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Algirdas Avizienis

Bio: Algirdas Avizienis is an academic researcher from Vytautas Magnus University. The author has contributed to research in topics: Fault tolerance & Software fault tolerance. The author has an hindex of 26, co-authored 64 publications receiving 14436 citations. Previous affiliations of Algirdas Avizienis include California Institute of Technology & University of California, Berkeley.


Papers
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Journal ArticleDOI
TL;DR: The aim is to explicate a set of general concepts, of relevance across a wide range of situations and, therefore, helping communication and cooperation among a number of scientific and technical communities, including ones that are concentrating on particular types of system, of system failures, or of causes of systems failures.
Abstract: This paper gives the main definitions relating to dependability, a generic concept including a special case of such attributes as reliability, availability, safety, integrity, maintainability, etc. Security brings in concerns for confidentiality, in addition to availability and integrity. Basic definitions are given first. They are then commented upon, and supplemented by additional definitions, which address the threats to dependability and security (faults, errors, failures), their attributes, and the means for their achievement (fault prevention, fault tolerance, fault removal, fault forecasting). The aim is to explicate a set of general concepts, of relevance across a wide range of situations and, therefore, helping communication and cooperation among a number of scientific and technical communities, including ones that are concentrating on particular types of system, of system failures, or of causes of system failures.

4,695 citations

01 Jan 2007
TL;DR: In this paper, the main definitions relating to dependability, a generic concept including a special case of such attributes as reliability, availability, safety, integrity, maintainability, etc.
Abstract: This paper gives the main definitions relating to dependability, a generic concept including a special case of such attributes as reliability, availability, safety, integrity, maintainability, etc. Security brings in concerns for confidentiality, in addition to availability and integrity. Basic definitions are given first. They are then commented upon, and supplemented by additional definitions, which address the threats to dependability and security (faults, errors, failures), their attributes, and the means for their achievement (fault prevention, fault tolerance, fault removal, fault forecasting). The aim is to explicate a set of general concepts, of relevance across a wide range of situations and, therefore, helping communication and cooperation among a number of scientific and technical communities, including ones that are concentrating on particular types of system, of system failures, or of causes of system failures.

4,335 citations

Journal ArticleDOI
TL;DR: Sign-digit representations limit carry-propagation to one position to the left during the operations of addition and subtraction in digital computers and arithmetic operations with signed-digit numbers: addition, subtraction, multiplication, division and roundoff are discussed.
Abstract: This paper describes a class of number representations which are called signed-digit representations. Signed-digit representations limit carry-propagation to one position to the left during the operations of addition and subtraction in digital computers. Carry-propagation chains are eliminated by the use of redundant representations for the operands. Redundancy in the number representation allows a method of fast addition and subtraction in which each sum (or difference) digit is the function only of the digits in two adjacent digital positions of the operands. The addition time for signed-digit numbers of any length is equal to the addition time for two digits. The paper discusses the properties of signed-digit representations and arithmetic operations with signed-digit numbers: addition, subtraction, multiplication, division and roundoff. A brief discussion of logical design problems for a signed-digit adder concludes the presentation.

1,232 citations

Journal ArticleDOI
TL;DR: Principal requirements for the implementation of N-version software are summarized and the DEDIX distributed supervisor and testbed for the execution of N -version software is described.
Abstract: Evolution of the N-version software approach to the tolerance of design faults is reviewed. Principal requirements for the implementation of N-version software are summarized and the DEDIX distributed supervisor and testbed for the execution of N-version software is described. Goals of current research are presented and some potential benefits of the N-version approach are identified.

1,093 citations

01 Jan 2000
TL;DR: The Origins and Integration of the Concepts Critical Applications was held in 1989 fostered the interaction of the dependability and security communities, and advanced the integration of security into the framework of dependable computing.
Abstract: 1 Origins and Integration of the Concepts Critical Applications was held in 1989 This and the six working conferences that followed fostered the interaction of the dependability and security communities, and advanced the integration of security (confidentiality, integrity and availability) into the framework of dependable computing [22] A summary of [22] is presented next The concept of dependable computing first appears in the 1830’s in the context of Babbage’s Calculating Engine [1,2] The first generation of electronic computers (late 1940’s to mid-50’s) used rather unreliable components, therefore practical techniques were employed to improve their reliability, such as error control codes, duplexing with comparison, triplication with voting, diagnostics to locate failed components, etc [3-5] 2 The Principal Concepts: a Summary

765 citations


Cited by
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Journal ArticleDOI
TL;DR: Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis.
Abstract: Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

13,246 citations

Journal ArticleDOI
TL;DR: The aim is to explicate a set of general concepts, of relevance across a wide range of situations and, therefore, helping communication and cooperation among a number of scientific and technical communities, including ones that are concentrating on particular types of system, of system failures, or of causes of systems failures.
Abstract: This paper gives the main definitions relating to dependability, a generic concept including a special case of such attributes as reliability, availability, safety, integrity, maintainability, etc. Security brings in concerns for confidentiality, in addition to availability and integrity. Basic definitions are given first. They are then commented upon, and supplemented by additional definitions, which address the threats to dependability and security (faults, errors, failures), their attributes, and the means for their achievement (fault prevention, fault tolerance, fault removal, fault forecasting). The aim is to explicate a set of general concepts, of relevance across a wide range of situations and, therefore, helping communication and cooperation among a number of scientific and technical communities, including ones that are concentrating on particular types of system, of system failures, or of causes of system failures.

4,695 citations

01 Jan 2007
TL;DR: In this paper, the main definitions relating to dependability, a generic concept including a special case of such attributes as reliability, availability, safety, integrity, maintainability, etc.
Abstract: This paper gives the main definitions relating to dependability, a generic concept including a special case of such attributes as reliability, availability, safety, integrity, maintainability, etc. Security brings in concerns for confidentiality, in addition to availability and integrity. Basic definitions are given first. They are then commented upon, and supplemented by additional definitions, which address the threats to dependability and security (faults, errors, failures), their attributes, and the means for their achievement (fault prevention, fault tolerance, fault removal, fault forecasting). The aim is to explicate a set of general concepts, of relevance across a wide range of situations and, therefore, helping communication and cooperation among a number of scientific and technical communities, including ones that are concentrating on particular types of system, of system failures, or of causes of system failures.

4,335 citations

Journal ArticleDOI
TL;DR: The state machine approach is a general method for implementing fault-tolerant services in distributed systems and protocols for two different failure models—Byzantine and fail stop are described.
Abstract: The state machine approach is a general method for implementing fault-tolerant services in distributed systems. This paper reviews the approach and describes protocols for two different failure models—Byzantine and fail stop. Systems reconfiguration techniques for removing faulty components and integrating repaired components are also discussed.

2,559 citations

01 Jan 1978
TL;DR: This ebook is the first authorized digital version of Kernighan and Ritchie's 1988 classic, The C Programming Language (2nd Ed.), and is a "must-have" reference for every serious programmer's digital library.
Abstract: This ebook is the first authorized digital version of Kernighan and Ritchie's 1988 classic, The C Programming Language (2nd Ed.). One of the best-selling programming books published in the last fifty years, "K&R" has been called everything from the "bible" to "a landmark in computer science" and it has influenced generations of programmers. Available now for all leading ebook platforms, this concise and beautifully written text is a "must-have" reference for every serious programmers digital library. As modestly described by the authors in the Preface to the First Edition, this "is not an introductory programming manual; it assumes some familiarity with basic programming concepts like variables, assignment statements, loops, and functions. Nonetheless, a novice programmer should be able to read along and pick up the language, although access to a more knowledgeable colleague will help."

2,120 citations