DOCSLIB.ORG

MIT Laboratory for Computer Science Progress Report No. 23, July 1985-June 1986

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
MIT Laboratory for Computer Science Progress Report No. 23, July 1985-June 1986 61 , on Massachusetts Institute of Technology Laboratory for Computer Science July 1985- Progress Report June1986 23 DTIC M,% ;,I ECTE ,->0 CT05 1990 DISSTRB 101,STAThmb57 A Approved for public release; 90 10r4t13ed 90 10 04 13-0- .ccession For gi'S 3TCC T\3GRA&I Massachusetts Institute of Technology UxTnounced Laboratory for Computer Science Just ificatio 545 Technology Square Cambridge, MA 02139 Distribution/ 617-253-5851 Availability Codes Avail and/or Dist Special The work reported herein was carried out within the Laboratory for Computer Science, an MIT interdepartmental laboratory. During 1985-86 the principal financial support of the Laboratory has come from the Defense Advanced Research Projects Agency (DARPA). DARPA has been instrumental in supporting most of our research during the last 23 years and is gratefully acknowledged here. Our overall support has come from the following organizations: " Defense Advanced Research Projects Agency; " Department of Energy; " National Institutes of Health; * National Science Foundation; " Office of Naval Research; * United States Air Force; " United States Army Research Office; " MIT controlled IBM funds under an IBM/MIT joint study contract. Other support of a generally smaller level has come from Harris Corporation, Siemens, and Giers. Final assembly and production of this report was done by Paula Vancini with special assistance from Maria Sensale and Mary Weston. Unclassified SECURITY CLASSIFICATION OF THIS PAGE REPORT DOCUMENTATION PAGE la. REPORT SECURITY CLASSIFICATION lb. RESTRICTIVE MARKINGS Unclassified 2a. SECURITY CLASSIFICATION AUTHORITY 3. DISTRIBUTION /AVAILABILITY OF REPORT Approved for public release; distribution SCHEDULE Approved 2b. DECLASSIFICATION/DOWNGRADING is unlimited. 4. PERFORMING ORGANIZATION REPORT NUMBER(S) 5. MONITORING ORGANIZATION REPORT NUMBER(S) MIT/LCS/PR - 23 6a. NAME OF;I PERFORMING ORGANIZATION i6b. OFFICE(ifapplicable) SYMBOL 7a. NAME OF MONITORING ORGANIZATION MIT Lab for Computer Science Office of Naval Research/Dept. of Navy 6c. ADDRESS (City, State, and ZIP Code) 7b. ADDRESS (City, State, and ZIP Code) 545 Technology Square Information Systems Program Cambridge, MA 02139 Arlington, VA 22217 8a. NAME OF FUNDING/SPONSORING 8b. OFFICE SYMBOL 9. PROCUREMENT INSTRUMENT IDENTIFICATION NUMBER ORGANIZATIONI (If applicable) DARPA/ DOD 8c. ADDRESS (City, State, and ZIPCode) 10. SOURCE OF FUNDING NUMBERS PROGRAM PROJECT TASK WORK UNIT 1400 Wilson Blvd. ELEMENT NO. NO. NO. ACCESSION NO. Arlington, VA 22217 11. TITLE (Include Security Classification) MIT Laboratory for Computer Science Progress Report 23 12. PERSONAL AUTHOR(S) Dertouzos, M.L. 13a. TYPE OF REPORT 13b. TIME COVERED 114. DATE OF REPORT (Year, Month, Day) 15. PAGE COUNT Technical/Progress I FROM 7/85 TO 6/86 June 1986 i 292 16. SUPPLEMENTARY NOTATION 17. COSATI CODES 18. SUBJECT TERMS (Continue on reverse if necessary and identify by blck number) FIELD GROUP T SUB-GROUP Computer Architecture, Computer Science, Computer Systems, Electrical Engineering, Networks Theory of Computers, Proarammina Lanauaasc 19. ABSTRACT (Continue on reverse if necessary and identify by block number) Annual Report of Progress made at the MIT Laboratory for Computer Science Under contracts: a.) N00014-83k-0125,Darpa Order 5602/2095 b.) N00014-84k-0059, Darpa Order 4920 20 DISTRIBUTION/AVAILABILITY OF ABSTRACT 21. ABSTRACT SECURITY CLASSIFCArION M] UNCLASSIFIED/UNLIMITED 0 SAME AS RPT. 0 OTIC USERS Unclassified 22a, NAME OF RESPONSIBLE INDIVIDUAL 22b. TELEPHONE (Include Area Code) 22c. OFFICE SYMBOL Carol Nicolora i (617) 253-5894 1 1 DD FORM 1473,84 MAR 83 APR edition may be used until exhausted. SECURITY CLASSIFICATION OF THIS PAGE All other editions are obsolete. *153. Gomrnwnt- rktdn Offi-: 1M-807-47 Unclassified INTRODUCTION MAIG1 CLINICAL DECISION .K,.GJ 5 1. Introduction 7 2. An Artificial Intelligence Appro0ch to Clinical Decision Making 7 2.1. Knowledge Representtio'n 10 2.2. Development of a nlfform Knowledge Base 13 2.3. Importing C onents of Existing Reasoning Systems 18 2.4-Repre-entation and Organization of Case-Specific Knowledge 18 2.5. Qualitative Methods of Reasoning 19 2.6. Integration of Al and Decision Analytic Methods 20 2.7. Decision Tree Critiquer 20 2.8. Planning Under Uncertainty 25 3. A Program for the Management of Heart Failure 26 COMMON SYSTEM, \ 35 1. Overview 36 2. Remote In on 36 3. .rogrm Specification 39 4. Service Interfaces 40 5. Future Plans S /,ft 41 COMPUTATION STRUCTURES '/43 1. Introduction 45 2. Personnel 46 3. Multiprocessor Emulation Facility 47 3.1. The Current MEF Hardware and the Circuit Switch 47 3.2. The Packet Switch Development 49 3.3. The Hardware Laboratory and New Equipment 51 4. Tools for Dataflow Experiments 51 4.1. Id Compiler 52 4.2. GITA 53 4.3. U-GITA 54 4.4. MEF-GITA 54 4.5. SITA: A Simulator for the Tagged-Token Machine 55 4.6. Id World 55 5. Experiments on MEF 56 5.1. Dataflow Experiments 56 5.1.1 Token Storage Management 56 5.1.2 Structure Storage Management 57 5.1.3 Work Distribution 57 5.1.4 Limitations of MEF GITA 58 5.2. DisCoRd: Parallel Graph Reduction on the MEF 58 6. Language Research for the Tagged-Token Dataflow 59 Architecture 6.1. Id/83s 59 6.1.1 I-structures in Id/83s 60 6.1.2 Types in ld/83s 61 6.1.3 Garbage Collection Experiments on MEF 63 6.2. Demand-driven Evaluation 64 6.3. Databases and Functional Languages 64 6.3.1 Data Models and Type Structure 65 6.3.2 Modeling State 65 6.3.3 Functional Databases 66 7. Work Under Professor Dennis 67 7.1. The ViM Project 67 7.2. Accomplishments 67 7.3. Compiling for the Static Dataflow Machine 69 7.4. Simulating Applicative Architectures on the Connection 70 Machine DISTRIBUTED COMPUTING SYSTEMS' 79 1. Introduction 80 2. SWIFT 80 3. Residential CATV-Based Data Commu cations 81 4. Long Atomic Transactions 82 5. Resource Management in Pac etworks 84 6. The NETBLT Protocol 85 7. PCMAIL: A.Distribtited Mail System for Personal Computers 86 ,,,,.-NtWork onitoring 88 9. Access to Inter-Organization Computer Networks 89 INFORMATION MECHANICS . 95 1. Introduction 96 2. Cellular Automata Machines 96 3. The CAM-7 Multi ro 96 4. Fl id-.Dy mics Modeling 97 -. Combinatorial Dynamics 97 6. CA '86 97 7. Neural Networks 97 8. STATPHYS-16 98 PROGRAMMING METHODOLOGY 101 1. Summary 103 1.1. Argus 103 2. Evaluation of Argus 104 3. Specificatio o istributed Programs 108 4 i-tiations on Availability in the Presence of Partit' ns 116 4.1. Assumptions and Definitions 117 4.2. Analysis 118 P,,G3 AM,,..,,,,,,M,, ING V ,.,,,..,RA., RESEARC. , 127 1. Introduction ) 128 2. Plans for the Next Year 128 3. Overview of the Boston Community Information System 129 4. The Data Model 131 5. Composite Databases 133 © 6. The Personal Database System 134 7. Database Servers 137 8. Related Work 141 9. Performance and Implementation Statu$ 143 10. Conclusions 144 - EAL TIME SYSTEMS' 155 1. Introduction j) 157 2. Parallel Processing 157 2.1. The Concert Multi rocessor Testbed 157 161 2.3.2.2. CollaborationParallel Lisp tth Other Organizationts 158 162 3. The3.1. LArchit Architect ral Model 161164 3.2. Pr typical L Implementation 164 4. Arc cturalh Building Blocks 165 5. imulation Tools for VLSI 166 5.1.3 Circuit Partitioning 167 5.2. Decoupling the Simulations 170169 // 5.3. PRSIM Performance 6. Schema Developments 171 6.1. Schematic Entry System 172 6.2. Software Organization 7. Database Accelerator 173 8. X-Windows 173 SYSTEMATIC PROGRAM DEVELOPMENT) 183 1. Introduction 184 2. Larch 184 2.1. The Larch Family of S t n Lalguages 186 or for e arch Shared Langoeige 187 2.3. Analysis Tools 188 2.4. Concurrency 188 2.5. Larch Interface Languages 189 3. The Reve Term Rewriting System 190 3.1. Reve 2.4 190 3.2. Unification 191 THEORY OF COMPUTATION, 197 1. Research Overview 199 2. Faculty and Research Associates 199 3. Students and Visitors 209 THEORY OF DISTRIBUTED SYSTEMS 235 1. Individual Progress Reports 236 PUBLICATIONS 247 ADMINISTRATION Academic Staff M. Dertouzos Director R. Rivest Associate Director Administrative Staff P. Anderegg Assistant Administrative Officer A. Chow Fiscal Officer G. Brown Facilities Officer J. Hynes Administrative Officer M. Jones Assistant Administrative Officr M. Sensale Librarian Support Staff L. Cavallaro B. Pierce R. Donahue E. Profirio M. Gibson D. Simmons A. Kekejian P. Vancini T. LoDuca S. Van Norden INTRODUCTION The MIT Laboratory for Computer Science (LCS) is an interdepartmental laboratory .hose principal goal is research in computer science and engineering. Founded in 1963 as Project MAC (for Multiple Access Computer and Machine Aided Cognition), the Laboratory developed the Compatible Time Sharing System (CTSS), one of the first time shared systems in the world, and Multics -- an improved time shared system that introduced several new concepts. These two major developments stimulated research activities in the application of on-line computing to such diverse disciplines as engineering, architecture, mathematics, biology, medicine, library science and management. Since that time, the Laboratory's pursuits expanded, leading to pioneering research in Expert Systems, Computer Networks and Public Cryptography. Today, the Laboratory's research spans a broad front of activities, grouped in four major are a s ' The first such area entitled ' owledge Based Systems involves making programs more intelligent by capturing, representing, and using knowle ge which is specific to the problem domain. Examples are the use of expert medical nowledge for assistance in diagnosis carried out by the Clinical Decision Making Gl up; and the use of solid-state circuit design knowledge for an expert VLSI (very lar( scale integration) design system by the VLSI Design Project. Research in the second and largest area, entitled Machines, Languages, and Systemstrives to discover and understand computing systems at both the hardware and softwa' levels that open new application areas and/or effect sizable improvements in their ease f utilization and cost effectiveness.
Load more

Recommended publications
  • Constructive Design of a Hierarchy of Semantics of a Transition System by Abstract Interpretation
    1 Constructive Design of a Hierarchy of Semantics of a Transition System by Abstract Interpretation Patrick Cousota aD´epartement d’Informatique, Ecole´ Normale Sup´erieure, 45 rue d’Ulm, 75230 Paris cedex 05, France, [email protected], http://www.di.ens.fr/~cousot We construct a hierarchy of semantics by successive abstract interpretations. Starting from the maximal trace semantics of a transition system, we derive the big-step seman- tics, termination and nontermination semantics, Plotkin’s natural, Smyth’s demoniac and Hoare’s angelic relational semantics and equivalent nondeterministic denotational se- mantics (with alternative powerdomains to the Egli-Milner and Smyth constructions), D. Scott’s deterministic denotational semantics, the generalized and Dijkstra’s conser- vative/liberal predicate transformer semantics, the generalized/total and Hoare’s partial correctness axiomatic semantics and the corresponding proof methods. All the semantics are presented in a uniform fixpoint form and the correspondences between these seman- tics are established through composable Galois connections, each semantics being formally calculated by abstract interpretation of a more concrete one using Kleene and/or Tarski fixpoint approximation transfer theorems. Contents 1 Introduction 2 2 Abstraction of Fixpoint Semantics 3 2.1 Fixpoint Semantics ............................... 3 2.2 Fixpoint Semantics Approximation ...................... 4 2.3 Fixpoint Semantics Transfer .......................... 5 2.4 Semantics Abstraction ............................. 7 2.5 Fixpoint Semantics Fusion ........................... 8 2.6 Fixpoint Iterates Reordering .......................... 8 3 Transition/Small-Step Operational Semantics 9 4 Finite and Infinite Sequences 9 4.1 Sequences .................................... 9 4.2 Concatenation of Sequences .......................... 10 4.3 Junction of Sequences ............................. 10 5 Maximal Trace Semantics 10 2 5.1 Fixpoint Finite Trace Semantics .......................
    [Show full text]
  • Towards a Unified Theory of Operational and Axiomatic Semantics — Extended Abstract —
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Illinois Digital Environment for Access to Learning and Scholarship Repository Towards a Unified Theory of Operational and Axiomatic Semantics — Extended Abstract — Grigore Ros¸u and Andrei S¸tefanescu˘ Department of Computer Science, University of Illinois at Urbana-Champaign fgrosu, [email protected] Abstract. This paper presents a nine-rule language-independent proof system that takes an operational semantics as axioms and derives program properties, including ones corresponding to Hoare triples. This eliminates the need for language-specific Hoare-style proof rules in order to verify programs, and, implicitly, the tedious step of proving such proof rules sound for each language separately. The key proof rule is Circularity, which is coinductive in nature and allows for reasoning about constructs with repetitive behaviors (e.g., loops). The generic proof system is shown sound and has been implemented in the MatchC program verifier. 1 Introduction An operational semantics defines a formal executable model of a language typically in terms of a transition relation cfg ) cfg0 between program configurations, and can serve as a formal basis for language understanding, design, and implementation. On the other hand, an axiomatic semantics defines a proof system typically in terms of Hoare triples f g code f 0g, and can serve as a basis for program reasoning and verification. Operational semantics are well-understood and comparatively easier to define than axiomatic semantics for complex languages. More importantly, operational semantics are typically executable, and thus testable. For example, we can test them by executing the program benchmarks that compiler testers use, as has been done with the operational semantics of C [5].
    [Show full text]
  • Axiomatic Semantics
    Advanced Topics in Programming Languages Spring Semester, 2012 Lecture 6: April 24, 2012 Lecturer: Mooly Sagiv Scribe: Michal Balas and Yair Asa Axiomatic Semantics 6.1 The basic idea The problem we would like to solve is how to prove that a program does what we require of it. Given a program, we specify its required behavior based on our intuitive understanding of it. We can run it according to the operational semantics or denotational semantics and compare to its behavior there. For some programs we need to be more abstract (for example programs that receive input), and then it is necessary to use some logic to reason about the program (and how it behaves on a set of inputs and not in one specific execution path). In this case we may eventually develop a formal proof system for properties of the program or showing that it satisfies a requirement. We can then use the proof system to show correctness. These rules of the proof system are called Hoare or Floyd-Hoare rules. Floyd-rules are for flow-charts and Hoare-rules are for structured languages. Originally their approach was advocated not just for proving properties of programs but also giving a method for explaining the meaning of program. The meaning of a program was specified in terms of \axioms" saying how to prove properties of it, in other words it is given by a set of verification rules. Therefore, this approach was named axiomatic semantics. Axiomatic semantics has many applications, such as: Program verifiers • Symbolic execution tools for bug hunting • Software validation tools • Malware detection • Automatic test generation • It is also used for proving the correctness of algorithms or hardware descriptions, \extended static checking (e.g., checking array bounds), and documenting programs and interfaces.
    [Show full text]
  • Making Classes Provable Through Contracts, Models and Frames
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by CiteSeerX DISS. ETH NO. 17610 Making classes provable through contracts, models and frames A dissertation submitted to the SWISS FEDERAL INSTITUTE OF TECHNOLOGY ZURICH (ETH Zurich)¨ for the degree of Doctor of Sciences presented by Bernd Schoeller Diplom-Informatiker, TU Berlin born April 5th, 1974 citizen of Federal Republic of Germany accepted on the recommendation of Prof. Dr. Bertrand Meyer, examiner Prof. Dr. Martin Odersky, co-examiner Prof. Dr. Jonathan S. Ostroff, co-examiner 2007 ABSTRACT Software correctness is a relation between code and a specification of the expected behavior of the software component. Without proper specifica- tions, correct software cannot be defined. The Design by Contract methodology is a way to tightly integrate spec- ifications into software development. It has proved to be a light-weight and at the same time powerful description technique that is accepted by software developers. In its more than 20 years of existence, it has demon- strated many uses: documentation, understanding object-oriented inheri- tance, runtime assertion checking, or fully automated testing. This thesis approaches the formal verification of contracted code. It conducts an analysis of Eiffel and how contracts are expressed in the lan- guage as it is now. It formalizes the programming language providing an operational semantics and a formal list of correctness conditions in terms of this operational semantics. It introduces the concept of axiomatic classes and provides a full library of axiomatic classes, called the mathematical model library to overcome prob- lems of contracts on unbounded data structures.
    [Show full text]
  • The Monastic Rules of Visigothic Iberia: a Study of Their Text and Language
    THE MONASTIC RULES OF VISIGOTHIC IBERIA: A STUDY OF THEIR TEXT AND LANGUAGE By NEIL ALLIES A thesis submitted to The University of Birmingham for the degree of DOCTOR OF PHILOSOPHY Department of Theology and Religion College of Arts and Law The University of Birmingham July 2009 University of Birmingham Research Archive e-theses repository This unpublished thesis/dissertation is copyright of the author and/or third parties. The intellectual property rights of the author or third parties in respect of this work are as defined by The Copyright Designs and Patents Act 1988 or as modified by any successor legislation. Any use made of information contained in this thesis/dissertation must be in accordance with that legislation and must be properly acknowledged. Further distribution or reproduction in any format is prohibited without the permission of the copyright holder. Abstract This thesis is concerned with the monastic rules that were written in seventh century Iberia and the relationship that existed between them and their intended, contemporary, audience. It aims to investigate this relationship from three distinct, yet related, perspectives: physical, literary and philological. After establishing the historical and historiographical background of the texts, the thesis investigates firstly the presence of a monastic rule as a physical text and its role in a monastery and its relationship with issues of early medieval literacy. It then turns to look at the use of literary techniques and structures in the texts and their relationship with literary culture more generally at the time. Finally, the thesis turns to issues of the language that the monastic rules were written in and the relationship between the spoken and written registers not only of their authors, but also of their audiences.
    [Show full text]
  • Chapter 1 Introduction
    Chapter Intro duction A language is a systematic means of communicating ideas or feelings among people by the use of conventionalized signs In contrast a programming lan guage can be thought of as a syntactic formalism which provides ameans for the communication of computations among p eople and abstract machines Elements of a programming language are often called programs They are formed according to formal rules which dene the relations between the var ious comp onents of the language Examples of programming languages are conventional languages likePascal or C and also the more the oretical languages such as the calculus or CCS A programming language can b e interpreted on the basis of our intuitive con cept of computation However an informal and vague interpretation of a pro gramming language may cause inconsistency and ambiguity As a consequence dierent implementations maybegiven for the same language p ossibly leading to dierent sets of computations for the same program Had the language in terpretation b een dened in a formal way the implementation could b e proved or disproved correct There are dierent reasons why a formal interpretation of a programming language is desirable to give programmers unambiguous and p erhaps informative answers ab out the language in order to write correct programs to give implementers a precise denition of the language and to develop an abstract but intuitive mo del of the language in order to reason ab out programs and to aid program development from sp ecications Mathematics often emphasizes
    [Show full text]
  • Aspects of Language
    Aspects of Language CONTENTS CHAPTER 1 : Definitions CHAPTER 2 : Origin CHAPTER 3 : Grammar CHAPTER 4 : Usage and meaning CHAPTER 5 : Philosophy of language CHAPTER 6 : Mind and language CHAPTER 7 : Programming language CHAPTER 8 : Derivation and definitions CHAPTER 9 : Ambiguity CHAPTER 10 : Linguistics CHAPTER 11 : Modern theories CHAPTER 12 : Sign language CHAPTER 1 Language Language is the human capacity for acquiring and using complex systems of communication, and a language is any specific example of such a system. The scientific study of language is called linguistics. Estimates of the number of languages in the world vary between 6,000 and 7,000. However, any precise estimate depends on a partly arbitrary distinction between languages and dialects. Natural languages are spoken or signed, but any language can be encoded into secondary media using auditory, visual, or tactile stimuli, for example, in graphic writing, braille, or whistling. This is because human language is modality-independent. When used as a general concept, "language" may refer to the cognitive ability to learn and use systems of complex communication, or to describe the set of rules that makes up these systems, or the set of utterances that can be produced from those rules. All languages rely on the process of semiosis to relate signs with particular meanings. Oral and sign languages contain a phonological system that governs how symbols are used to form sequences known as words or morphemes, and a syntactic system that governs how words and morphemes are combined to form phrases and utterances. Human language has the properties of productivity, recursivity, and displacement, and it relies entirely on social convention and learning.
    [Show full text]
  • Concepts of Programming Languages, Eleventh Edition, Global Edition
    GLOBAL EDITION Concepts of Programming Languages ELEVENTH EDITION Robert W. Sebesta digital resources for students Your new textbook provides 12-month access to digital resources that may include VideoNotes (step-by-step video tutorials on programming concepts), source code, web chapters, quizzes, and more. Refer to the preface in the textbook for a detailed list of resources. Follow the instructions below to register for the Companion Website for Robert Sebesta’s Concepts of Programming Languages, Eleventh Edition, Global Edition. 1. Go to www.pearsonglobaleditions.com/Sebesta 2. Click Companion Website 3. Click Register and follow the on-screen instructions to create a login name and password Use a coin to scratch off the coating and reveal your access code. Do not use a sharp knife or other sharp object as it may damage the code. Use the login name and password you created during registration to start using the digital resources that accompany your textbook. IMPORTANT: This access code can only be used once. This subscription is valid for 12 months upon activation and is not transferable. If the access code has already been revealed it may no longer be valid. For technical support go to http://247pearsoned.custhelp.com This page intentionally left blank CONCEPTS OF PROGRAMMING LANGUAGES ELEVENTH EDITION GLOBAL EDITION This page intentionally left blank CONCEPTS OF PROGRAMMING LANGUAGES ELEVENTH EDITION GLOBAL EDITION ROBERT W. SEBESTA University of Colorado at Colorado Springs Global Edition contributions by Soumen Mukherjee RCC Institute
    [Show full text]
  • Concurrent Structures in Game Semantics Simon Castellan
    Concurrent structures in game semantics Simon Castellan To cite this version: Simon Castellan. Concurrent structures in game semantics. Logic in Computer Science [cs.LO]. Université de Lyon, 2017. English. NNT : 2017LYSEN034. tel-01587718 HAL Id: tel-01587718 https://tel.archives-ouvertes.fr/tel-01587718 Submitted on 14 Sep 2017 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Numéro National de Thèse: 2017LYSENO34. THÈSE DE DOCTORAT DE L’UNIVERSTÉ DE LYON opérée par l’École Normale Supérieure de Lyon École doctorale: 512 École doctorale en Informatique et Mathématiques de Lyon Spécialité de doctorat : Informatique Discipline : Informatique fondamentale Soutenue publiquement le 13/07/2017, par: Simon Castellan Structures concurrentes en sémantique des jeux Devant le jury composé de: Hyland, Martin Professor at the University of Cambridge Rapporteur Dal Lago, Ugo Professore Associoto all’Università di Bologna Rapporteur Alglave, Jade Senior Lecturer at University College London Examinatrice Curien, Pierre-Louis Directeur de Rercherche à l’Université Paris VII Examinateur Winskel, Glynn Professor at the University of Cambridge Examinateur Yoshida, Nobuko Professor at Imperial College London Examinatrice Laurent, Olivier Directeur de Recherche à l’ENS de Lyon Directeur de thèse Clairambault, Pierre Chargé de Recherche à l’ENS de Lyon Co-Encadrant 1 2 Remerciements et autres acknowledgements Mais, vous savez, moi je ne crois pas qu’il y ait de bonne ou de mauvaise situation.
    [Show full text]
  • Axiomatic Semantics Review
    • Still need volunteers to teach – BDDs – SAT-solvers Axiomatic Semantics – SAT-based decision procedures – Temporal logic (and maybe other modal logics) – ESC/Java • Please let me know soon Automated Deduction - George Necula - Lecture 2 1 Automated Deduction - George Necula - Lecture 2 2 Review - Operational Semantics More Semantics • We have an imperative language with pointers and • There is also denotational semantics function calls – Each program has a meaning in the form of a mathematical object – Compositional • We have defined the semantics of the language – More complex formalism • e.g. what are appropriate meanings ? • Operational semantics – Relatively simple • Neither is good for arguing program correctness – Not compositional (due to loops and recursive calls) – Operational semantics requires running the code – Adequate guide for an implementation – Denotational semantics requires complex calculations • We do instead: Programs → Theorems → Proofs Automated Deduction - George Necula - Lecture 2 3 Automated Deduction - George Necula - Lecture 2 4 Programs →→→ Theorems. Axiomatic Semantics Partial Correctness Assertions • Consists of: • The assertions we make about programs are of the – A language for making assertions about programs form: – Rules for establishing when assertions hold {A} c {B } with the meaning that: • Typical assertions: – Whenever we start the execution of c in a state that – During the execution, only non-null pointers are dereferenced satisfies A, the program either does not terminate or it – This program
    [Show full text]
  • Unifying Semantics for Programming and Verification
    Unifying Semantics for Programming and Verification Sergey Goncharov April 28, 2018 Contents 1 Unifying Semantics: Methodology2 1.1 General View of Semantics...........................2 1.1.1 Denotational vs. Operational Semantics...............3 1.1.2 Denotational vs. Axiomatic Semantics................5 1.2 Towards Categorical Semantics........................6 1.2.1 Algebraic vs. Domain Semantics...................6 1.2.2 Domains and Universes........................7 1.2.3 Extensional Monads..........................8 1.2.4 Intensional Coalgebras.........................9 1.2.5 Extensional Collapse.......................... 10 1.2.6 Unifying Semantics........................... 11 2 Unifying Semantics: Worked Scenarios 12 2.1 Coalgebraic Machines and Process Algebra................. 12 2.1.1 Generic Observations and Coalgebraic Chomsky Hierarchy... 12 2.1.2 Coalgebraic Weak Bisimulation.................... 16 2.2 Monad-Based Program Logics......................... 17 2.2.1 Hoare Logic for Order-Enriched Effects............... 17 2.2.2 Calculi for Asynchronous Side-Effecting Processes......... 21 2.3 Guarded and Unguarded Iteration...................... 23 2.3.1 Unguarded Recursion via Complete Elgot Monads........ 23 2.3.2 Unifying Guarded and Unguarded Iteration............ 26 2.3.3 Monads for Iteration vs. Algebras for Iteration........... 30 2.4 Effect Combination............................... 31 3 Auhtor's Publications 33 4 References 34 1 1 Unifying Semantics: Methodology Correct well-designed semantics precedes solutions of principal research problems in computer science. As a somewhat allusive, but spectacular illustration of this motto we may view the seminal work of Turing [110], which arguably gave rise to computer science as a separate discipline not entirely reducible to pure mathematics. In his famous result of undecidability of the halting problem for what then became known as the Turing machine he made two essential steps to achieve the goal: 1.
    [Show full text]
  • Formalization of the Data Flow Diagram Rules for Consistency Check
    International Journal of Software Engineering & Applications (IJSEA), Vol.1, No.4, October 2010 FORMALIZATION OF THE DATA FLOW DIAGRAM RULES FOR CONSISTENCY CHECK Rosziati Ibrahim and Siow Yen Yen Department of Software Engineering, Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia (UTHM), Parit Raja, 86400, Batu Pahat, Johor Malaysia [email protected] [email protected] ABSTRACT In system development life cycle (SDLC), a system model can be developed using Data Flow Diagram (DFD). DFD is graphical diagrams for specifying, constructing and visualizing the model of a system. DFD is used in defining the requirements in a graphical view. In this paper, we focus on DFD and its rules for drawing and defining the diagrams. We then formalize these rules and develop the tool based on the formalized rules. The formalized rules for consistency check between the diagrams are used in developing the tool. This is to ensure the syntax for drawing the diagrams is correct and strictly followed. The tool automates the process of manual consistency check between data flow diagrams. KEYWORDS Consistency Check, Context Diagram, Data Flow Diagram, Formal Method 1. INTRODUCTION System development life cycle (SDLC) is an essential process uses during the development of any system. SDLC consists of four main phases. They are planning, analysis, design and implementation. During analysis phase, context diagram and data flow diagrams are used to produce the process model of a system. A consistency of the context diagram to lower-level data flow diagrams is very important in smoothing up developing the process model of a system.
    [Show full text]