Advanced Techniques Integration into Efficient Scientific Software (Softcover Reprint of the Origi) (Paperback Bog) [Softcover Reprint of the Original 1st Ed. 1991 edition] (1991) (2024)

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Description for Sales People:This ESPRIT project integrates formal proof techniques and abstraction mechanisms within a common framework to create an environment for scientific software design. It focuses upon recent developments concerning abstraction of data types, data base management, specification and program verification. Table of Contents:1 Introduction.- 1.1 Abstract data types, Proof techniques.- 1.2 Motivation.- 1.3 Organization of the book.- 1.4 Acknowledgements.- 2 State of the Art.- 2.1 Abstract specification and programming languages.- 2.1.1 The AFFIRM progamming environment.- 2.1.2 The GYPSY programming environment.- 2.1.3 The Stanford Pascal Verifier.- 2.1.4 The IOTA programming environment.- 2.1.5 The Alphard programming language.- 2.1.6 Summary.- 2.2 Proof systems.- 2.2.1 The LCF proof system.- 2.2.2 The Boyer-Moore theorem prover.- 2.2.3 The Illinois theorem prover.- 2.2.4 Plaisted s theorem prover.- 2.2.5 The SPADE proof system.- 2.2.6 Final remarks.- 2.3 Conclusions.- 2.4 References.- 3 The Programming Language.- 3.1 General presentation.- 3.1.1 Overview.- 3.1.2 Characteristic properties.- 3.1.3 Notations.- 3.2 Types and operators.- 3.2.1 Objects and types.- 3.2.2 Operator specification.- 3.2.3 Operator chapter.- 3.3 Constructions and algorithms.- 3.3.1 Abstract context.- 3.3.2 Constructions.- 3.3.3 Algorithms.- 3.3.4 Algorithm chapter.- 3.4 Structures and modules.- 3.4.1 Concrete context.- 3.4.2 Structures.- 3.4.3 Modules.- 3.4.4 Module chapter.- 3.5 Development with ATES.- 3.5.1 Books.- 3.5.2 Chapters.- 3.5.3 Actions on a book.- 3.5.4 Debugging.- 3.6 Advanced features.- 3.6.1 Genericity.- 3.6.2 Special operators.- 4 The Applications within the ATES Project.- 4.1 Introduction.- 4.2 The first application.- 4.2.1 Problem description.- 4.2.2 Formulation.- 4.2.3 The finite element method: theoretical overview.- 4.2.4 The finite element method: implementation overview.- 4.2.5 The F. E. M. model.- 4.2.6 Results validation.- 4.3 The second application.- 4.3.1 3-D extension of the library.- 4.3.2 3-D mesh generation.- 4.3.3 The Delaunay triangulation.- 4.3.4 Boundary conformity problems.- 4.3.5 General chart.- 4.3.6 Some applications.- 4.4 Performance considerations.- 4.4.1 Performances and ATES system.- 4.4.2 IO aspect.- 4.4.3 Memory aspect.- 4.4.4 CPU Aspect.- 4.4.5 CPU: A performance test.- 4.5 References.- 5 The Specification and Proof Language.- 5.1 Basic mathematical elements for proof.- 5.1.1 The sets.- 5.1.2 Functions and constants.- 5.1.3 Expressions and predicates.- 5.2 Axioms.- 5.2.1 Definition.- 5.2.2 Syntax.- 5.2.3 Example.- 5.3 Types and Operator specifications.- 5.3.1 Modeling types.- 5.3.2 Definingpre- and post-conditions foroperators.- 5.3.3 Specifying secondary variables.- 5.3.4 Specifications of system-generated operators.- 5.4 Proof elements.- 5.4.1 Loops and invariants.- 5.4.2 Syntax.- 5.4.3 Concrete models.- 5.4.4 Abstraction functions.- 5.4.5 Representation functions.- 6 Proving the Correctness of ATES Programs.- 6.1 Definition of the correctness.- 6.1.1 An operational semantics of ATES operators.- 6.1.2 A first order predicate logic.- 6.1.3 The predicate transformer WP.- 6.2 The interactive proof environment.- 6.2.1 Elements required for proofs.- 6.2.2 Predicate transformation and interactivity.- 6.2.3 The proof system s user interface.- 6.3 Proving the verification conditions.- 6.3.1 Introduction.- 6.3.2 The simplification methods.- 6.3.3 Relations with theorem proving.- 6.4 Example: the 1D heat transfer problem.- 6.4.1 Reading the input.- 6.4.2 Solving the discrete mathematical problem.- 6.4.3 Write result on output.- 6.4.4 The data-structures and their models.- 6.4.5 The actual proof.- 6.5 Conclusions.- 6.6 References.- 7 Extending the Techniques to Parallel Programs.- 7.1 Formal synthesis and verification of concurrent programs.- 7.1.1 Introduction.- 7.1.2 Parallelism within the sequential framework.- 7.1.3 Formal tools for nondeterministic concurrency.- 7.1.4 Development of a data transfer protocol.- 7.2 Validation of the approach in the real-time area.- 7.2.1 Objective.- 7.2.2 Ada features.- 7.2.3 Specifications and proofs.- 7.2.4 Related works.- 7.2.5 A short example.- 7.2.6 Specification and proof with LOTOS.- 7.2.7 Conclusion.- 7.3 References.- 8 Implementation Issues.- 8.1 Generalities.- 8.1.1 Some data about the system.- 8.1.2 Overview of the system organization.- 8.2 The ATES compiler.- 8.2.1 Initialisation.- 8.2.2 The parser.- 8.2.3 Semantic analysis of operators.- 8.2.4 Semantic analysis of algorithms.- 8.2.5 Semantic analysis of modules.- 8.2.6 Code generation.- 8.2.7 Code compilation and execution.- 8.3 The ATES proof system.- 8.3.1 Semantic analysis of axiom chapters.- 8.3.2 Semantic analysis of specification chapters.- 8.3.3 Semantic analysis of proof chapters.- 8.4 The ATES correctness proof system.- 8.4.1 The simplifier.- 8.4.2 The data manager.- 8.4.3 The graphic proof interface.- 8.5 References.- 9 Conclusion.- Appendix A. Formal Specification of the 1D Heat Transfer Problem.- Appendix B. Grammar of the ATES Specification Language.- Appendix C. Grammar of the ATES Source Language."Publisher Marketing:Today, people use a large number of "systems" ranging in complexity from washing machines to international airline reservation systems. Computers are used in nearly all such systems: accuracy and security are becoming increasingly essential. The design of such computer systems should make use of development methods as systematic as those used in other engineering disciplines. A systematic development method must provide a way of writing specifications which are both precise and concise; it must also supply a way of relating design to specification. A concise specification can be achieved by restricting attention to what a system has to do: all considerations of implementation details are postponed. With computer systems, this is done by: 1) building an abstract model of the system -operations being specified by pre-and post-conditions; 2) defining languages by mapping program texts onto some collection of objects modelizing the concepts of the system to be dealt with, whose meaning is understood; 3) defining complex data objects in terms of abstractions known from mathematics. This last topic, the use of abstract data types, pervades all work on specifications and is necessary in order to apply ideas to systems of significant complexity. The use of mathematics based notations is the best way to achieve precision. 1.1 ABSTRACT DATA TYPES, PROOF TECHNIQUES From a practical point of view, a solution to these three problems consists to introduce abstract data types in the programming languages, and to consider formal proof methods.

352 pages, 15 black & white illustrations, biography

Se alt med Armand Puccetti ( f.eks. Paperback Bog )