PPT-Matching Logic

A New Program Verification Approach Grigore Rosu and Andrei Stefanescu University of Illinois at UrbanaChampaign Question could it be that after 40 years of program verification we still lack the right semantically grounded program verification foundation. Quater wavelength transformer matching its advantages and limitations Single stub matching technique and its special features brPage 2br Module 2 Transmission Lines Lecture 15 Impedance Matching using Transmission Line Impedance Matching Impedance Permission granted for photocopy reproduction. Please do not alter or modify contents. All rights reserved. 800-338-4065 www.loveandlogic.com HEP Development. HEP Development. Who is HEP?. With more than 5,000 customers and 15 years experience, HEP has developed proven tools to help you identify and promote match opportunities, gain access to the highest quality prospect development information and enhance your data. . Based on. http://www.cs.engr.uky.edu/~. lewis/cs-heuristic/text/integer/linprog.html. The . bipartite graph matching problem.  is to find a set of unconnected edges which cover as many of the vertices as possible. If we select the set of edges. Logic. Grigore. . Rosu. and Andrei Stefanescu. University of Illinois, USA. Main Goal. Language-independent. program verification framework. D. erive program properties from . operational semantics. Grigore. . Rosu. and Andrei Stefanescu. University of Illinois, USA. Matching Logic . Reachability. - Goal -. Language independent program verification framework. Derives program properties based on the operational semantics of a language. Lecture 19: Nov 23. This Lecture. Graph matching is an important problem in graph theory.. It has many applications and is the basis of more advanced problems.. In this lecture we will cover two versions of graph matching problems.. t. o Programming Language Semantics,. to Program Verification. Grigore . Rosu. University of Illinois at Urbana-Champaign, USA. 1. How it all started. 1996: Started PhD with Joseph . Goguen. Discovered Maude as “fast OBJ”, then rewriting logic. ?. Anatoliy. . Konversky. ,. academician of National Academy . of Science of Ukraine,. D. ean of Philosophy Faculty. Taras. Shevchenko National University of Kyiv. . Dear colleagues. , participants of the conference! . Grigore. . Rosu. University of Illinois at . Urbana-Champaign (UIUC). Joint work with. Chucky Ellison . (UIUC). Wolfram Schulte . (Microsoft Research). How It Started. NASA project runtime . verification effort. We already know that the language of the machine is . binary. – that is, sequences of 1’s and 0’s. But why is this? . At the hardware level, computers are streams of signals. These signals only have two states of interest, high voltage and low voltage. . Learning Objectives. Know the three basic logic gate operators . Work out the output of given inputs using a truth table. All the instructions and data inside a computer are stored using binary. . Computer memory uses many small transistors and capacitors to store data. . Logic Gates. NOT (Inverter) Gate. AND Gate. OR Gate. NAND Gate. NOR Gate. XOR Gate. Digital Signals. Digital signals 0 (false) or 1 (true). Digital signal 1 is represented by a small voltage.. Digital signal 0 is represented by no voltage.. Learn what a logic gate is and what they are for.. Be able to identify common logic gates.. Understand how truth tables work.. What is a logic gate?. Logic gates are part of the circuits inside your computer. They can take several INPUTS. .