'Dynamic semantics' diaporamas de présentation

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Inductive Definitions

Inductive Definitions. COS 510 David Walker. Inductive Definitions. Inductive definitions play a central role in the study of programming languages They specify the following aspects of a language: Concrete syntax (via CFGs) Abstract syntax (via CFGs/ML datatypes)

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Segmented Discourse Representation Theory A theory of discourse interpretation

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A Type System for Preventing Data Races and Deadlocks in the Java Virtual Machine Language

A Type System for Preventing Data Races and Deadlocks in the Java Virtual Machine Language. Pratibha Permandla Michael Roberson Chandrasekhar Boyapati. University of Michigan. Outline. Motivation Data Races Deadlocks Object Encapsulation Type System Related Work.

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Chapter 3

Chapter 3. Describing Syntax and Semantics. Chapter 3: Describing Syntax and Semantics. Objectives:. - Introduction - The General Problem of Describing Syntax - Formal Methods of Describing Syntax - Attribute Grammars - Describing the Meanings of Programs: Dynamic Semantics.

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Natural Ontologies : Understanding and Addressing Alignment Issues

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Role-based Access Control in a Mobile Environment

Role-based Access Control in a Mobile Environment. Elsa L Gunter (UI-UC) Joint work with Adriana Compagnoni (Stevens) Pablo Garralda (Stevens). Security in Necessary for Correct Functionality. Embeded devices often need to receive data (and increasingly new code) from remote sources

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Programming Language: Concurrent ML

Matt Defenthaler John Maskasky Vinash Seenath. Programming Language: Concurrent ML. 7/15/2009. Presentation Outline. CML Origins/History ML in CaML Shell Features of CML TraceCML CML vs. SML Dynamic Semantics Definitions Classes Grammar Evaluation Context Event Matching

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WebSim: A Pathway to Unveiling Term Relationships using a Web Search Technology [2006] Seokkyung Chung, Jongeun Jun,

WebSim: A Pathway to Unveiling Term Relationships using a Web Search Technology [2006] Seokkyung Chung, Jongeun Jun, and Dennis McLeod. Presented By: Amandeep Singh. Overview. Focus WebSim (Web Based Similarity Matrix) Dealing with Ambiguities

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Creating Visual DSMLs from End-User Demonstration

Creating Visual DSMLs from End-User Demonstration. Models in Software Engineering Workshop Zurich, Switzerland June 2 , 2012. Hyun Cho, Jeff Gray, and Eugene Syriani University of Alabama Department of Computer Science. This work supported in part by NSF CAREER #1052616.

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Automata Based Method for Domain Specific Languages Definition

Automata Based Method for Domain Specific Languages Definition . Ulyana Tikhonova PhD student at St. Petersburg State Politechnical University, supervised by Fedor Novikov Guest at TU/e, SET supervised by Mark van den Brand. Motivation. Domain Specific Languages

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MinML: an idealized programming language

MinML: an idealized programming language. CS 510 David Walker. MinML. Reading: Pierce chapter 1, 9 the meaning of program safety the typed lambda calculus Harper 5-8 MinML. MinML. MinML is an idealized programming language based on the lambda calculus the definition of MinML includes

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The Rosetta Meta-Model Framework

The Rosetta Meta-Model Framework. When see ball, wag tail. MEMS. OPTICS. HARDWARE. SOFTWARE. POWER. The Sony AIBO. MOTIVATION. Heterogeneous systems naturally complex Different technologies with different domain specific semantics Use of different techniques in design

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Key Challenges for Modeling Language Creation by Demonstration

Key Challenges for Modeling Language Creation by Demonstration. Hyun Cho, Jeff Gray Department of Computer Science University of Alabama. Yu Sun Dept. of Computer and Information science University of Alabama at Birmingham. Jules White Bradley Dept. of Electrical and Computer Engineering

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Reasoning about Relaxed Programs

Reasoning about Relaxed Programs. Michael Carbin Deokhwan Kim, Sasa Misailovic , and Martin Rinard. Research Focus. Non-Traditional Program Transformation Program Repair Eliminate memory leaks Eliminate memory errors (buffer overflows, segfaults ) Escape from infinite loops

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Forges: Synthesizing Verified Generators

Forges: Synthesizing Verified Generators. Kestrel Institute PIs: Cordell Green, John Anton CSs: Lindsay Errington, Doug Smith, Alessandro Coglio, Stephen Westfold, Jim McDonald. Objective: synthesize model-based generators!. Produce generators quicker! Produce generators that are verified!.

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Forges: Synthesizing Verified Generators

Forges: Synthesizing Verified Generators. Kestrel Institute PIs: Cordell Green, John Anton CSs: Lindsay Errington, Doug Smith, Alessandro Coglio, Stephen Westfold, Jim McDonald. Objective: synthesize model-based generators!. Produce generators quicker! Produce generators that are verified!.

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An ASN.1 Profile Anders Ek

An ASN.1 Profile Anders Ek. Motivation / Scenarios Profile Basics A Draft ASN.1 Profile Example Summary. Motivation: Usage Scenarios. Access to ASN.1 module from UML models Visualization of ASN.1 Modules Design of ASN.1 Modules. Accessing ASN.1 Modules. Precond: ASN.1 module exist

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Project-Team Triskell Model Driven Engineering for Component Based Software

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Static Checking and Type Systems

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