Data abstractions for database systems

Lockemann, Peter C.; Mayr, Heinrich C.; Weil, Wolfgang H.; Wohlleber, Wolfgang H.

doi:10.1145/320064.320067

Cited by 36 publications

(6 citation statements)

References 11 publications

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“…The first uses were focused on organizing data, rather than revealing semantics. Historically, the goal was to build database models that used data abstractions to hide the implementation details from the database user, see Smith and Smith and Smith [ 111 ], Lockemann et al [ 68 ], Cardelli and Wegner [ 15 ], and Goldstein and Storey [ 40 ].…”

Section: A Survey Of Powertypes In Isementioning

confidence: 99%

Formalization of the classification pattern: survey of classification modeling in information systems engineering

et al. 2016

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Formalization is becoming more common in all stages of the development of information systems, as a better understanding of its benefits emerges. Classification systems are ubiquitous, no more so than in domain modeling. The classification pattern that underlies these systems provides a good case study of the move toward formalization in part because it illustrates some of the barriers to formalization, including the formal complexity of the pattern and the ontological issues surrounding the “one and the many.” Powersets are a way of characterizing the (complex) formal structure of the classification pattern, and their formalization has been extensively studied in mathematics since Cantor’s work in the late nineteenth century. One can use this formalization to develop a useful benchmark. There are various communities within information systems engineering (ISE) that are gradually working toward a formalization of the classification pattern. However, for most of these communities, this work is incomplete, in that they have not yet arrived at a solution with the expressiveness of the powerset benchmark. This contrasts with the early smooth adoption of powerset by other information systems communities to, for example, formalize relations. One way of understanding the varying rates of adoption is recognizing that the different communities have different historical baggage. Many conceptual modeling communities emerged from work done on database design, and this creates hurdles to the adoption of the high level of expressiveness of powersets. Another relevant factor is that these communities also often feel, particularly in the case of domain modeling, a responsibility to explain the semantics of whatever formal structures they adopt. This paper aims to make sense of the formalization of the classification pattern in ISE and surveys its history through the literature, starting from the relevant theoretical works of the mathematical literature and gradually shifting focus to the ISE literature. The literature survey follows the evolution of ISE’s understanding of how to formalize the classification pattern. The various proposals are assessed using the classical example of classification; the Linnaean taxonomy formalized using powersets as a benchmark for formal expressiveness. The broad conclusion of the survey is that (1) the ISE community is currently in the early stages of the process of understanding how to formalize the classification pattern, particularly in the requirements for expressiveness exemplified by powersets, and (2) that there is an opportunity to intervene and speed up the process of adoption by clarifying this expressiveness. Given the central place that the classification pattern has in domain modeling, this intervention has the potential to lead to significant improvements.

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Section: A Survey Of Powertypes In Isementioning

confidence: 99%

Formalization of the classification pattern: survey of classification modeling in information systems engineering

et al. 2016

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“…This approach is further developed in [36] and [37], where databases and views are modeled as data abstractions. Also Rowe and Schoens [39], Claybrook et al [ll], Arora and Carlson [3], Lockemann et al [31], and Weber [45] all use an abstract data type approach to model database views.…”

Section: Related Workmentioning

confidence: 99%

Properties and update semantics of consistent views

Gottlob

Puppa

Zicari

1988

ACM Trans. Database Syst.

106

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The problem of translating view updates to database updates is considered. Both databases and views are modeled as data abstractions. A data abstraction consists of a set of states and of a set of primitive update operators representing state transition functions. It is shown how complex update programs can be built from primitive update operators and how view update programs are translated into database update programs. Special attention is paid to a class of views that we call "consistent." Loosely speaking, a consistent view is a view with the following property: If the effect of a view update program on a view state is determined, then the effect of the corresponding database update is unambiguously determined. Thus, in order to know how to translate a given view update into a database update, it is sufficient to be aware of a functional specification of such a program. We show that consistent views have a number of interesting properties with respect to the concurrency of (high-level) update transactions. Moreover we show that the class of consistent views includes as a subset the class of views that translate updates under maintenance of a constant complement. However, we show that there exist consistent views that do not translate under constant complement. The results of Bancilhon and Spyratos [6] are generalized in order to capture the update semantics of the entire class of consistent views. In particular we show that the class of consistent views is obtained if we relax the requirement of a constant complement by allowing the complement to decrease according to a suitable partial order.

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“…The application of the abstract data type paradigm to database systems has been discussed at length. 1,2,3,4,5,6,7, 8,9,10,11,12,13,14,15 However, practical use of abstract data types in the full specification of a database system/appfication still awaits realization. This paper reports on one part of an effort to use abstract data types in both the formalization of database t TI~ material is lined ulxm work supported by the National Science Foundation under Grant No.…”

Section: 8 Introductionmentioning

confidence: 99%

Abstract data types in databases: Specification, manipulation and access

Stemple¹,

Sheard²,

Bunker³

1986

1986 IEEE Second International Conference on Data Engineering

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The basic data types from which records can be constructed in most database management systems are limited to a few simple types such as integers, reals, and character strings. There are many applications, exemplified by office automation, computer-aided design and geographic information systems, that could benefit from management of databases containing the complex objects typically used in programming these systems. We call databases that contain user defined abstract data" types object-extended databases.In this paper we examine three aspects of providing support for object-extended databases: their specification, their manipulation by transactions, and access to them via queries. We show that a database specification scheme grounded formally in three abstract data types, finite sets, tuples and lists, accommodates the integration of databases and arbitrary abstract data types from the points of view of database designers, transaction programmers, and query writers and implementers?

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Data abstractions for database systems

Cited by 36 publications

References 11 publications

Formalization of the classification pattern: survey of classification modeling in information systems engineering

Formalization of the classification pattern: survey of classification modeling in information systems engineering

Properties and update semantics of consistent views

Abstract data types in databases: Specification, manipulation and access

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