A New Approach for Checking Schema Validation Properties

Farré, Carles; Teniente, Ernest; Urpí, Toni

doi:10.1007/978-3-540-30075-5_8

Cited by 7 publications

(12 citation statements)

References 13 publications

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“…Moreover, it is able to determine several properties on a database schema, namely state satisfiability, predicate liveliness, constraint redundancy and state reachability [7,8]. It is a semidecidable procedure for finite satisfiability and unsatisfiability.…”

Section: The Cqc Methods In a Nutshellmentioning

confidence: 99%

Reasoning on UML Class Diagrams with OCL Constraints

Queralt

Teniente

2006

Conceptual Modeling - ER 2006

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Abstract. We propose a new approach to check whether a given UML class diagram with its OCL integrity constraints satisfies a set of desirable properties such as schema satisfiability, class liveliness, redundancy of integrity constraints or reachability of partially specified states. Our approach is based on translating both the class diagram and the OCL constraints into a logic representation. Then, we use the CQC Method to verify whether these properties hold for the given diagram and constraints.

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Section: The Cqc Methods In a Nutshellmentioning

confidence: 99%

Reasoning on UML Class Diagrams with OCL Constraints

Queralt

Teniente

2006

Conceptual Modeling - ER 2006

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“…Reference [2] showed how to use the CQC method [3] to validate highly expressive database schemas (featuring integrity constraints, negations and comparisons). However, the CQC method does not provide any kind of explanation when a schema validation property test fails.…”

Section: The Approachmentioning

confidence: 99%

“…Step 3 inserts the selected ground literal Emp(0 1 , ceo 2 ) from the goal to the EDB under construction. Label 3 is attached to this new tuple in order to keep record of which node was responsible for this insertion.…”

Section: Examplementioning

confidence: 99%

“…An important drawback of previous research in this area is that none of the methods proposed to deal with this problem [2,4,10] is able to provide explanations when a certain property does not hold. Therefore, the designer has to consider the full database schema to identify the required schema changes that would fix the problem.…”

Section: Introductionmentioning

confidence: 99%

“…In this paper, we assume that schema validation properties are expressed in terms of a goal G = ← L 1 ∧ … ∧ L m and a set of conditions to enforce F ⊆ IC [2]. In this way, we say that a schema validation property is satisfiable if there is at least one database instance that makes G true and does not violate any integrity constraint in F.…”

Section: Introductionmentioning

confidence: 99%

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Providing Explanations for Database Schema Validation

Rull

Farré

Teniente

et al.

Lecture Notes in Computer Science

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Abstract. We propose a new method for database schema validation that provides an explanation when it determines that a certain desirable property of a database schema does not hold. Explanations are required to give the designer a hint about the changes of the schema that are needed to fix the problem identified. Our method is an extension of the CQC method, which has been shown successful for testing such properties, and its contribution is twofold: Firstly, it is the first method that offers an explanation when the schema is not adequately defined. Secondly, the extension proposed here provides a significant efficiency improvement as far as the run-time performance of the method is concerned.

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Comparative study of view update algorithms in rational choice theory

Delhibabu¹

2014

Appl Intell

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The dynamics of belief and knowledge is one of the major components of any autonomous system that should be able to incorporate new pieces of information. We show that knowledge base dynamics has interesting connection with kernel change via hitting set and abduction. The approach extends and integrates standard techniques for efficient query answering and integrity checking. The generation of hitting set is carried out through a hyper tableaux calculus and magic set that is focused on the goal of minimality. Many different view update algorithms have been proposed in the literature to address this problem. The present paper provides a comparative study of view update algorithms in rational approach. ⋆ This paper extends work from Delhibabu [34] and Mayol [83] Our knowledge base dynamics is defined in two parts: an immutable part (formulae) and updatable part (literals) (for definition and properties see works of Nebel [88] and Segerberg [98]). Knowledge bases have a set of integrity constraints (see the definitions in later section). In the case of finite knowledge bases, it is sometimes hard to see how the update relations should be modified to accomplish certain knowledge base updates.Example 1. Consider a database with an (immutable) rule that a staff member is a person who is currently working in a research group under a chair. Additional (updatable) facts are that matthias and gerhard are group chairs, and delhibabu and aravindan are staff members in group info1. Our first integrity constraint (IC) is that each research group has only one chair ie. ∀x, y, z (y=x) ← group chair(x,y) ∧ group chair(x,z). Second integrity constraint is that a person can be a chair for only one research group ie. ∀x, y, z (y=z)← group chair(y,x) ∧ group chair(z,x).Immutable part: staff chair(X,Y)← staff group(X,Z),group chair(Z,Y). Updatable part: group chair(infor1,matthias)← group chair(infor2,gerhard)← staff group(delhibabu,infor1)← staff group(aravindan,infor1)← Suppose we want to update this database with the information, staff chair(aravindan,gerhard); From the immutable part, we can deduce that this can be achieved by asserting staff group(aravindan,Z) group chair(Z,gerhard)If we are restricted to definite clauses, there are three plausible ways to do this: first case is, aravindan and gerhard belong to infor1, i.e, staff group(aravindan,-info1) group chair(info1,gerhard). We need to delete both base facts group chair-(infor1,matthias)← and group chair(infor2,gerhard)←, because our first IC as well as second IC would be violated otherwise. In order to change the view, we need to insert group chair(infor1,gerhard)← as a base fact. Assume that we have an algorithm that deletes the base facts staff group(delhibabu,infor1)← from the database. But, no rational person will agree with such an algorithm, because the fact staff group(delhibabu,infor1)← is not "relevant" to the view atom.Second case, aravindan and gerhard belong to infor2, that is staff group(aravindan,info2) group chair(info2,gerhard). Simply, insert the new fact ...

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A New Approach for Checking Schema Validation Properties

Cited by 7 publications

References 13 publications

Reasoning on UML Class Diagrams with OCL Constraints

Reasoning on UML Class Diagrams with OCL Constraints

Providing Explanations for Database Schema Validation

Comparative study of view update algorithms in rational choice theory

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