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  • 1
    Electronic Resource
    Electronic Resource
    s.l. : American Chemical Society
    Langmuir 8 (1992), S. 1666-1670 
    ISSN: 1520-5827
    Source: ACS Legacy Archives
    Topics: Chemistry and Pharmacology
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    s.l. : American Chemical Society
    Langmuir 7 (1991), S. 1274-1280 
    ISSN: 1520-5827
    Source: ACS Legacy Archives
    Topics: Chemistry and Pharmacology
    Type of Medium: Electronic Resource
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  • 3
    Electronic Resource
    Electronic Resource
    s.l. : American Chemical Society
    Journal of the American Chemical Society 111 (1989), S. 3702-3707 
    ISSN: 1520-5126
    Source: ACS Legacy Archives
    Topics: Chemistry and Pharmacology
    Type of Medium: Electronic Resource
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  • 4
    Electronic Resource
    Electronic Resource
    Springer
    Machine learning 3 (1988), S. 45-77 
    ISSN: 0885-6125
    Keywords: Learning by failing to explain ; explanation-based learning ; graph grammar ; design
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract Explanation-based learning depends on having an explanation on which to base generalization. Thus, a system with an incomplete or intractable domain theory cannot use this method to learn from every precedent. However, in such cases the system need not resort to purely empirical generalization methods, because it may already know almost everything required to explain the precedent. Learning by failing to explain is a method that uses current knowledge to prune the well-understood portions of complex precedents (and rules) so that what remains may be conjectured as a new rule. This paper describes precedent analysis, partial explanation of a precedent (or rule) to isolate the new technique(s) it embodies, and rule reanalysis, which involves analyzing old rules in terms of new rules to obtain a more general set. The algorithms PA, PA-RR, and PA-RR-GW implement these ideas in the domains of digital circuit design and simplified gear design.
    Type of Medium: Electronic Resource
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  • 5
    Electronic Resource
    Electronic Resource
    Springer
    Machine learning 3 (1988), S. 45-77 
    ISSN: 0885-6125
    Keywords: Learning by failing to explain ; explanation-based learning ; graph grammar ; design
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract Explanation-based learning depends on having an explanation on which to base generalization. Thus, a system with an incomplete or intractable domain theory cannot use this method to learn from every precedent. However, in such cases the system need not resort to purely empirical generalization methods, because it may already know almost everything required to explain the precedent. Learning by failing to explain is a method that uses current knowledge to prune the well-understood portions of complex precedents (and rules) so that what remains may be conjectured as a new rule. This paper describes precedent analysis, partial explanation of a precedent (or rule) to isolate the new technique(s) it embodies, and rule reanalysis, which involves analyzing old rules in terms of new rules to obtain a more general set. The algorithms PA, PA-RR, and PA-RR-GW implement these ideas in the domains of digital circuit design and simplified gear design.
    Type of Medium: Electronic Resource
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  • 6
    Electronic Resource
    Electronic Resource
    Springer
    Optical and quantum electronics 18 (1986), S. 319-327 
    ISSN: 1572-817X
    Source: Springer Online Journal Archives 1860-2000
    Topics: Electrical Engineering, Measurement and Control Technology , Physics
    Notes: Abstract The effect of finite-bandwidth multimode pump lasers in CARS is normally accounted for by an intensity convolution integral based on gaussian (thermal) pump sources. This paper presents a derivation of the convolution integral for non-gaussian pump sources derived from frequency doubling. The modified convolution integral makes it possible to identify regions of insensitivity to pump stochastic properties.
    Type of Medium: Electronic Resource
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  • 7
    Electronic Resource
    Electronic Resource
    Springer
    Journal of automated reasoning 8 (1992), S. 367-394 
    ISSN: 1573-0670
    Keywords: Limited propositional reasoning ; resolution theorem proving ; bounded resolution ; clause management systems
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract Complete propositional reasoning is impractical as a tool in artificial intelligence, because it is computationally intractable. Most current approaches to limited propositional reasoning cannot easily be adjusted to use more (or less) time to prove more (fewer) theorems when the task requires it. This difficulty can be solved byparameterizing the reasoner: designing in a ‘power dial’ giving the user fine control over cost and performance. System designers face the significant problem of choosing the best parameter scheme to use. This paper proposes an empirical methodology for comparing parameter schemes and illustrates its use in comparing eight such schemes for a given complete, resolution-based propositional reasoner. From the data, a clear choice emerges as the most preferable of the eight.
    Type of Medium: Electronic Resource
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  • 8
    Electronic Resource
    Electronic Resource
    Springer
    Automated software engineering 2 (1995), S. 33-53 
    ISSN: 1573-7535
    Keywords: program slicing ; subsetting ; reuse ; redesign
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract Developers of software product families and maintainers of “legacy” software can benefit from the ability to automatically extract a correctly functioning subset of the code of a system that performs a desired subset of its behaviors. This article introduces a technique for automatic subsetting based on computing asimultaneous dynamic program slice of the code for a set of representative inputs. I show first why the naive approach (unioning traditional dynamic slices) fails, then give an abstract algorithm that succeeds in any slicing framework satisfying certain (mild) assumptions. Experiments using an implementation within the ISAT environment indicate that the algorithm consistently produces significantly smaller subsets than three competing approaches. I also discuss how to characterize the subset's correctness on inputs of interest outside the set used to compute the slice.
    Type of Medium: Electronic Resource
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  • 9
    Electronic Resource
    Electronic Resource
    Springer
    Automated software engineering 2 (1995), S. 131-166 
    ISSN: 1573-7535
    Keywords: validation ; reactive systems ; explanation-based generalization ; ISAT
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract Validating the specification of a reactive system, such as a telephone switching system, traffic controller, or automated network service, is difficult, primarily because it is extremely hard even tostate a set of complete and correct requirements, let alone toprove that a specification satisfies them. In the ISAT project[10], end-user requirements are stated as concrete behavior scenarios, and a multi-functional apprentice system aids the human developer in acquiring and maintaining a specification consistent with the scenarios. ISAT's Validation Assistant (isat-va) embodies a novel, systematic, and incremental approach to validation based on the novel technique ofsound scenario generalization, which automatically states and proves validation lemmas. This technique enablesisat-va to organize the validity proof around a novel knowledge structure, thelibrary of generalized fragments, and provides automated progress tracking and semi-automated help in increasing proof coverage. The approach combines the advantages of software testing and automated theorem proving of formal requirements, avoiding most of their shortcomings, while providing unique advantages of its own.
    Type of Medium: Electronic Resource
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  • 10
    Electronic Resource
    Electronic Resource
    Springer
    Automated software engineering 7 (2000), S. 157-177 
    ISSN: 1573-7535
    Keywords: scenario generation ; reactive system ; validation ; explanation-based generalization
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract Reactive systems control many useful and complex real-world devices. Tool-supported specification modeling helps software engineers design such systems correctly. One such tool, a scenario generator, constructs an input event sequence for the spec model that reaches a state satisfying given criteria. It can uncover counterexamples to desired safety properties, explain feature interactions in concrete terms to requirements analysts, and even provide online help to end users learning how to use a system. However, while exhaustive search algorithms such as model checkers work in limited cases, the problem is highly intractable for the functionally rich models that correspond naturally to complex systems engineers wish to design. This paper describes a novel heuristic approach to the problem that is applicable to a large class of infinite state reactive systems. The key idea is to piece together scenarios that achieve subgoals into a single scenario achieving the conjunction of the subgoals. The scenarios are mined from a library captured independently during requirements acquisition. Explanation-based generalization then abstracts them so they may be coinstantiated and interleaved. The approach is implemented, and I present the results of applying the tool to 63 scenario generation problems arising from a case study of telephony feature validation.
    Type of Medium: Electronic Resource
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