Long gone are the days when program veri?cation was a task carried out merely by hand with paper and pen. For one, we are increasingly interested in proving actual program artifacts, not … Mehr…
Long gone are the days when program veri?cation was a task carried out merely by hand with paper and pen. For one, we are increasingly interested in proving actual program artifacts, not just abstractions thereof or core algorithms. The programs we want to verify today are thus longer, including whole classes and modules. As we consider larger programs, the number of cases to be considered in a proof increases. The creative and insightful parts of a proof can easily be lost in scores of mundane cases. Another problem with paper-and-pen proofs is that the features of the programming languages we employ in these programs are plentiful, including object-oriented organizations of data, facilities for specifying di?erent c- trol ?ow for rare situations, constructs for iterating over the elements of a collection, and the grouping together of operations into atomic transactions. These language features were designed to facilitate simpler and more natural encodings of programs, and ideally they are accompanied by simpler proof rules. But the variety and increased number of these features make it harder to remember all that needs to be proved about their uses. As a third problem, we have come to expect a higher degree of rigor from our proofs. A proof carried out or replayed by a machine somehow gets more credibility than one that requires human intellect to understand. Books > Computer Science eBook, Springer Shop<
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Long gone are the days when program veri?cation was a task carried out merely by hand with paper and pen. For one, we are increasingly interested in proving actual program artifacts, not … Mehr…
Long gone are the days when program veri?cation was a task carried out merely by hand with paper and pen. For one, we are increasingly interested in proving actual program artifacts, not just abstractions thereof or core algorithms. The programs we want to verify today are thus longer, including whole classes and modules. As we consider larger programs, the number of cases to be considered in a proof increases. The creative and insightful parts of a proof can easily be lost in scores of mundane cases. Another problem with paper-and-pen proofs is that the features of the programming languages we employ in these programs are plentiful, including object-oriented organizations of data, facilities for specifying di?erent c- trol ?ow for rare situations, constructs for iterating over the elements of a collection, and the grouping together of operations into atomic transactions. These language features were designed to facilitate simpler and more natural encodings of programs, and ideally they are accompanied by simpler proof rules. But the variety and increased number of these features make it harder to remember all that needs to be proved about their uses. As a third problem, we have come to expect a higher degree of rigor from our proofs. A proof carried out or replayed by a machine somehow gets more credibility than one that requires human intellect to understand., Springer<
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Nr. 978-3-540-69061-0. Versandkosten:Worldwide free shipping, , plus shipping costs. (EUR 0.00) Details...
(*) Derzeit vergriffen bedeutet, dass dieser Titel momentan auf keiner der angeschlossenen Plattform verfügbar ist.
Long gone are the days when program veri?cation was a task carried out merely by hand with paper and pen. For one, we are increasingly interested in proving actual program artifacts, not … Mehr…
Long gone are the days when program veri?cation was a task carried out merely by hand with paper and pen. For one, we are increasingly interested in proving actual program artifacts, not just abstractions thereof or core algorithms. The programs we want to verify today are thus longer, including whole classes and modules. As we consider larger programs, the number of cases to be considered in a proof increases. The creative and insightful parts of a proof can easily be lost in scores of mundane cases. Another problem with paper-and-pen proofs is that the features of the programming languages we employ in these programs are plentiful, including object-oriented organizations of data, facilities for specifying di?erent c- trol ?ow for rare situations, constructs for iterating over the elements of a collection, and the grouping together of operations into atomic transactions. These language features were designed to facilitate simpler and more natural encodings of programs, and ideally they are accompanied by simpler proof rules. But the variety and increased number of these features make it harder to remember all that needs to be proved about their uses. As a third problem, we have come to expect a higher degree of rigor from our proofs. A proof carried out or replayed by a machine somehow gets more credibility than one that requires human intellect to understand. Books > Computer Science eBook, Springer Shop<
new in stock. Versandkosten:zzgl. Versandkosten. (EUR 0.00)
Long gone are the days when program veri?cation was a task carried out merely by hand with paper and pen. For one, we are increasingly interested in proving actual program artifacts, not … Mehr…
Long gone are the days when program veri?cation was a task carried out merely by hand with paper and pen. For one, we are increasingly interested in proving actual program artifacts, not just abstractions thereof or core algorithms. The programs we want to verify today are thus longer, including whole classes and modules. As we consider larger programs, the number of cases to be considered in a proof increases. The creative and insightful parts of a proof can easily be lost in scores of mundane cases. Another problem with paper-and-pen proofs is that the features of the programming languages we employ in these programs are plentiful, including object-oriented organizations of data, facilities for specifying di?erent c- trol ?ow for rare situations, constructs for iterating over the elements of a collection, and the grouping together of operations into atomic transactions. These language features were designed to facilitate simpler and more natural encodings of programs, and ideally they are accompanied by simpler proof rules. But the variety and increased number of these features make it harder to remember all that needs to be proved about their uses. As a third problem, we have come to expect a higher degree of rigor from our proofs. A proof carried out or replayed by a machine somehow gets more credibility than one that requires human intellect to understand., Springer<
Nr. 978-3-540-69061-0. Versandkosten:Worldwide free shipping, , plus shipping costs. (EUR 0.00)
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Detailangaben zum Buch - Verification of Object-Oriented Software. The KeY Approach
EAN (ISBN-13): 9783540690610 ISBN (ISBN-10): 3540690611 Erscheinungsjahr: 2007 Herausgeber: Springer Berlin Heidelberg 29 Seiten Sprache: eng/Englisch
Buch in der Datenbank seit 2010-01-17T22:25:45+01:00 (Zurich) Detailseite zuletzt geändert am 2023-09-18T00:58:50+02:00 (Zurich) ISBN/EAN: 9783540690610
ISBN - alternative Schreibweisen: 3-540-69061-1, 978-3-540-69061-0 Alternative Schreibweisen und verwandte Suchbegriffe: Autor des Buches: peter becker, bernhard beck, beckert, peter hahn, seymour bernstein, schmitt peter Titel des Buches: object oriented object oriented, key, software
Daten vom Verlag:
Autor/in: Bernhard Beckert Titel: Lecture Notes in Artificial Intelligence; Lecture Notes in Computer Science; Verification of Object-Oriented Software. The KeY Approach - Foreword by K. Rustan M. Leino Verlag: Springer; Springer Berlin 658 Seiten Erscheinungsjahr: 2007-04-21 Berlin; Heidelberg; DE Sprache: Englisch 99,00 € (DE)
EA; E107; eBook; Nonbooks, PBS / Informatik, EDV/Informatik; Künstliche Intelligenz; Verstehen; AI logics; JML; Java; Java Card; OCL; deductive verification; formal methods; formal reasoning; logic reasoning; natural language generation; object-oriented software; program verification; proof obligations; software security; specification languages; systems modeling; theorem proving; C; Artificial Intelligence; Computer Science Logic and Foundations of Programming; Formal Languages and Automata Theory; Compilers and Interpreters; Software Engineering; Computer Science; Theoretische Informatik; Compiler und Übersetzer; Software Engineering; BC
A New Look at Formal Methods for Software Construction.- A New Look at Formal Methods for Software Construction.- I: Foundations.- First-Order Logic.- Dynamic Logic.- Construction of Proofs.- II: Expressing and Formalising Requirements.- Formal Specification.- Pattern-Driven Formal Specification.- Natural Language Specifications.- Proof Obligations.- From Sequential Java to Java Card.- III: Using the KeY System.- Using KeY.- Proving by Induction.- Java Integers.- Proof Reuse.- IV: Case Studies.- The Demoney Case Study.- The Schorr-Waite-Algorithm.- Appendices.- Predefined Operators in Java Card DL.- The KeY Syntax.
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