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Evaluating and Tuning a Static Analysis to Find Null Pointer Bugs

Evaluating and Tuning a Static Analysis to Find Null Pointer Bugs

Evaluating and Tuning a Static Analysis to Find Null Pointer Bugs. Dave Hovemeyer Bill Pugh Jaime Spacco. How hard is it to find null-pointer exceptions?. Large body of work academic research too much to list on one slide commercial applications PREFix / PREFast Coverity Polyspace.

By ryanadan
(412 views)

AVL-Trees

AVL-Trees

COMP171 Fall 2005. AVL-Trees. Balanced binary tree. The disadvantage of a binary search tree is that its height can be as large as N-1 This means that the time needed to perform insertion and deletion and many other operations can be O(N) in the worst case We want a tree with small height

By Patman
(894 views)

Evaluating and Tuning a Static Analysis to Find Null Pointer Bugs

Evaluating and Tuning a Static Analysis to Find Null Pointer Bugs

Evaluating and Tuning a Static Analysis to Find Null Pointer Bugs. Dave Hovemeyer Bill Pugh Jaime Spacco. How hard is it to find null-pointer exceptions?. Large body of work academic research too much to list on one slide commercial applications PREFix / PREFast Coverity Polyspace.

By sawyer
(98 views)

Chapter 20 Lists, Stacks, Queues, Trees, and Heaps

Chapter 20 Lists, Stacks, Queues, Trees, and Heaps

Chapter 20 Lists, Stacks, Queues, Trees, and Heaps. Objectives. To describe what a data structure is (§20.1). To explain the limitations of arrays (§20.1). To implement a dynamic list using an array (§20.2.1). To implement a dynamic list using a linked structure (§20.2.2 Optional).

By lathrop
(573 views)

Mathematical Induction II

Mathematical Induction II

Mathematical Induction II. Lecture 22 Section 4.3 Mon, Feb 26, 2007. Example. Find a formula for 1 + 3 + 5 + … + (2 n – 1). and use mathematical induction to prove that it is correct. Exercise. Find a formula for 1 2 + 3 2 + 5 2 + … + (2 n – 1) 2 .

By farren
(197 views)

Optimal binary search trees

Optimal binary search trees

Optimal binary search trees . e.g. binary search trees for 3, 7, 9, 12; . Optimal binary search trees. n identifiers : a 1 <a 2 <a 3 < … < a n P i , 1  i  n : the probability that a i is searched. Q i , 0  i  n : the probability that x is searched

By ofira
(839 views)

CSE 326: Data Structures Trees

CSE 326: Data Structures Trees

CSE 326: Data Structures Trees. Lecture 6: Friday, Jan 17, 2003. Trees. Material: Weiss Chapter 4 N-ary trees Binary Search Trees AVL Trees Splay Trees. Tree Jargon. Nodes: A, B, …, F Root node: A Leaf nodes: B, E, F, D Edges: (A,B), (A,C), …, (C, F)

By liesel
(240 views)

B-Trees

B-Trees

B-Trees. Large degree B-trees used to represent very large dictionaries that reside on disk. Smaller degree B-trees used for internal-memory dictionaries to overcome cache-miss penalties. AVL Trees. n = 2 30 = 10 9 (approx). 30 <= height <= 43 .

By lorant
(144 views)

Priority Queues

Priority Queues

Priority Queues. Priority queue. A stack is first in, last out A queue is first in, first out A priority queue is least-first-out The “smallest” element is the first one removed (You could also define a largest-first-out priority queue)

By iphigenie
(274 views)

Proving termination conditions

Proving termination conditions

Proving termination conditions . Mentor : Dr. Ben Livshits & Dr. Stephan Tobies. The Project. The aim: Investigate state of the art approaches for termination proof; Prove termination of sample algorithms. We focused on the following cases: Nested loops ; Recursion ;

By terry
(279 views)

A Binary Search Tree Implementation

A Binary Search Tree Implementation

A Binary Search Tree Implementation. Chapter 17. Getting Started An Interface for the Binary Search Tree Duplicate Entries Beginning the Class Definition Searching and Retrieving Traversing Adding an Entry Recursive Implementation Removing an Entry Whose Node is a leaf.

By ryo
(248 views)

Binary Trees

Binary Trees

Binary Trees. Overview. Trees. Terminology. Traversal of Binary Trees. Expression Trees. Binary Search Trees. Trees. Family Trees. Organisation Structure Charts. Program Design. Structure of a chapter in a book. Parts of a Tree. Parts of a Tree. nodes. Parts of a Tree. parent node.

By lucretia
(112 views)

Recall: Representation Changes:

Recall: Representation Changes:

Recall: Representation Changes: Gaussian elimination solves a system of linear equations by first transforming it to another system that makes finding a solution quite easy.

By wardah
(114 views)

Chapter 7

Chapter 7

Chapter 7. Dynamic Programming. Fibonacci sequence. Fibonacci sequence : 0 , 1 , 1 , 2 , 3 , 5 , 8 , 13 , 21 , … F i = i if i  1 F i = F i-1 + F i-2 if i  2 Solved by a recursive program: Much replicated computation is done.

By libby
(170 views)

Binary Search Trees

Binary Search Trees

Binary Search Trees. Dictionary Operations: get(key) put(key, value) remove(key) Additional operations: ascend() get(index) (indexed binary search tree) remove(index) (indexed binary search tree). n is number of elements in dictionary.

By makya
(160 views)

AVL Search Trees

AVL Search Trees

AVL Search Trees. What is an AVL Tree? AVL Tree Implementation. Why AVL Trees? Rotations. What is an AVL Tree?. An AVL tree is a binary search tree with a height balance property: For each node v, the heights of the subtrees of v differ by at most 1.

By huey
(198 views)

Binary Search Trees

Binary Search Trees

Binary Search Trees. 6. <. 2. 9. >. =. 8. 1. 4. Ordered Dictionaries. Keys are assumed to come from a total order. New operations: first (): first entry in the dictionary ordering last (): last entry in the dictionary ordering

By karli
(115 views)

CS 332: Algorithms

CS 332: Algorithms

CS 332: Algorithms. Go Over Midterm Intro to Graph Algorithms. T(n) = 1 + 1 + 1 + 1 + … + 1 = O(n) . O(n) terms. Problem 1: Recurrences. Give asymptotic bounds for the following recurrences. Justify by naming the case of the master theorem, iterating, or substitution a. T(n) = T(n-2) + 1

By mieko
(155 views)

B-Trees

B-Trees

B-Trees. Large degree B-trees used to represent very large dictionaries that reside on disk. Smaller degree B-trees used for internal-memory dictionaries to overcome cache-miss penalties. AVL Trees. n = 2 30 = 10 9 (approx). 30 <= height <= 43 .

By kiara
(173 views)

Set Implementations

Set Implementations

Set Implementations. Bit Vector Linked List (Sorted and Unsorted) Hash Table Search Trees. Bit Vector. A = 1 0 0 1 1 0 0 1 0 1 0 0 1 1 0 1 U = a i , 0 <= i <= 15 A = {a 0 ,a 3 ,a 4 ,a 7 ,a 9 ,a 12 ,a 13 ,a 15 } 1 Bit per possible element

By nairi
(118 views)

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