Results 331 to 340 of about 44,292,339 (363)
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Acta Informatica, 2006
The use of abstraction in the context of abstract data types, is investigated. Properties to be checked are formulas in a first order logic under Kleene's 3-valued interpretation. Abstractions are defined as pairs consisting of a congruence and a predicate interpretation. Three types of abstractions are considered,??, ?? and ?0,1?, and for each of them
Ţiplea, Ferucio Laurenţiu +1 more
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The use of abstraction in the context of abstract data types, is investigated. Properties to be checked are formulas in a first order logic under Kleene's 3-valued interpretation. Abstractions are defined as pairs consisting of a congruence and a predicate interpretation. Three types of abstractions are considered,??, ?? and ?0,1?, and for each of them
Ţiplea, Ferucio Laurenţiu +1 more
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Data types, parameters and type checking
Proceedings of the 7th ACM SIGPLAN-SIGACT symposium on Principles of programming languages - POPL '80, 1980In statically typed programming languages, each variable and expression in a program is assigned a unique "type" and the program is checked to ensure that the arguments in each application are "type-compatible" with the corresponding parameters. The rules by which this "type-checking" is performed must be carefully considered for modern languages that ...
James E. Donahue, Alan Demers
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2010
The most important part of a visualization of data is the data themselves. If it does not show the data clearly, a visualization can be pretty, interesting, technically well executed, and all kinds of other good things, but it fails in its basic task. In this chapter we will look at data, and time-based data in particular, with a view to understanding ...
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The most important part of a visualization of data is the data themselves. If it does not show the data clearly, a visualization can be pretty, interesting, technically well executed, and all kinds of other good things, but it fails in its basic task. In this chapter we will look at data, and time-based data in particular, with a view to understanding ...
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ACM SIGAPL APL Quote Quad, 1989
This paper describes a form of data typing implemented in APL. By contrast with conventional data typing, which basically specifies a storage format for a data type, it is a means of specifying the set of logical values that a variable is to be permitted to take. To assign a data type, a new copula analogous to value-assign is used. Hence only a single
H. Gharib, D. Livingstone
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This paper describes a form of data typing implemented in APL. By contrast with conventional data typing, which basically specifies a storage format for a data type, it is a means of specifying the set of logical values that a variable is to be permitted to take. To assign a data type, a new copula analogous to value-assign is used. Hence only a single
H. Gharib, D. Livingstone
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2004
In the previous chapter, we discussed how to location-enable application data and how to organize geographic data into multiple tables, each containing SDO_GEOMETRY columns. In this chapter, we focus on storing and modeling different types of location information using the SDO_GEOMETRY data type in Oracle. The SDO_GEOMETRY type can store a wide variety
Euro Beinat +2 more
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In the previous chapter, we discussed how to location-enable application data and how to organize geographic data into multiple tables, each containing SDO_GEOMETRY columns. In this chapter, we focus on storing and modeling different types of location information using the SDO_GEOMETRY data type in Oracle. The SDO_GEOMETRY type can store a wide variety
Euro Beinat +2 more
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, 2012
Copyright is retained by the first or sole author, who grants right of first publication to the Practical Assessment, Research & Evaluation. Permission is granted to distribute this article for nonprofit, educational purposes if it is copied in its ...
A. Gadermann, M. Guhn, B. Zumbo
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Copyright is retained by the first or sole author, who grants right of first publication to the Practical Assessment, Research & Evaluation. Permission is granted to distribute this article for nonprofit, educational purposes if it is copied in its ...
A. Gadermann, M. Guhn, B. Zumbo
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2016
While it is tempting to proceed immediately to analysis and model-building, it is critically important to spend time to fully understand the dataset. Different types of data (nominal, ordinal, interval, and ratio) are suitable for only specific types of analysis.
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While it is tempting to proceed immediately to analysis and model-building, it is critically important to spend time to fully understand the dataset. Different types of data (nominal, ordinal, interval, and ratio) are suitable for only specific types of analysis.
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Data Types and Operators [PDF]
, 2001 In Part One of this book, we covered strategic issues relating to the.NET Framework—what it is and where it fits into both Microsoft’s world and yours. In Part Two, we covered key concepts—those language-related ideas that must be understood lest old habits lead one to seriously flawed architectural decisions.
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1993
Active knowledge of Maple data types is quite often needed even when using Maple interactively as a symbolic calculator. Recall the elementary data types polynom and ratpoly, and the simplification and manipulation of such expressions. This chapter will introduce you to composite data types like sequence, set, list, Array, (r)table, Record, and ...
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Active knowledge of Maple data types is quite often needed even when using Maple interactively as a symbolic calculator. Recall the elementary data types polynom and ratpoly, and the simplification and manipulation of such expressions. This chapter will introduce you to composite data types like sequence, set, list, Array, (r)table, Record, and ...
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2019
Julia natively provides a fairly complete and hierarchically organized set of predefined types (especially the numerical ones). These are either scalar—like integers, floating-point numbers, and chars,—or container-like structures able to hold other objects—like multidimensional arrays, dictionaries, sets, etc.
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Julia natively provides a fairly complete and hierarchically organized set of predefined types (especially the numerical ones). These are either scalar—like integers, floating-point numbers, and chars,—or container-like structures able to hold other objects—like multidimensional arrays, dictionaries, sets, etc.
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