CSE 130, Spring 2014 Name/ID ANSWER KEY Instructor: Ranjit Jhala Final Exam Instructions: read these first! Do not open the exam, turn it over, or look inside until you are told to begin. Switch off cell phones and other potentially noisy devices. Write your full name on the line at the top of this page. […]
Higher Order Functions CS 345 Lecture 6 In writing (for example) negate-all functionally, what do we do differently from an imperative style? We avoid the mutation of state… Do we iterate with a for loop? No, we use recursion Do we use an array? No, we use a list (recursive data structure) Do we mutate
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PowerPoint Presentation Haskell! Intro to Haskell Named after logician Haskell Curry (1900-1982) A more modern functional language: created late 1980’s Many similarities with Racket: Programming with expressions, not statements – No mutation! Everything is immutable. Functions are values – Can be passed as parameters to and returned from functions Lists are the fundamental data structure
1. Name three different ways that the following code is “imperative.” 1) It mutates state, for example: myarray[firstPos] = myarray[otherPos] 2) To hold data it uses an array “myarray,” which is not a recursive data structure. 3) To accomplish repetitive computation, it iterates with a for loop. 2. Consider the following function definition: (define (fib
PowerPoint Presentation Time and Space Complexity in Functional Programming, Part Two Introduction to the Lambda Calculus CS 345 Lecture 11 Functional programming invites certain problems! Recursion can cause… Stack overflow! Always passing data around as arguments to functions (instead of mutating it) leads to… Copies, copies everywhere! Only using recursive data structures (linked lists) leads
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PowerPoint Presentation Time and space complexity in functional programming CS 345 Lecture 10 Functional programming invites certain problems! Recursion can cause… Stack overflow! Always passing data around as arguments to functions (instead of mutating it) leads to… Copies, copies everywhere! Only using recursive data structures (linked lists) leads to… 0(n) lookup times compared to O(1)
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PowerPoint Presentation CS 345 Lecture 5 Last Session Lists as “recursive data structures” all lists are composed of the “head of the list” (car ls) and the “rest of the list” (cdr ls) (list 1 2 3) (car ls) = 1 (cdr ls) = (list 2 3) Recursion over lists evaluate (car ls) and recurse
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CS 345 CS 345 Lecture 4 Lab #1 Lab #1 Circle will be called ONCE. Lab #1 Last time: conditional branching class WhileIfDemo { public static void main(String[] args){ int count = 1; while (count < 11) { System.out.print("Count: " + count); if (count % 2 == 0) { System.out.println(“ is even.”); } else {
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AFE Lab 2 Unit Root tests and non-stationary time series This set of exercises are adapted from Example 3.2 of Mills and Markellos (2008). We shall be using the same data as in Lab 1 ‘FTSE.csv’. The learn- ing objective is to understand (a) the unit root tests and (b) the difference between a trend
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For the rest of the session… Functional Concurrency To review… We can write concurrent code with threads Definitions Concurrency: A program is concurrent if it may have more than one active execution context, i.e. more than one “thread of control” Thread: An independent pathway of code execution Parallelism: A concurrent program is “parallel” if more
CS计算机代考程序代写 Java concurrency data structure For the rest of the session… Read More »