Words in parentheses (like this) are hints that will advise the student on the relative importance of a given topic, and are not part of the section titles in the respective books.
Date  Activity  Topic  GT Readings  CLRS Readings 
Tue Jan 18  Lecture 0:  Required Background material   27.1  27.2  27.3  27.5 

Wed Jan 19  Lecture 1:  Intro to design and analysis of algorithms   27.4  1.1  1.2  1.3  1.4 
Review CLRS A.1. Read CLRS 1.12 \& 2.1. 
Mon Jan 24  Lecture 2A:  Asymptotic complexity; recurrences; design techniques: incremental, divide \& conquer, twofinger.   4.0  4.1  4.2  15.0  15.1 
Review CLRS A.2, Read CLRS 2.22.3, 3.1, 4.0, and skim 3.2. 
Wed Jan 26  Lecture 2B:  Solving recurrences: recursion tree, proof by induction   15.2 
CLRS 4.4, 4.3, 4.5 (we recommend reading in that order). 
Mon Jan 31  Lecture 3A:  Master Method and More Sorting Strategies   3.0  3.1  3.2  3.3  3.4  3.5  4.3 
Review CLRS 4.5. Read the Introduction to Part II, pp 147150. Begin reading 6.1, 6.4, 7.1, 7.2, 8.1. 
Wed Feb 02  Lecture 3B:  Asymptotic Complexity of the Sorting Problem and Sorting Algorithms  (empty)  CLRS 6.16.4, 7.17.2, 8.1 Begin reading C.1, C.2, 5.1. 
Mon Feb 07  Lecture 4A:  Decision Tree Model, Sorting Problem Lower Bound, Counting Sort, Radix Sort   4.4  5.0  5.1  5.2 
CLRS 8.18.3 
Wed Feb 09  Lecture 4B:  Indicator Random Variables, Randomized Quicksort, Selection   5.3 
CLRS 5.25.3, 9.19.3 
Mon Feb 14  Lecture 4C:  Catchup and Review Block 1  (empty)  Introduce Block 2 
Wed Feb 23  Lecture 5A:  Dynamic Programming: Branch \& Bound, Greedy Algorithms   6.0  6.1  18.5  7.0  7.1  7.2  7.3  7.6 
CLRS 15.115.4 
Thu Feb 24  Lecture 5B:  Optimal binary search trees AND Dynamic Programming Recitation  (empty)  CLRS 15.5 
Mon Feb 28  Lecture 6A:  Algorithmic Paradigms Review. Backtrack Programming. KMP String Matching.  (empty)  CLRS 32.1, 32.4. 
Wed Mar 02  Lecture 6B:  Review of Types of Analysis. Amortized Analysis.   1.5 
CLRS 17.117.4 
Mon Mar 07  Lecture 7A:  Dynamic abstract data types amd candidate data structures.   2.0  2.1  2.2  2.3  2.4  8.0  8.1  8.2  8.3  8.4  8.5 
CLRS Intro to Part III, Chapter 10.110.3, and Chapter 12.112.3. 
Wed Mar 09  Lecture 7B:  RedBlack Trees and other balanced trees   9.0  9.1  9.2  9.3  20.3  9.4 
CLRS 13.113.4 
Mon Mar 14  Lecture 8A:  Augmenting data structures  (empty)  CLRS 14.114.3 
Wed Mar 16  Lecture 8B:  Hashing   10.0  10.1  10.2  10.3  10.4  10.6 
CLRS 11.111.4 
Mon Mar 28  Lecture 9A:  Graphs, Breadth First Search, Depth First Search   11.0  11.1  11.2  11.3  11.4 
CLRS 22.122.3 
Wed Mar 30  Lecture 9B:  Cut vertices, Biconnected components   11.6 
CLRS Problem 22.2, pp. 621ff. 
Mon Apr 11  Lecture 10A  Topological sort, Strongly Connected Components   11.5 
CLRS 22.4, 22.5 
Wed Apr 13  Lecture 10B:  Minimum spanning trees (and needed data structure)   12.0  12.1  12.2  14.0  14.1  14.3  12.3  3.6  12.4 
CLRS 23. CLRS 21.1, 21.2. 
Wed Apr 20  Lecture 11A:  Single Source Shortest Paths: Two Algorithms   13.0  13.1  13.2  13.3  13.4  13.5 
CLRS 24.124.3 
Fri Apr 22  Lecture 11B:  Tufts Virtual Monday: All Pairs Shortest Path   13.6 
CLRS Intro to 25, 25.2. 
Mon Apr 25  Lecture 12A:  Fibonacci heaps  (empty)  CLRS 19.119.4 (note: ch. 20 in 2nd ed.) 
Wed Apr 27  Lecture 12B:  Lower bounds, upper bounds, reduction, NPcompleteness   17.0  17.1  17.2  17.3  17.4  17.5  17.6  17.7 
CLRS 34.134.5 
Mon May 02  Final Lecture:   17.7  18.0  18.1  18.2  18.4 