Wednesday, April 16, 2014

Size: px
Start display at page:

Download "Wednesday, April 16, 2014"

Transcription

1 Wednesday, pril 16, 2014 Topics for today Homework #5 solutions Code generation nalysis lgorithm 4: infix to tree Synthesis lgorithm 5: tree to code Optimization HW #5 solutions 1. lda 0,i ; for sum of elements ldx 510,I ; index of last element L: adda CMRIN,x ; add current element to total subx 2,i brge L ; branch if more to add asra asra asra asra asra asra asra asra ; divide total by 256 to get average sta av,d ldx 510,I ; second pass to get count L2: lda CMRIN,x cpa av,d brle skip ; branch if not greater than average lda count,d adda 1,i sta count,d ; count is incremented Skip:subx 2,i brge L2 ; branch if more to look at deco count,d stop av:.block 2 count:.word 0.end Comp 162 Notes Page 1 of 16 pril 16, 2014

2 2. ; exor ; precondition: stack,,? ; postcondition: stack,,exor(,) ; exor(,) = ( or ) and not ( and ) ; exor: ; for local sta -2,s ; save current value of Reg stx -4,s ; save current value of RegX lda 4,s ; ora 6,s ; or ; saved for later lda 4,s anda 6,s ; and nota ; not ( and ) anda 0,s ; ( or ) and not ( and ) sta 8,s ; is exor(,) = result lda -2,s ; restore register ldx -4,s ; restore register X ret2 3. Q3: lda 0,i Sta 0,s ; result initialized to zero ldx 4,s ; N aslx ; byte offset of Nth element L: lda 2,sxf ; element from array cpa 9999,i brgt add ; branch if larger than 9999 cpa -999,i brgt next ; branch if no need to bump count add: lda 6,s adda 2,i sta 6,s ; result is incremented next:subx 2,i brge L ; branch of more elements to look at ret0 Comp 162 Notes Page 2 of 16 pril 16, 2014

3 4. (a) void Q4 (int R[]) int i=15; while (i>=0 && R[i]==0) i--; if (i>=0) i--; while (i>=0) R[i]= 1-R[i]; i--; (b) negates the number Comp 162 Notes Page 3 of 16 pril 16, 2014

4 lgorithm 4: building a tree from an infix expression This algorithm is a variation on algorithm 3. It uses two stacks, one of operators and one of pointers to tree nodes. Here are the actions for the four types of symbol: Symbol ( ction put it on the operator stack with lowest possible priority ) Unstack and apply operators until "(" reached. Unstack but do not apply the "(" operand create a binary tree node with the operand as the data item and nil in the two pointer fields. Push a pointer to this node onto the operand stack operator while ( priority(top-of-operator-stack) priority(input) ) unstack and apply the top-of-operator-stack. push the input onto the operator stack t the end: unstack and apply any operators remaining on the operator stack What does "apply" an operator mean in this algorithm? It means create a binary tree node with the operator as the data item and left and right pointers containing the pointer values in the top items on the operand stack. Then pop those two items and push a pointer to the new node. For example, efore fter * 9 * Operator Operand Operator Operand Comp 162 Notes Page 4 of 16 pril 16, 2014

5 fter the expression has been read, we should get a binary expression tree pointed to from the only item left on the operand stack. Example: Expression * C D Input: Operator Stack <empty> Input: Operator Stack Comp 162 Notes Page 5 of 16 pril 16, 2014

6 Input: Operator Stack Input: * Operator Stack * Comp 162 Notes Page 6 of 16 pril 16, 2014

7 Input: C Operator Stack * C Input: Operator Stack * C Comp 162 Notes Page 7 of 16 pril 16, 2014

8 Input: D Operator Stack D * C t the end of input we unstack and apply the operators on the operator stack resulting in first. Comp 162 Notes Page 8 of 16 pril 16, 2014

9 Operator Stack D * C and finally, Operator Stack <empty> D * C Comp 162 Notes Page 9 of 16 pril 16, 2014

10 Error checking Here are some simple error checks we can add to lgorithm 4 to make it more robust 1. llowable sequences of symbols in the input Previous Symbol Current Symbol ( ) Operator Operand ( OK Error Error OK ) Error OK OK Error Operator OK Error Error OK Operand Error OK OK Error 2. Parentheses. We can maintain a counter, initially zero, that is incremented whenever we read an opening parenthesis and decremented when we read a closing one. The counter should never go negative and must be zero at the end of the input. 3. Operator. In general an operator requires n operands. In our case we just have n=2. There should be at least n items on the operand stack when we apply the operator. Next we will see how to generate assembly code from the binary tree. Comp 162 Notes Page 10 of 16 pril 16, 2014

11 Code generation lgorithm 5: generating assembly code Visiting all the nodes in a linked list is easy. We start at the beginning and move node-by-node to the end. Note that a list can be viewed as a recursive structure because it is made up of a head (the first node) and tail the rest of the list. The tail is also a list. Thus we could write a function to print a list recursively as follows: void printlist (listnode *L) if (L!= NULL) output (L->data); printlist(l->next); If we want to print the list backwards, it is quite tricky to do with iteration but a recursive solution is simple: void printlistbackwards (listnode *L) if (L!= NULL) printlistbackwards(l->next); output (L->data); binary tree can also be regarded as a recursive structure. It consists of a root node and (possibly empty) left and right sub-trees each of which in turn is a binary tree. "tree traversal" is a systematic visiting of all the nodes in a tree. Three common traversals are characterized by the order in which they visit the left and right sub-trees and the root node. Preorder: Inorder: Postorder: root, left, right left, root, right left, right, root. Comp 162 Notes Page 11 of 16 pril 16, 2014

12 The ordering is applied recursively to the sub-trees of the tree. For example if the tree is t / \ / \ w x / \ / \ / \ / \ h b a r / \ / \ j m preorder traversal visits the nodes in this order: t w h b x a r j m n inorder traversal visits the nodes in this order: h w b t a x j r m postorder traversal visits the nodes in this order: h b w a j m r x t lgorithm 5 Consider the binary expression tree that we have constructed by processing an arithmetic expression with lgorithm 4. We can traverse this tree and output appropriate instruction sequences for our target machine (in this case Pep/8). In the example that follows we assume that there is a MUL and a DIV instruction for * and / respectively. The sequence of instructions uses the Pep/8 user stack to evaluate the expression because, unlike the set of registers, this is virtually unlimited in size. For example, if the binary expression tree is X / \ / \ Y We generate ; next three lines from leaf X lda X,d ; next three lines from leaf Y lda Y,d ; next four lines from operator lda 0,s adda 2,s sta 2,s Comp 162 Notes Page 12 of 16 pril 16, 2014

13 When this sequence is executed on the Pep/8 machine we end up with the value of the expression as the top item on the Pep/8 stack. You can see from this example that the traversal we need is postorder (left, right, root). ecause the same ordering is used within subtrees, tree traversal algorithms are often recursive. This is illustrated in the following C/pseudocode function generate that outputs assembly language from a given expression tree. It assumes that the operands in the expression tree are names of global variables so it uses direct mode to reference them. void generate (treenode* T) if (T!= null) if ( T->left==NULL) /* true if node is a leaf */ printf("\n"); printf("lda %s,d\n",t->data);/* ssume T->data is name of a global */ printf("\n"); else generate(t->left); generate(t->right); printf("lda 0,s\n"); if (T->data == ) printf( DDa 2,s\n ); if (T->data == - ) printf( SUa 2,s\n ); if (T->data == * ) printf( MULa 2,s\n ); if (T->data == / ) printf( DIVa 2,s\n ); printf("sta 2,s\n"); printf("\n"); ) The tree generated from assignment X = ( C ) * ( D E ) Comp 162 Notes Page 13 of 16 pril 16, 2014

14 is = X * C D E In our implementation, because of the way that pointers in nodes are actually assigned, the code generated begins lda e,d lda d,d lda 0,s DDa 2,s sta 2,s If we substitute a call to a MUL subroutine in place of the MULr instruction then the complete sequence contains 32 instructions: 3 generated from each of the 5 leaves/operands 4 generated from each of the 3 operators 2 generated from the * operator ( call to MUL) 3 for the assignment and tidy up of stack Comp 162 Notes Page 14 of 16 pril 16, 2014

15 Optimization There is clearly scope for an optimizer to improve the code generated from lgorithm 5. Some possibilities are: (1) Removing redundant load instructions. See line 7 in the example above. (2) Combining/eliminating consecutive SP changes The translation of x=a*bc*d includes call MUL lda b,d oth changes to SP can be removed. In general, changes to SP on consecutive lines can be combined and if the net change is zero, they can be eliminated. (3) Combining SP operations with a wider view Example optimization (1) and (2) only require the optimizer to look at small sections of assembly code (perhaps two or three lines). y looking at larger sections, further savings might be possible. For example, the beginning of the translation of x=a*bc*d is lda d,d lda c,d which can be simplified to subsp 4,i lda d,d sta 2,s lda c,d Optimizations (1) and (2) have been implemented as shown in the following example. Comp 162 Notes Page 15 of 16 pril 16, 2014

16 $ codegen "x=a5*b7" $ codegen " x=a5*b7" optimizer lda 7,i lda b,d lda 5,i call MUL lda a,d lda 0,s DDa 2,s sta 2,s lda 0,s DDa 2,s sta 2,s lda 0,s sta x,d lda 7,i lda b,d lda 5,i call MUL lda a,d DDa 2,s sta 2,s lda 0,s DDa 2,s sta 2,s lda 0,s sta x,d Reading We have reached the end of Chapter 7 and will begin Chapter 8 next week. Comp 162 Notes Page 16 of 16 pril 16, 2014

Monday, April 15, We will lead up to the Analysis and Synthesis algorithms involved by first looking at three simpler ones.

Monday, April 15, We will lead up to the Analysis and Synthesis algorithms involved by first looking at three simpler ones. Monday, pril 15, 2013 Topics for today Code generation nalysis lgorithm 1: evaluation of postfix lgorithm 2: infix to postfix lgorithm 3: evaluation of infix lgorithm 4: infix to tree Synthesis lgorithm

More information

Wednesday, November 15, 2017

Wednesday, November 15, 2017 Wednesday, November 15, 2017 Topics for today Code generation Synthesis Algorithm 5: tree to code Optimizations Code generation Algorithm 5: generating assembly code Visiting all the nodes in a linked

More information

Monday, November 13, 2017

Monday, November 13, 2017 Monday, November 13, 2017 Topics for today ode generation nalysis lgorithm 1: evaluation of postfix lgorithm 2: infix to postfix lgorithm 3: evaluation of infix lgorithm 4: infix to tree nalysis We are

More information

Monday, November 9, 2015

Monday, November 9, 2015 Monday, November 9, 2015 Topics for today Grammars and Languages (Chapter 7) Finite State Machines Semantic actions Code generation - Overview nalysis lgorithm 1: evaluation of postfix lgorithm 2: infix

More information

Wednesday, March 12, 2014

Wednesday, March 12, 2014 Wednesday, March 12, 2014 Topics for today Solutions to HW #3 Arrays and Indexed Addressing Global arrays Local arrays Buffer exploit attacks Solutions to Homework #3 1. deci N,d < (a) N not defined lda

More information

Wednesday, October 17, 2012

Wednesday, October 17, 2012 Wednesday, October 17, 2012 Topics for today Arrays and Indexed Addressing Arrays as parameters of functions Multi-dimensional arrays Indexed branching Implementation of switch statement Arrays as parameters

More information

Monday, April 14, 2014

Monday, April 14, 2014 Monday, April 14, 2014 Topics for today Grammars and Languages (Chapter 7) Finite State Machines Semantic actions Code generation - Overview Analysis Algorithm 1: evaluation of postfix Algorithm 2: infix

More information

Monday, October 24, 2016

Monday, October 24, 2016 Monday, October 24, 2016 Topics for today Arrays and Indexed Addressing Arrays as parameters of functions Multi-dimensional arrays Option A: Space-minimal solution Option B: Iliffe vectors Array bound

More information

Monday, March 9, 2015

Monday, March 9, 2015 Monday, March 9, 2015 Topics for today C functions and Pep/8 subroutines Passing parameters by reference Globals Locals More reverse engineering: Pep/8 to C Representation of Booleans C Functions and Pep/8

More information

Monday, October 17, 2016

Monday, October 17, 2016 Monday, October 17, 2016 Topics for today C functions and Pep/8 subroutines Passing parameters by reference Globals Locals Reverse Engineering II Representation of Booleans C Functions and Pep/8 Subroutines

More information

Monday, October 26, 2015

Monday, October 26, 2015 Monday, October 26, 2015 Topics for today Indexed branching Implementation of switch statement Reusable subroutines Indexed branching It turns out that arrays are useful in translating other language constructs,

More information

CSC 221: Computer Organization, Spring 2009

CSC 221: Computer Organization, Spring 2009 1 of 7 4/17/2009 10:52 AM Overview Schedule Resources Assignments Home CSC 221: Computer Organization, Spring 2009 Practice Exam 2 Solutions The exam will be open-book, so that you don't have to memorize

More information

Monday, March 13, 2017

Monday, March 13, 2017 Monday, March 13, 2017 Topics for today Arrays and Indexed Addressing Global arrays Local arrays Buffer exploit attacks Arrays and indexed addressing (section 6.4) So far we have looked at scalars (int,

More information

Formal Languages and Automata Theory, SS Project (due Week 14)

Formal Languages and Automata Theory, SS Project (due Week 14) Formal Languages and Automata Theory, SS 2018. Project (due Week 14) 1 Preliminaries The objective is to implement an algorithm for the evaluation of an arithmetic expression. As input, we have a string

More information

Wednesday, February 28, 2018

Wednesday, February 28, 2018 Wednesday, February 28, 2018 Topics for today C functions and Pep/9 subroutines Introduction Location of subprograms in a program Translating functions (a) Void functions (b) Void functions with parameters

More information

Wednesday, March 14, 2018

Wednesday, March 14, 2018 Wednesday, March 14, 2018 Topics for today Arrays and Indexed Addressing Arrays as parameters of functions Multi-dimensional arrays Option A: Space-minimal solution Option B: Iliffe vectors Array bound

More information

Chapter 20: Binary Trees

Chapter 20: Binary Trees Chapter 20: Binary Trees 20.1 Definition and Application of Binary Trees Definition and Application of Binary Trees Binary tree: a nonlinear linked list in which each node may point to 0, 1, or two other

More information

Also, recursive methods are usually declared private, and require a public non-recursive method to initiate them.

Also, recursive methods are usually declared private, and require a public non-recursive method to initiate them. Laboratory 11: Expression Trees and Binary Search Trees Introduction Trees are nonlinear objects that link nodes together in a hierarchical fashion. Each node contains a reference to the data object, a

More information

Monday, March 6, We have seen how to translate void functions. What about functions that return a value such as

Monday, March 6, We have seen how to translate void functions. What about functions that return a value such as Monday, March 6, 2017 Topics for today C functions and Pep/9 subroutines Translating functions (c) Non-void functions (d) Recursive functions Reverse Engineering: Pep/9 to C C Functions and Pep/9 Subroutines

More information

Wednesday, February 15, 2017

Wednesday, February 15, 2017 Wednesday, February 15, 2017 Topics for today Before and after assembly: Macros, Linkers Overview of Chapter 6 Branching Unconditional Status bits and branching If statements While statements The V and

More information

Monday, March 27, 2017

Monday, March 27, 2017 Monday, March 27, 2017 Topics for today Indexed branching Implementation of switch statement Reusable subroutines Indexed branching It turns out that arrays are useful in translating other language constructs,

More information

Section 5.5. Left subtree The left subtree of a vertex V on a binary tree is the graph formed by the left child L of V, the descendents

Section 5.5. Left subtree The left subtree of a vertex V on a binary tree is the graph formed by the left child L of V, the descendents Section 5.5 Binary Tree A binary tree is a rooted tree in which each vertex has at most two children and each child is designated as being a left child or a right child. Thus, in a binary tree, each vertex

More information

TREES. Trees - Introduction

TREES. Trees - Introduction TREES Chapter 6 Trees - Introduction All previous data organizations we've studied are linear each element can have only one predecessor and successor Accessing all elements in a linear sequence is O(n)

More information

Lecture 37 Section 9.4. Wed, Apr 22, 2009

Lecture 37 Section 9.4. Wed, Apr 22, 2009 Preorder Inorder Postorder Lecture 37 Section 9.4 Hampden-Sydney College Wed, Apr 22, 2009 Outline Preorder Inorder Postorder 1 2 3 Preorder Inorder Postorder 4 Preorder Inorder Postorder Definition (Traverse)

More information

Wednesday, September 27, 2017

Wednesday, September 27, 2017 Wednesday, September 27, 2017 Topics for today Chapter 6: Mapping High-level to assembly-level The Pep/9 run-time stack (6.1) Stack-relative addressing (,s) SP manipulation Stack as scratch space Global

More information

Abstract Data Structures IB Computer Science. Content developed by Dartford Grammar School Computer Science Department

Abstract Data Structures IB Computer Science. Content developed by Dartford Grammar School Computer Science Department Abstract Data Structures IB Computer Science Content developed by Dartford Grammar School Computer Science Department HL Topics 1-7, D1-4 1: System design 2: Computer Organisation 3: Networks 4: Computational

More information

Why Do We Need Trees?

Why Do We Need Trees? CSE 373 Lecture 6: Trees Today s agenda: Trees: Definition and terminology Traversing trees Binary search trees Inserting into and deleting from trees Covered in Chapter 4 of the text Why Do We Need Trees?

More information

Revision Statement while return growth rate asymptotic notation complexity Compare algorithms Linear search Binary search Preconditions: sorted,

Revision Statement while return growth rate asymptotic notation complexity Compare algorithms Linear search Binary search Preconditions: sorted, [1] Big-O Analysis AVERAGE(n) 1. sum 0 2. i 0. while i < n 4. number input_number(). sum sum + number 6. i i + 1 7. mean sum / n 8. return mean Revision Statement no. of times executed 1 1 2 1 n+1 4 n

More information

Wednesday, September 21, 2016

Wednesday, September 21, 2016 Wednesday, September 21, 2016 Topics for today More high-level to translations Compilers and Assemblers How assemblers work Symbol tables ILC Pass 1 algorithm, Error checking Pass 2 Immediate mode and

More information

Wednesday, March 29, Implementation of sets in an efficient manner illustrates some bit-manipulation ideas.

Wednesday, March 29, Implementation of sets in an efficient manner illustrates some bit-manipulation ideas. Wednesday, March 29, 2017 Topics for today Sets: representation and manipulation using bits Dynamic memory allocation Addressing mode summary Sets Implementation of sets in an efficient manner illustrates

More information

An Introduction to Trees

An Introduction to Trees An Introduction to Trees Alice E. Fischer Spring 2017 Alice E. Fischer An Introduction to Trees... 1/34 Spring 2017 1 / 34 Outline 1 Trees the Abstraction Definitions 2 Expression Trees 3 Binary Search

More information

FORTH SEMESTER DIPLOMA EXAMINATION IN ENGINEERING/ TECHNOLIGY- MARCH, 2012 DATA STRUCTURE (Common to CT and IF) [Time: 3 hours

FORTH SEMESTER DIPLOMA EXAMINATION IN ENGINEERING/ TECHNOLIGY- MARCH, 2012 DATA STRUCTURE (Common to CT and IF) [Time: 3 hours TED (10)-3071 Reg. No.. (REVISION-2010) (Maximum marks: 100) Signature. FORTH SEMESTER DIPLOMA EXAMINATION IN ENGINEERING/ TECHNOLIGY- MARCH, 2012 DATA STRUCTURE (Common to CT and IF) [Time: 3 hours PART

More information

CSI33 Data Structures

CSI33 Data Structures Outline Department of Mathematics and Computer Science Bronx Community College November 13, 2017 Outline Outline 1 C++ Supplement.1: Trees Outline C++ Supplement.1: Trees 1 C++ Supplement.1: Trees Uses

More information

Stacks, Queues and Hierarchical Collections

Stacks, Queues and Hierarchical Collections Programming III Stacks, Queues and Hierarchical Collections 2501ICT Nathan Contents Linked Data Structures Revisited Stacks Queues Trees Binary Trees Generic Trees Implementations 2 Copyright 2002- by

More information

Course Administration

Course Administration Fall 2018 EE 3613: Computer Organization Chapter 2: Instruction Set Architecture Introduction 4/4 Avinash Karanth Department of Electrical Engineering & Computer Science Ohio University, Athens, Ohio 45701

More information

CMSC351 - Fall 2014, Homework #2

CMSC351 - Fall 2014, Homework #2 CMSC351 - Fall 2014, Homework #2 Due: October 8th at the start of class Name: Section: Grades depend on neatness and clarity. Write your answers with enough detail about your approach and concepts used,

More information

Data Structure Advanced

Data Structure Advanced Data Structure Advanced 1. Is it possible to find a loop in a Linked list? a. Possilbe at O(n) b. Not possible c. Possible at O(n^2) only d. Depends on the position of loop Solution: a. Possible at O(n)

More information

1. Stack overflow & underflow 2. Implementation: partially filled array & linked list 3. Applications: reverse string, backtracking

1. Stack overflow & underflow 2. Implementation: partially filled array & linked list 3. Applications: reverse string, backtracking Review for Test 2 (Chapter 6-10) Chapter 6: Template functions & classes 1) What is the primary purpose of template functions? A. To allow a single function to be used with varying types of arguments B.

More information

Introduction to Binary Trees

Introduction to Binary Trees Introduction to inary Trees 1 ackground ll data structures examined so far are linear data structures. Each element in a linear data structure has a clear predecessor and a clear successor. Precessors

More information

Stacks, Queues and Hierarchical Collections. 2501ICT Logan

Stacks, Queues and Hierarchical Collections. 2501ICT Logan Stacks, Queues and Hierarchical Collections 2501ICT Logan Contents Linked Data Structures Revisited Stacks Queues Trees Binary Trees Generic Trees Implementations 2 Queues and Stacks Queues and Stacks

More information

Data Structures. Trees. By Dr. Mohammad Ali H. Eljinini. M.A. Eljinini, PhD

Data Structures. Trees. By Dr. Mohammad Ali H. Eljinini. M.A. Eljinini, PhD Data Structures Trees By Dr. Mohammad Ali H. Eljinini Trees Are collections of items arranged in a tree like data structure (none linear). Items are stored inside units called nodes. However: We can use

More information

Monday, November 7, Structures and dynamic memory

Monday, November 7, Structures and dynamic memory Monday, November 7, 2016 Topics for today Structures Structures and dynamic memory Grammars and Languages (Chapter 7) String generation Parsing Regular languages Structures We have seen one composite data

More information

March 20/2003 Jayakanth Srinivasan,

March 20/2003 Jayakanth Srinivasan, Definition : A simple graph G = (V, E) consists of V, a nonempty set of vertices, and E, a set of unordered pairs of distinct elements of V called edges. Definition : In a multigraph G = (V, E) two or

More information

! Tree: set of nodes and directed edges. ! Parent: source node of directed edge. ! Child: terminal node of directed edge

! Tree: set of nodes and directed edges. ! Parent: source node of directed edge. ! Child: terminal node of directed edge Trees & Heaps Week 12 Gaddis: 20 Weiss: 21.1-3 CS 5301 Fall 2018 Jill Seaman!1 Tree: non-recursive definition! Tree: set of nodes and directed edges - root: one node is distinguished as the root - Every

More information

9/26/2018 Data Structure & Algorithm. Assignment04: 3 parts Quiz: recursion, insertionsort, trees Basic concept: Linked-List Priority queues Heaps

9/26/2018 Data Structure & Algorithm. Assignment04: 3 parts Quiz: recursion, insertionsort, trees Basic concept: Linked-List Priority queues Heaps 9/26/2018 Data Structure & Algorithm Assignment04: 3 parts Quiz: recursion, insertionsort, trees Basic concept: Linked-List Priority queues Heaps 1 Quiz 10 points (as stated in the first class meeting)

More information

University of Palestine. Final Exam 2 nd semester 2014/2015 Total Grade: 50

University of Palestine. Final Exam 2 nd semester 2014/2015 Total Grade: 50 First Question Q1 B1 Choose the best Answer: No. of Branches (1) (10/50) 1) 2) 3) 4) Suppose we start with an empty stack and then perform the following operations: Push (A); Push (B); Pop; Push (C); Top;

More information

A. Year / Module Semester Subject Topic 2016 / V 2 PCD Pointers, Preprocessors, DS

A. Year / Module Semester Subject Topic 2016 / V 2 PCD Pointers, Preprocessors, DS Syllabus: Pointers and Preprocessors: Pointers and address, pointers and functions (call by reference) arguments, pointers and arrays, address arithmetic, character pointer and functions, pointers to pointer,initialization

More information

2. Arithmetic Instructions addition, subtraction, multiplication, divison (HCS12 Core Users Guide, Sections 4.3.4, and ).

2. Arithmetic Instructions addition, subtraction, multiplication, divison (HCS12 Core Users Guide, Sections 4.3.4, and ). AS12 Assembler Directives A Summary of 9S12 instructions Disassembly of 9S12 op codes Huang Section 1.8, Chapter 2 MC9S12 V1.5 Core User Guide Version 1.2, Section 12 o A labels is a name assigned the

More information

Advanced Java Concepts Unit 5: Trees. Notes and Exercises

Advanced Java Concepts Unit 5: Trees. Notes and Exercises dvanced Java Concepts Unit 5: Trees. Notes and Exercises Tree is a data structure like the figure shown below. We don t usually care about unordered trees but that s where we ll start. Later we will focus

More information

CSC148 Week 6. Larry Zhang

CSC148 Week 6. Larry Zhang CSC148 Week 6 Larry Zhang 1 Announcements Test 1 coverage: trees (topic of today and Wednesday) are not covered Assignment 1 slides posted on the course website. 2 Data Structures 3 Data Structures A data

More information

CS350: Data Structures Tree Traversal

CS350: Data Structures Tree Traversal Tree Traversal James Moscola Department of Engineering & Computer Science York College of Pennsylvania James Moscola Defining Trees Recursively Trees can easily be defined recursively Definition of a binary

More information

CE 221 Data Structures and Algorithms

CE 221 Data Structures and Algorithms CE 221 Data Structures and Algorithms Chapter 4: Trees (Binary) Text: Read Weiss, 4.1 4.2 Izmir University of Economics 1 Preliminaries - I (Recursive) Definition: A tree is a collection of nodes. The

More information

Binary Trees. Examples:

Binary Trees. Examples: Binary Trees A tree is a data structure that is made of nodes and pointers, much like a linked list. The difference between them lies in how they are organized: In a linked list each node is connected

More information

Trees. (Trees) Data Structures and Programming Spring / 28

Trees. (Trees) Data Structures and Programming Spring / 28 Trees (Trees) Data Structures and Programming Spring 2018 1 / 28 Trees A tree is a collection of nodes, which can be empty (recursive definition) If not empty, a tree consists of a distinguished node r

More information

MULTIMEDIA COLLEGE JALAN GURNEY KIRI KUALA LUMPUR

MULTIMEDIA COLLEGE JALAN GURNEY KIRI KUALA LUMPUR STUDENT IDENTIFICATION NO MULTIMEDIA COLLEGE JALAN GURNEY KIRI 54100 KUALA LUMPUR FIFTH SEMESTER FINAL EXAMINATION, 2014/2015 SESSION PSD2023 ALGORITHM & DATA STRUCTURE DSEW-E-F-2/13 25 MAY 2015 9.00 AM

More information

IX. Binary Trees (Chapter 10)

IX. Binary Trees (Chapter 10) IX. Binary Trees (Chapter 10) -1- A. Introduction: Searching a linked list. 1. Linear Search /* To linear search a list for a particular Item */ 1. Set Loc = 0; 2. Repeat the following: a. If Loc >= length

More information

Advanced Java Concepts Unit 5: Trees. Notes and Exercises

Advanced Java Concepts Unit 5: Trees. Notes and Exercises Advanced Java Concepts Unit 5: Trees. Notes and Exercises A Tree is a data structure like the figure shown below. We don t usually care about unordered trees but that s where we ll start. Later we will

More information

CISC 235 Topic 3. General Trees, Binary Trees, Binary Search Trees

CISC 235 Topic 3. General Trees, Binary Trees, Binary Search Trees CISC 235 Topic 3 General Trees, Binary Trees, Binary Search Trees Outline General Trees Terminology, Representation, Properties Binary Trees Representations, Properties, Traversals Recursive Algorithms

More information

FORTH SEMESTER DIPLOMA EXAMINATION IN ENGINEERING/ TECHNOLIGY- OCTOBER, 2012 DATA STRUCTURE

FORTH SEMESTER DIPLOMA EXAMINATION IN ENGINEERING/ TECHNOLIGY- OCTOBER, 2012 DATA STRUCTURE TED (10)-3071 Reg. No.. (REVISION-2010) Signature. FORTH SEMESTER DIPLOMA EXAMINATION IN ENGINEERING/ TECHNOLIGY- OCTOBER, 2012 DATA STRUCTURE (Common to CT and IF) [Time: 3 hours (Maximum marks: 100)

More information

Binary Trees, Binary Search Trees

Binary Trees, Binary Search Trees Binary Trees, Binary Search Trees Trees Linear access time of linked lists is prohibitive Does there exist any simple data structure for which the running time of most operations (search, insert, delete)

More information

Wednesday, February 19, 2014

Wednesday, February 19, 2014 Wednesda, Februar 19, 2014 Topics for toda Solutions to HW #2 Topics for Eam #1 Chapter 6: Mapping High-level to assembl-level The Pep/8 run-time stack Stack-relative addressing (,s) SP manipulation Stack

More information

C Data Structures Stacks. Stack. push Adds a new node to the top of the stack

C Data Structures Stacks. Stack. push Adds a new node to the top of the stack 1 12 C Data Structures 12.5 Stacks 2 Stack New nodes can be added and removed only at the top Similar to a pile of dishes Last-in, first-out (LIFO) Bottom of stack indicated by a link member to NULL Constrained

More information

Data Structures. Binary Trees. Root Level = 0. number of leaves:?? leaves Depth (Maximum level of the tree) leaves or nodes. Level=1.

Data Structures. Binary Trees. Root Level = 0. number of leaves:?? leaves Depth (Maximum level of the tree) leaves or nodes. Level=1. Data Structures inary Trees number of leaves:?? height leaves Depth (Maximum level of the tree) leaves or nodes Root Level = 0 Level=1 57 feet root 2 Level=2 Number of nodes: 2 (2+1) - 1 = 7 2 inary Trees

More information

Wednesday, April

Wednesday, April Wednesday, April 9. 2014 Topics for today Addressing mode summary Structures Structures and dynamic memory Grammars and Languages (Chapter 7) String generation Parsing Regular languages Summary of addressing

More information

COMP 303 Computer Architecture Lecture 3. Comp 303 Computer Architecture

COMP 303 Computer Architecture Lecture 3. Comp 303 Computer Architecture COMP 303 Computer Architecture Lecture 3 Comp 303 Computer Architecture 1 Supporting procedures in computer hardware The execution of a procedure Place parameters in a place where the procedure can access

More information

WYSE Academic Challenge State Finals Computer Science 2007 Solution Set

WYSE Academic Challenge State Finals Computer Science 2007 Solution Set WYSE Academic Challenge State Finals Computer Science 2007 Solution Set 1. Correct answer: C. a) PGP is for encrypting documents, traditionally used for email. b) SSH is used to gain secure access to a

More information

Monday, February 16, 2015

Monday, February 16, 2015 Monday, February 16, 2015 Topics for today How assemblers work Symbol tables ILC Pass 1 algorithm, Error checking Pass 2 Immediate mode and equate Assembler variants: Disassembler, Cross assembler Macros

More information

F453 Module 7: Programming Techniques. 7.2: Methods for defining syntax

F453 Module 7: Programming Techniques. 7.2: Methods for defining syntax 7.2: Methods for defining syntax 2 What this module is about In this module we discuss: explain how functions, procedures and their related variables may be used to develop a program in a structured way,

More information

Trees. Q: Why study trees? A: Many advance ADTs are implemented using tree-based data structures.

Trees. Q: Why study trees? A: Many advance ADTs are implemented using tree-based data structures. Trees Q: Why study trees? : Many advance DTs are implemented using tree-based data structures. Recursive Definition of (Rooted) Tree: Let T be a set with n 0 elements. (i) If n = 0, T is an empty tree,

More information

Solution for Data Structure

Solution for Data Structure Solution for Data Structure May 2016 INDEX Q1 a 2-3 b 4 c. 4-6 d 7 Q2- a 8-12 b 12-14 Q3 a 15-18 b 18-22 Q4- a 22-35 B..N.A Q5 a 36-38 b N.A Q6- a 39-42 b 43 1 www.brainheaters.in Q1) Ans: (a) Define ADT

More information

CS61B Lecture #20: Trees. Last modified: Mon Oct 8 21:21: CS61B: Lecture #20 1

CS61B Lecture #20: Trees. Last modified: Mon Oct 8 21:21: CS61B: Lecture #20 1 CS61B Lecture #20: Trees Last modified: Mon Oct 8 21:21:22 2018 CS61B: Lecture #20 1 A Recursive Structure Trees naturally represent recursively defined, hierarchical objects with more than one recursive

More information

Computer Science 210 Data Structures Siena College Fall Topic Notes: Trees

Computer Science 210 Data Structures Siena College Fall Topic Notes: Trees Computer Science 0 Data Structures Siena College Fall 08 Topic Notes: Trees We ve spent a lot of time looking at a variety of structures where there is a natural linear ordering of the elements in arrays,

More information

Branch Addressing. Jump Addressing. Target Addressing Example. The University of Adelaide, School of Computer Science 28 September 2015

Branch Addressing. Jump Addressing. Target Addressing Example. The University of Adelaide, School of Computer Science 28 September 2015 Branch Addressing Branch instructions specify Opcode, two registers, target address Most branch targets are near branch Forward or backward op rs rt constant or address 6 bits 5 bits 5 bits 16 bits PC-relative

More information

Binary Trees. Height 1

Binary Trees. Height 1 Binary Trees Definitions A tree is a finite set of one or more nodes that shows parent-child relationship such that There is a special node called root Remaining nodes are portioned into subsets T1,T2,T3.

More information

Linear Data Structure

Linear Data Structure Linear Data Structure Definition A data structure is said to be linear if its elements form a sequence or a linear list. Examples: Array Linked List Stacks Queues Operations on linear Data Structures Traversal

More information

IX. Binary Trees (Chapter 10) Linear search can be used for lists stored in an array as well as for linked lists. (It's the method used in the find

IX. Binary Trees (Chapter 10) Linear search can be used for lists stored in an array as well as for linked lists. (It's the method used in the find IX. Binary Trees IX-1 IX. Binary Trees (Chapter 10) A. Introduction: Searching a linked list. 1. Linear Search /* To linear search a list for a particular Item */ 1. Set Loc = 0; 2. Repeat the following:

More information

Binary Tree. Binary tree terminology. Binary tree terminology Definition and Applications of Binary Trees

Binary Tree. Binary tree terminology. Binary tree terminology Definition and Applications of Binary Trees Binary Tree (Chapter 0. Starting Out with C++: From Control structures through Objects, Tony Gaddis) Le Thanh Huong School of Information and Communication Technology Hanoi University of Technology 11.1

More information

Assembly Language Manual for the STACK Computer

Assembly Language Manual for the STACK Computer Computer Science 301 1 Assembly Language Manual for the STACK Computer Assembly language programmers should read the hardware description of the STACK computer together with information about the effect

More information

First Semester - Question Bank Department of Computer Science Advanced Data Structures and Algorithms...

First Semester - Question Bank Department of Computer Science Advanced Data Structures and Algorithms... First Semester - Question Bank Department of Computer Science Advanced Data Structures and Algorithms.... Q1) What are some of the applications for the tree data structure? Q2) There are 8, 15, 13, and

More information

Recursive Data Structures and Grammars

Recursive Data Structures and Grammars Recursive Data Structures and Grammars Themes Recursive Description of Data Structures Grammars and Parsing Recursive Definitions of Properties of Data Structures Recursive Algorithms for Manipulating

More information

1) What is the primary purpose of template functions? 2) Suppose bag is a template class, what is the syntax for declaring a bag b of integers?

1) What is the primary purpose of template functions? 2) Suppose bag is a template class, what is the syntax for declaring a bag b of integers? Review for Final (Chapter 6 13, 15) 6. Template functions & classes 1) What is the primary purpose of template functions? A. To allow a single function to be used with varying types of arguments B. To

More information

EE 368. Week 6 (Notes)

EE 368. Week 6 (Notes) EE 368 Week 6 (Notes) 1 Expression Trees Binary trees provide an efficient data structure for representing expressions with binary operators. Root contains the operator Left and right children contain

More information

Exam I Review February 2017

Exam I Review February 2017 Exam I Review February 2017 Binary Number Representations Conversion of binary to hexadecimal and decimal. Convert binary number 1000 1101 to hexadecimal: Make groups of 4 bits to convert to hexadecimal,

More information

UNIT-II. Part-2: CENTRAL PROCESSING UNIT

UNIT-II. Part-2: CENTRAL PROCESSING UNIT Page1 UNIT-II Part-2: CENTRAL PROCESSING UNIT Stack Organization Instruction Formats Addressing Modes Data Transfer And Manipulation Program Control Reduced Instruction Set Computer (RISC) Introduction:

More information

! Tree: set of nodes and directed edges. ! Parent: source node of directed edge. ! Child: terminal node of directed edge

! Tree: set of nodes and directed edges. ! Parent: source node of directed edge. ! Child: terminal node of directed edge Trees (& Heaps) Week 12 Gaddis: 20 Weiss: 21.1-3 CS 5301 Spring 2015 Jill Seaman 1 Tree: non-recursive definition! Tree: set of nodes and directed edges - root: one node is distinguished as the root -

More information

3137 Data Structures and Algorithms in C++

3137 Data Structures and Algorithms in C++ 3137 Data Structures and Algorithms in C++ Lecture 3 July 12 2006 Shlomo Hershkop 1 Announcements Homework 2 out tonight Please make sure you complete hw1 asap if you have issues, please contact me will

More information

Tree traversals and binary trees

Tree traversals and binary trees Tree traversals and binary trees Comp Sci 1575 Data Structures Valgrind Execute valgrind followed by any flags you might want, and then your typical way to launch at the command line in Linux. Assuming

More information

There are many other applications like constructing the expression tree from the postorder expression. I leave you with an idea as how to do it.

There are many other applications like constructing the expression tree from the postorder expression. I leave you with an idea as how to do it. Programming, Data Structures and Algorithms Prof. Hema Murthy Department of Computer Science and Engineering Indian Institute of Technology, Madras Lecture 49 Module 09 Other applications: expression tree

More information

Unit 8: Analysis of Algorithms 1: Searching

Unit 8: Analysis of Algorithms 1: Searching P Computer Science Unit 8: nalysis of lgorithms 1: Searching Topics: I. Sigma and Big-O notation II. Linear Search III. Binary Search Materials: I. Rawlins 1.6 II. Rawlins 2.1 III. Rawlins 2.3 IV. Sigma

More information

Wednesday, February 7, 2018

Wednesday, February 7, 2018 Wednesday, February 7, 2018 Topics for today The Pep/9 memory Four example programs The loader The assembly language level (Chapter 5) Symbolic Instructions Assembler directives Immediate mode and equate

More information

EE 361 University of Hawaii Fall

EE 361 University of Hawaii Fall C functions Road Map Computation flow Implementation using MIPS instructions Useful new instructions Addressing modes Stack data structure 1 EE 361 University of Hawaii Implementation of C functions and

More information

SPRING TERM BM 310E MICROPROCESSORS LABORATORY PRELIMINARY STUDY

SPRING TERM BM 310E MICROPROCESSORS LABORATORY PRELIMINARY STUDY BACKGROUND 8086 CPU has 8 general purpose registers listed below: AX - the accumulator register (divided into AH / AL): 1. Generates shortest machine code 2. Arithmetic, logic and data transfer 3. One

More information

Binary Search Tree Binary Search tree is a binary tree in which each internal node x stores an element such that the element stored in the left subtree of x are less than or equal to x and elements stored

More information

Tree: non-recursive definition. Trees, Binary Search Trees, and Heaps. Tree: recursive definition. Tree: example.

Tree: non-recursive definition. Trees, Binary Search Trees, and Heaps. Tree: recursive definition. Tree: example. Trees, Binary Search Trees, and Heaps CS 5301 Fall 2013 Jill Seaman Tree: non-recursive definition Tree: set of nodes and directed edges - root: one node is distinguished as the root - Every node (except

More information

Postfix (and prefix) notation

Postfix (and prefix) notation Postfix (and prefix) notation Also called reverse Polish reversed form of notation devised by mathematician named Jan Łukasiewicz (so really lü-kä-sha-vech notation) Infix notation is: operand operator

More information

A rubric for programming assignments

A rubric for programming assignments Fall 2012 Comp 162 Peter Smith A rubric for programming assignments Generally, half the points for a program assignment are for the Correctness of the program with respect to the specification. The other

More information

EECE.3170: Microprocessor Systems Design I Summer 2017 Homework 4 Solution

EECE.3170: Microprocessor Systems Design I Summer 2017 Homework 4 Solution 1. (40 points) Write the following subroutine in x86 assembly: Recall that: int f(int v1, int v2, int v3) { int x = v1 + v2; urn (x + v3) * (x v3); Subroutine arguments are passed on the stack, and can

More information

Wednesday, November 8, 2017

Wednesday, November 8, 2017 Wednesday, November 8, 207 Topics for today Grammars and Languages (hapter 7) Finite State Machines Semantic actions ode generation - Overview Finite State Machines (see 7.2) If a language is regular (Type

More information

12 Abstract Data Types

12 Abstract Data Types 12 Abstract Data Types 12.1 Foundations of Computer Science Cengage Learning Objectives After studying this chapter, the student should be able to: Define the concept of an abstract data type (ADT). Define

More information

Wednesday, September 20, 2017

Wednesday, September 20, 2017 Wednesday, September 20, 2017 Topics for today More high-level to Pep/9 translations Compilers and Assemblers How assemblers work Symbol tables ILC Pass 1 algorithm, Error checking Pass 2 Immediate mode

More information