned in before class on Wednesday of the week they're due. No credit is given for late solutions. For exceptional circumstances, see John Reif in advance, rather than after the due time.

Details about proper style [ps] for writing up homework solutions and some guidelines for grading are available.

It is recommended but not required that LaTeX be used for typesetting homework problems.

Honor code: For homework problems, discussion among students is permitted, but students must write up solutions independently on their own. No materials or sources from prior years' classes or from the Internet can be consulted. During every exam: all calculators, computers, cell phones, wireless or bluetooth-connected devices, and all other electronic devices must be identified and handed over to the person proctoring the exam. Breaking the rules can result in expulsion. Each student is required to make a copy of this paragraph, sign it indicating that the contents are understood, and turn it in to John Reif.


There will be no make-up exams for missed exams. Missing one of the three midterm exams due to an illness requires filing the web-based Short-Term Illness Notification Form at, and will result in the remaining midterm exams grades being re-weighted appropriately. By University Policy, missing the Final exam results in a grade X.

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