Temporal Logic: the Lesser of Three Evils
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Obituary: Amir Pnueli, 1941–2009 Krzysztof R. Apt and Lenore D. Zuck
Obituary: Amir Pnueli, 1941–2009 Krzysztof R. Apt and Lenore D. Zuck Amir Pnueli was born in Nahalal, Israel, on April 22, 1941 and passed away in New York City on November 2, 2009 as a result of a brain hemorrhage. Amir founded the computer science department in Tel-Aviv University in 1973. In 1981 he joined the department of mathematical sciences at the Weiz- mann Institute of Science, where he spent most of his career and where he held the Estrin family chair. In recent years, Amir was a faculty member at New York University where he was a NYU Silver Professor. Throughout his career, in spite of an impressive list of achievements, Amir remained an extremely modest and selfless researcher. His unique combination of excellence and integrity has set the tone in the large community of researchers working on specification and verification of programs and systems, program semantics and automata theory. Amir was devoid of any arrogance and those who knew him as a young promising researcher were struck how he maintained his modesty throughout his career. Amir has been an active and extremely hard working researcher till the last moment. His sudden death left those who knew him in a state of shock and disbelief. For his achievements Amir received the 1996 ACM Turing Award. The citation reads: “For seminal work introducing temporal logic into computing science and for outstanding contributions to program and system verification.” Amir also received, for his contributions, the 2000 Israel Award in the area of exact sciences. More recently, in 2007, he shared the ACM Software System Award. -
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Nir Piterman, Associate Professor Coordinates Email: fi[email protected] Homepage: www.cs.le.ac.uk/people/np183 Phone: +44-XX-XXXX-XXXX Research Interests My research area is formal verification. I am especially interested in algorithms for model checking and design synthesis. A major part of my work is on the automata-theoretic approach to verification and especially to model checking. I am also working on applications of formal methods to biological modeling. Qualifications Oct. 2000 { Mar. 2005 Ph.D. in the Department of Computer Science and Applied Mathe- matics at the Weizmann Institute of Science, Rehovot, Israel. • Research Area: Formal Verification. • Thesis: Verification of Infinite-State Systems. • Supervisor: Prof. Amir Pnueli. Oct. 1998 { Oct. 2000 M.Sc. in the Department of Computer Science and Applied Mathe- matics at the Weizmann Institute of Science, Rehovot, Israel. • Research Area: Formal Verification. • Thesis: Extending Temporal Logic with !-Automata. • Supervisor: Prof. Amir Pnueli and Prof. Moshe Vardi. Oct. 1994 { June 1997 B.Sc. in Mathematics and Computer Science in the Hebrew Univer- sity, Jerusalem, Israel. Academic Employment Mar. 2019 { Present Senior Lecturer/Associate Professor in the Department of Com- puter Science and Engineering in University of Gothenburg. Oct. 2012 { Feb. 2019 Reader/Associate Professor in the Department of Informatics in University of Leicester. Oct. 2010 { Sep. 2012 Lecturer in the Department of Computer Science in University of Leicester. Aug. 2007 { Sep. 2010 Research Associate in the Department of Computing in Imperial College London. Host: Dr. Michael Huth Oct. 2004 { July 2007 PostDoc in the school of Computer and Communication Sciences at the Ecole Polytechnique F´ed´eralede Lausanne. -
The Best Nurturers in Computer Science Research
The Best Nurturers in Computer Science Research Bharath Kumar M. Y. N. Srikant IISc-CSA-TR-2004-10 http://archive.csa.iisc.ernet.in/TR/2004/10/ Computer Science and Automation Indian Institute of Science, India October 2004 The Best Nurturers in Computer Science Research Bharath Kumar M.∗ Y. N. Srikant† Abstract The paper presents a heuristic for mining nurturers in temporally organized collaboration networks: people who facilitate the growth and success of the young ones. Specifically, this heuristic is applied to the computer science bibliographic data to find the best nurturers in computer science research. The measure of success is parameterized, and the paper demonstrates experiments and results with publication count and citations as success metrics. Rather than just the nurturer’s success, the heuristic captures the influence he has had in the indepen- dent success of the relatively young in the network. These results can hence be a useful resource to graduate students and post-doctoral can- didates. The heuristic is extended to accurately yield ranked nurturers inside a particular time period. Interestingly, there is a recognizable deviation between the rankings of the most successful researchers and the best nurturers, which although is obvious from a social perspective has not been statistically demonstrated. Keywords: Social Network Analysis, Bibliometrics, Temporal Data Mining. 1 Introduction Consider a student Arjun, who has finished his under-graduate degree in Computer Science, and is seeking a PhD degree followed by a successful career in Computer Science research. How does he choose his research advisor? He has the following options with him: 1. Look up the rankings of various universities [1], and apply to any “rea- sonably good” professor in any of the top universities. -
Lecture Notes in Computer Science
D. Dolev Z. Galil M. Rodeh (Eds.) Theory of Computing and Systems ISTCS '92, Israel Symposium Haifa, Israel, May 27-28, 1992 Proceedings Springer-Verlag Berlin Heidelberg NewYork London Paris Tokyo Hong Kong Barcelona Budapest Series Editors Gerhard Goos Juris Hartmanis Universit~it Karlsruhe Department of Computer Science Postfach 69 80 Cornell University Vincenz-Priessnitz-Stral3e 1 5149 Upson Hall W-7500 Karlsruhe, FRG Ithaca, NY 14853, USA Volume Editors Danny Dolev Hebrew University Givat Ram, Jerusalem, Israel Zvi Galil Columbia University, New York, NY 10027, USA and Tel Aviv University Ramat Aviv, Tel Aviv, Israel Michael Rodeh IBM Israel Ltd., Science and Technology, Technion City Haifa 32000, Israel CR Subject Classification (1991): F.1-4, B.3, C.2, G.1-2, 1.1, E.4, D.2-3 ISBN 3-540-55553-6 Springer-Verlag Berlin Heidelberg New York ISBN 0-387-55553-6 Springer-Verlag New York Berlin Heidelberg This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, re-use of illustrations, recitation, broadcasting, reproduction on microfilms or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permission for use must always be obtained from Springer-Verlag. Violations are liable for prosecution under the German Copyright Law. Springer-Verlag Berlin Heidelberg 1992 Printed in Germany Typesetting: Camera ready by author/editor Printing and binding: Druckhaus Beltz, Hemsbach/Bergstr. -
Sooner Is Safer Than Later Department of Computer Science
May 1991 Report No. STAN-CS-91-1360 Sooner is Safer Than Later bY Thomas A. Henzinger Department of Computer Science Stanford University Stanford, California 94305 f- Awwtd REPORT DOCUMENTATION PAGE ma No. 07044188 rt8d to wwq8 I how ou r-. lncllJdlng the ttm8 for nvmwlng tn8uuctl -. wrrtruq 82lsung e8t8 wurcg% Wv*lnQ th8 cOlM(0n Of dormatlon Sand comrrmo I ‘-‘9 th* -om mmate Q arty otwr m ol tha bwdm. to Wnkqtoft ~*dourrtw~ Sewc~. Duator8toT or tnformrt8oe ooer0tm aw v, 121~ - O(cltr of Muwgrmw wbd beget. ?8oemon adato + @~o*olI(i. Woahington. DC 2oSO3. I. AGENCY USE ONLY (Lea- bhd) 2. REPORT DATE 3. REPORT TYPE AND DATES COVERED s/28 p?( I. TITLE AND SulTlTLt 5. FUNDING NUMbERI SomEFz, 15 BIER T&W L-Am 1. PERFORMING ORGANIZATION NAME(S) AND ADDRESS 8. PERFORMING ORGANJZATION REPORT NUMIER jhpx OF- CO~PU’i-ER scii&E STANWD I)tdfhzs’;p/ . 5q-JWFi3RD) CA 9&S I. SPONSORING I’ MONITORING AGENCY NAME(S) AND ADDRESS 10. SPONSORING / MONlTORiNG AGENCY REPORT NUMBER 3ARi’A bJQx39 - 84 c - 020 fd&XW, VA 2220~ I 1. SUPPLEMENTARY NOTES . 12r. DISTRIBUTION / AVAILABILITY STATEMENT lib. DiStRlBUfiON CODE urjL?M:m E. ABSTRACT (Maxrmum 200 words) Abstract. It has been repeatedly observed that the standard safety-liveness classification of properties of reactive systems does not fit for real-time proper- ties. This is because the implicit “liveness” of time shifts the spectrum towards the safety side. While, for example, response - that “something good” will happen, eventually - is a classical liveness property, bounded response - that “something good” will happen soon, within a certain amount of time - has many characteristics of safety. -
Arxiv:2106.11534V1 [Cs.DL] 22 Jun 2021 2 Nanjing University of Science and Technology, Nanjing, China 3 University of Southampton, Southampton, U.K
Noname manuscript No. (will be inserted by the editor) Turing Award elites revisited: patterns of productivity, collaboration, authorship and impact Yinyu Jin1 · Sha Yuan1∗ · Zhou Shao2, 4 · Wendy Hall3 · Jie Tang4 Received: date / Accepted: date Abstract The Turing Award is recognized as the most influential and presti- gious award in the field of computer science(CS). With the rise of the science of science (SciSci), a large amount of bibliographic data has been analyzed in an attempt to understand the hidden mechanism of scientific evolution. These include the analysis of the Nobel Prize, including physics, chemistry, medicine, etc. In this article, we extract and analyze the data of 72 Turing Award lau- reates from the complete bibliographic data, fill the gap in the lack of Turing Award analysis, and discover the development characteristics of computer sci- ence as an independent discipline. First, we show most Turing Award laureates have long-term and high-quality educational backgrounds, and more than 61% of them have a degree in mathematics, which indicates that mathematics has played a significant role in the development of computer science. Secondly, the data shows that not all scholars have high productivity and high h-index; that is, the number of publications and h-index is not the leading indicator for evaluating the Turing Award. Third, the average age of awardees has increased from 40 to around 70 in recent years. This may be because new breakthroughs take longer, and some new technologies need time to prove their influence. Besides, we have also found that in the past ten years, international collabo- ration has experienced explosive growth, showing a new paradigm in the form of collaboration. -
Amir Pnueli University of Pennsylvania, Pa. 191D4 and Tel-Aviv University, Tel Aviv, Israel
THE TEMPORAL LOGIC OF PROGRAMS* Amir Pnueli University of Pennsylvania, Pa. 191D4 and Tel-Aviv University, Tel Aviv, Israel Summary: grams, always considered functional programs only. Those are programs with distinct beginning and end, and A unified approach to program verification is sane canputational instructions in between, whose suggested, which applies to both sequential and statement of correctness consists of the description parallel programs. The main proof method suggested is of the func tion of the input variables c anputed on that of temporal reasoning in which the time depend successful cOOlpletion. This approach canpletely ence of events is the basic concept. Two forma 1 ignored an important class of operating system or systems are presented for providing a basis for tem real time type programs, for which halting is rather poral reasoning. One forms a formalization of the an abnormal situation. Only recently 10,11,19 have method of intermittent assertions, while the other is people begun investigating the concept of correctness an adaptation of the tense logic system Kb, and is for non-terminating cyclic programs. It seems that the notion of temporal implication is the correct one. particularly suitable for reasoning about concurrent Thus, a specification of correctness for an operating programs. system may be that it responds correctly to any incoming request, expressible as: {Request arrival O. Introduction situation }~ System grants request }. Due to increasing maturity in the research on Similar to the unification of correctness basic program verification, and the increasing interest and concepts, there seems to be a unification in the basic understanding of the behavior of concurrent programs, proof methods. -
Alan Mathison Turing and the Turing Award Winners
Alan Turing and the Turing Award Winners A Short Journey Through the History of Computer TítuloScience do capítulo Luis Lamb, 22 June 2012 Slides by Luis C. Lamb Alan Mathison Turing A.M. Turing, 1951 Turing by Stephen Kettle, 2007 by Slides by Luis C. Lamb Assumptions • I assume knowlege of Computing as a Science. • I shall not talk about computing before Turing: Leibniz, Babbage, Boole, Gödel... • I shall not detail theorems or algorithms. • I shall apologize for omissions at the end of this presentation. • Comprehensive information about Turing can be found at http://www.mathcomp.leeds.ac.uk/turing2012/ • The full version of this talk is available upon request. Slides by Luis C. Lamb Alan Mathison Turing § Born 23 June 1912: 2 Warrington Crescent, Maida Vale, London W9 Google maps Slides by Luis C. Lamb Alan Mathison Turing: short biography • 1922: Attends Hazlehurst Preparatory School • ’26: Sherborne School Dorset • ’31: King’s College Cambridge, Maths (graduates in ‘34). • ’35: Elected to Fellowship of King’s College Cambridge • ’36: Publishes “On Computable Numbers, with an Application to the Entscheindungsproblem”, Journal of the London Math. Soc. • ’38: PhD Princeton (viva on 21 June) : “Systems of Logic Based on Ordinals”, supervised by Alonzo Church. • Letter to Philipp Hall: “I hope Hitler will not have invaded England before I come back.” • ’39 Joins Bletchley Park: designs the “Bombe”. • ’40: First Bombes are fully operational • ’41: Breaks the German Naval Enigma. • ’42-44: Several contibutions to war effort on codebreaking; secure speech devices; computing. • ’45: Automatic Computing Engine (ACE) Computer. Slides by Luis C. -
Unification Grammars Nissim Francez and Shuly Wintner Frontmatter More Information
Cambridge University Press 978-1-107-01417-6 - Unification Grammars Nissim Francez and Shuly Wintner Frontmatter More information Unification Grammars Like computer programs, the grammars of natural languages can be expressed as mathematical objects. Such a formal presentation of grammars facilitates mathematical reasoning with grammars (and the languages they denote), on one hand, and the compu- tational implementation of grammar processors, on the other hand. This book presents one of the most commonly used grammatical formalisms, unification grammars, which underlies such contemporary linguistic theories as lexical-functional grammar (LFG) and head-driven phrase structure grammar (HPSG). The book provides a robust and rigorous exposition of the formalism that is both mathematically well founded and lin- guistically motivated. Although the material is presented formally, and much of the text is mathematically oriented, a core chapter of the book addresses linguistic applications and the implementation of several linguistic insights in unification grammars. The authors provide dozens of examples and numerous exercises (many with solutions) to illustrate key points. Graduate students and researchers in both computer science and linguistics will find this book a valuable resource. NISSIM FRANCEZ is professor emeritus of computer science at the Technion-Israel Institute of Technology. His research for the last twenty years has focused on computational linguistics in general, and on the formal semantics of natural language in particular, mainly within the framework of type-logical grammar. His most recent research topic is proof-theoretic semantics for natural language. He is the author of several books and approximately 150 scientific articles. He regularly serves on editorial boards and program committees of several major conferences, including the committee of the FoLLI (Association for Logic, Language, and Information) Beth Dissertation Award. -
COMP 516 Research Methods in Computer Science Research Methods in Computer Science Lecture 3: Who Is Who in Computer Science Research
COMP 516 COMP 516 Research Methods in Computer Science Research Methods in Computer Science Lecture 3: Who is Who in Computer Science Research Dominik Wojtczak Dominik Wojtczak Department of Computer Science University of Liverpool Department of Computer Science University of Liverpool 1 / 24 2 / 24 Prizes and Awards Alan M. Turing (1912-1954) Scientific achievement is often recognised by prizes and awards Conferences often give a best paper award, sometimes also a best “The father of modern computer science” student paper award In 1936 introduced Turing machines, as a thought Example: experiment about limits of mechanical computation ICALP Best Paper Prize (Track A, B, C) (Church-Turing thesis) For the best paper, as judged by the program committee Gives rise to the concept of Turing completeness and Professional organisations also give awards based on varying Turing reducibility criteria In 1939/40, Turing designed an electromechanical machine which Example: helped to break the german Enigma code British Computer Society Roger Needham Award His main contribution was an cryptanalytic machine which used Made annually for a distinguished research contribution in computer logic-based techniques science by a UK based researcher within ten years of their PhD In the 1950 paper ‘Computing machinery and intelligence’ Turing Arguably, the most prestigious award in Computer Science is the introduced an experiment, now called the Turing test A. M. Turing Award 2012 is the Alan Turing year! 3 / 24 4 / 24 Turing Award Turing Award Winners What contribution have the following people made? The A. M. Turing Award is given annually by the Association for Who among them has received the Turing Award? Computing Machinery to an individual selected for contributions of a technical nature made Frances E. -
COS 360 Programming Languages Formal Semantics
COS 360 Programming Languages Formal Semantics Semantics has to do with meaning, and typically the meaning of a complex whole is a function of the meaning of its parts. Just as in an English sentence, we parse a sentence into subject, verb, objects, adjectives(noun qualifiers) and adverbs(verb qualifiers), so with a program we break it up into control structures, statements, expressions, each of which has a meaning. The meanings of the constituents contribute to the meaning of the program as a whole. Another way this is put is to say that the semantics is compositional en.wikipedia.org/wiki/Denotational_semantics#Compositionality Consequently, the grammar of a language guides the exposition of its meaning. Each of the three approaches to formal semantics, axiomatic, operational, and denotational, will use the grammar as a structuring device to explain the meaning. The grammar used, however, is not the same one that the compiler’s parser uses. It eliminates the punctuation and just contains the relevant, meaning carrying pieces and is often ambiguous, but the notion is that the parsing has already taken place and the parse tree simplified to what is referred to as an abstract syntax tree. Learning Objectives 1. to understand the difference between the abstract syntax trees used in expositions of semantics and the concrete syntax trees, or parse trees, used in parsing 2. to understand how the abstract syntax tree contributes to the explanation of program- ming language semantics 3. to understand the three major approaches to programming language semantics: ax- iomatic, operational, and denotational 4. to understand how axiomatic semantics can be used to prove algorithms are correct 5. -
Chp%3A10.1007%2F3-54
PART III PROJECT SUMMARIES 345 Parallel Unification Machine Design and Simulation Contact Person: Professor F~li N. Sibai Dept. of Electrical Engineering University of Akron Akron, OH 44325-3904 U.S.A. mail: r [email protected] Keywords Parallel Unification, Term Matching, Consistency Check, Shared and Distributed Memory Organizations Summary A parallel machine architecture for first-order unification was designed by F. N. Sibai. This machine can be used as a hardware unifier by itself, or can be used as a co-processor to a host PROLOG computer. The machine takes two terms to be unified for input, and outputs the most general unifier in case of unification success, or FAIL in case of failure. The machine is composed of an array of match processors (MPs) in charge of matching the arguments of the two terms in parallel and can therefore detect early failures at the match level. If no match failure exists, the MPs send the generated bindings to a consistency check processor (CCP) in charge of checking the consistency of the bindings. The CCP is a powerful unification processor which maintains the bindings in a content-addressable memory for fast search and retrieval. Thus the operations of the array of MPs and the CCP are pipelined in the machine. The performance evaluation of two versions of PUM has been conducted with simulation. The first version is based on a shared-memory or- ganization whereas the second uses a distributed memory organization. Reference Sibai, Fadi N.,"A Parallel Machine for the Unification Algorithm: Design, Simulation, and Performance Evaluation," Ph.D.