6.001 Structure and Interpretation of Computer Programs. Copyright o 2004 by Massachusetts Institute of Technology 6.001 Notes: Section 4.1 Slide 4.1.1 Today ' s topics In this lecture, we are going to take a careful look at the kinds

6.001 Structure and Interpretation of Computer Programs. Copyright o 2004 by Massachusetts Institute of Technology 6.001 Notes: Section 3.1 Slide 3.1.1 This Lecture In this lecture, we are going to put together the basic pieces of Scheme that we introduced in the previous lecture, in order to

Beating the Averages Paul Graham (This article is based on a talk given at the Franz Developer in Cambridge, MA, on March 25, 2001 In the summer of 1995, my friend rt morris and i started a startup called Viaweb. Our pla to write software that would let end users build online stores. What was novel about this

Slide l.l.1 This first thing we need to do is discuss the focus of 6.001 What is this course all about? This seems quite obvious-- this What is the focus of 6.001 is a course about computer science. But we are going to claim This course is about Computer Science in a rather strange way that this is not really true

In the last lecture, we began looking at the programming This lecture nguage Scheme. with the intent of learning how that anguage would provide a basis for describing procedures and Adding procedures and procedural abstractions

Recall from lecture 22 °Flow value:f=f(s,V) Cut: Any partition (S, T)of y such that s E S andt∈T Lemma. f=f(s, T) for any cut(S, T) Corollary. f(s, T) for any cut(S, T) Residual graph: The graph G=(v, ef) with strictly positive residual capacities c u, v) c(u,)-f(2y)>0

flow networks Definition. A flow network is a directed graph G=(, E)with two distinguished vertices:a source s and a sink t. Each edge(u, v)E E has a nonnegative capacity c(u, v). If(u, v) E, then c(u, v)=0 Example: c 2001 by Charles E Leiserson

麻省理工学院：《算法导论》（英文版） Lecture 21 Prof charles e. leiserson

Disioint-set data structure (Union-Find) Problem: maintain a dynamic collection of pairwise-disjoint sets S=(S Each set S; has one element distinguished as the representative element, rep[sil lust support 3 operations

Shortest paths Single-source shortest paths nonnegative edge weights Dijkstra's algorithm: O(E+ vlg n General