Algebraic specifications with generating constraints

  • H. Ehrig
  • E. G. Wagner
  • J. W. Thatcher
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 154)


In this paper we take a new look at one of the basic principles of abstract data types. Due to this principle the domain of an abstract data type must be generated by the operations. In the initial algebraic approach as well as in the loose case with initial restrictions or data constraints this principle is satisfied because of initiality resp. free construction. Actually initiality makes sure that the data under consideration are not only generated but even freely generated by the operations. In this paper we do not consider free generation but only generation leading to the new concept of algebraic specifications with generating constraints.

This new look was also motivated by the notion of hierarchy constraints, introduced by the CIP-group in Munich, but there are two main differences between hierarchy and generating constraints: First of all we remove the consistency condition “TRUE≠FALSE” for bool. This part of hierarchy constraints can be expressed (if necessary) in the axiom part of the specifications. Secondly we give a mechanism how to construct generating constraints and how to translate or reflect them from one part of a specification to other parts. More precisely we define syntax and semantics of a language building up generating constraints together with the stepwise construction of an algebraic specification. The main result of this paper shows how an arbitrary generating constraint built up in this way can be transformed to a very simple constraint in canonical form which is equivalent to the given one. Equivalence of two generating constraints on the same algebraic specification means that they have the same semantics, i.e. they define the same class of algebras.

Finally we discuss how concepts and results of this paper could be used for the design of algebraic specification languages where not only the specifications but also the constraints are built up in a stepwise way.


Forgetful Functor Data Constraint Denotational Semantic Constraint Language Abstract Data Type 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1983

Authors and Affiliations

  • H. Ehrig
    • 1
  • E. G. Wagner
    • 2
  • J. W. Thatcher
    • 2
  1. 1.Technische UniversitätBerlinGermany
  2. 2.IBM T.J.W. Research CenterYorktown HeightsUSA

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