A recursive algorithm must have a- This is some condition which, if satisfied, is often asimple version of the problem that can be solved directly. This stops the algorithm fromforever. A recursive algorithm must calland the values of local variables and arguments arerecorded on theon each of these calls. A recursive algorithm must change itsthe problem inin such a way that it moves towards the base case, bysome way.unwindingreducingrecursingprogramPythonincreasingheapiteratingbase caseitselfalgorithmcall stackstatetransforminga friendstack casememorylist

A recursive algorithm must have a - This is some condition which, if satisfied, is often a simple version of the problem that can be solved directly. This stops the algorithm from for ever. A recursive algorithm must call and the values of local variables and arguments are on each of these calls. A recursive algorithm must change its recorded on the in such a way that it moves towards the base case, by the problem in some way. unwinding reducing recursing program Python increasing heap iterating base case itself algorithm call stack state transforming a friend stack case memory list

A recursive algorithm must have a - This is some condition which, if satisfied, is often a simple version of the problem that can be solved directly. This stops the algorithm from for ever. A recursive algorithm must call and the values of local variables and arguments are on each of these calls. A recursive algorithm must change its recorded on the in such a way that it moves towards the base case, by the problem in some way. unwinding reducing recursing program Python increasing heap iterating base case itself algorithm call stack state transforming a friend stack case memory list

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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A. Construct a RECURSIVE solution for following iterative solution to find a value in a circular-linked list B. Analyze the runtime complexity (correctly explain the scenario, show how much work would be done, and represent the work using asymptotic notations, i.e. big O), of the given iterative solution and your recursive solution for the best case scenario and the worse case scenario. C. prove the correctness of your recursive solution by induction /**@param value - a value to search for@return true if the value is in the list and set the current reference to itotherwise return false and not updating the current reference*/public boolean find(T value){ if(this.cur == null) return false; //get out, nothing is in here Node<T> tmp = this.cur; //start at the current position if(tmp.data == value) return true; // found it at the starting location tmp = tmp.next; //adv. to next node, if there is one while(tmp != cur) { if(tmp.data == value){ this.cur = tmp;…
8- Determine if each of the following recursive definition is a valid recursive definition of a function f from a set of non-negative integers. If f is well defined, find a formula for f(n) where n is non- negative and prove that your formula is valid. a. f(0) = 2,f(1) = 3, f(n) = f(n-1)-1 for n ≥ 2 b. f(0) = 1,f(1) = 2, f(n) = 2f (n-2) for n = 2
Given three sequences of length m, n, and p each, you are to design and analyze an algorithm to find the longest common subsequence (LCSS) for the three sequence. Is it possible to use dynamic programming to find the LCSS between the three sequences? If yes, provide recursive solution to the above problem. (Hint: We already designed dynamic programming algorithm for two sequences of length m and n in our class.)
a. Correctness of dynamic programming algorithm: Usually, a dynamic programming algorithm can be seen as a recursion and proof by induction is one of the easiest way to show its correctness. The structure of a proof by strong induction for one variable, say n, contains three parts. First, we define the Proposition P(n) that we want to prove for the variable n. Next, we show that the proposition holds for Base case(s), such as n = 0, 1, . . . etc. Finally, in the Inductive step, we assume that P(n) holds for any value of n strictly smaller than n' , then we prove that P(n') also holds. Use the proof by strong induction properly to show that the algorithm of the Knapsack problem above is correct. b. Bounded Knapsack Problem: Let us consider a similar problem, in which each item i has ci > 0 copies (ci is an integer). Thus, xi is no longer a binary value, but a non-negative integer at most equal to ci , 0 ≤ xi ≤ ci . Modify the dynamic programming algorithm seen at class for this…
Given three sequences of length m, n, and p each, you are to design and analyze an algorithm to find the longest common subsequence (LCSS) for the three sequence. Is it possible to use dynamic programming to find the LCSS between the three sequences? If yes, provide recursive solution to the above problem.
Recursion can be direct or indirect. It is direct when a function calls itself and it is indirect recursion when a function calls another function that then calls the first function. To illustrate solving a problem using recursion, consider the Fibonacci series: - 1,1,2,3,5,8,13,21,34...The way to solve this problem is to examine the series carefully. The first two numbers are 1. Each subsequent number is the sum of the previous two numbers. Thus, the seventh number is the sum of the sixth and fifth numbers. More generally, the nth number is the sum of n - 2 and n - 1, as long as n > 2.Recursive functions need a stop condition. Something must happen to cause the program to stop recursing, or it will never end. In the Fibonacci series, n < 3 is a stop condition. The algorithm to use is this: 1. Ask the user for a position in the series.2. Call the fib () function with that position, passing in the value the user entered.3. The fib () function examines the argument (n). If n < 3…
The Tower of Hanoi is a puzzle where n disks of different sizes arestacked in ascending order on one rod and there are two other rods with nodisks on them. The objective is to move all disks from the first rod to thethird, such that:- only one disk is moved at a time- a larger disk can never be placed on top of a smaller oneWrite a recursive function that outputs the sequence of steps needed tosolve the puzzle with n disks.Write a test program in C++ that allows the user to input number of disks andthen uses your function to output the steps needed to solve the puzzle.Hint: If you could move up n−1 of the disks from the first post to thethird post using the second post as a spare, the last disk could be moved fromthe first post to the second post. Then by using the same technique you canmove the n−1 disks from the third post to the second post, using the firstdisk as a spare. There! You have the puzzle solved. You only have to decidewhat the nonrecursive case is, what the recursive…
In programming, a recursive function calls itself. The classical example is factorial(n), which can be defined recursively as n*factorial(n-1). Nonethessless, it is important to take note that a recursive function should have a terminating condition (or base case), in the case of factorial, factorial(0)=1. Hence, the full definition is: factorial(n) = 1, for n = 0 factorial(n) = n * factorial(n-1), for all n > 1 For example, suppose n = 5: // Recursive call factorial(5) = 5 * factorial(4) factorial(4) = 4 * factorial(3) factorial(3) = 3 * factorial(2) factorial(2) = 2 * factorial(1) factorial(1) = 1 * factorial(0) factorial(0) = 1 // Base case // Unwinding factorial(1) = 1 * 1 = 1 factorial(2) = 2 * 1 = 2 factorial(3) = 3 * 2 = 6 factorial(4) = 4 * 6 = 24 factorial(5) = 5 * 24 = 120 (DONE) Exercise (Factorial) (Recursive): Write a recursive method called factorial() to compute the factorial of the given integer. public static int factorial(int n) The recursive algorithm is:…
Question: Let t(x) be the number of primes that are
Consider the following problems for recursive definition/solution. Answer the following questions. [Remember that a recursive definition/solution requires base case and recursive case] We learned that its power set has 2" elements when a set has n elements. Define it in a recursive solution.
16. Give a recursive definition for the set of all strings of 0's and l's for which all the O's precede all the l's.
REMINDER: - Every recursive function must have one or more base cases, - The general (recursive) case must eventually be reduced to a base case (terminating condition), - The base case stops the recursion, - Every recursive cal has its own copy of parameters and the local variables (1), -A recursive function is a function that calls itself (5). Let a be an array of integers. Present recursive algorithms and write their C implementations to compute: the maximum (minimum) element of the array, • the sum (product) of the elements of the array, • the average of the elements of the array HINT: Use functions having the following prototypes: name_of_the_function (int al 1, int n); For example, function that computes maximum/minimum element in the array can be named as find_max()/ find min ().