Extending Conditional Dependencies with Built-in Predicates

This paper proposes a natural extension of conditional functional dependencies (CFDs [1]) and conditional inclusion dependencies (CINDs [2]), denoted by CFDps and CIND(p)s, respectively, by specifying patterns of data values with not equal, <, <=, >, and >= predicates. As data quality rules, CFDps and CIND(p)s are able to capture errors that commonly arise in practice but cannot be detected by CFDs and CINDs. We establish two sets of results for central technical problems associated with CFD(p)s and CIND(p)s. (a) One concerns the satisfiability and implication problems for CFD(p)s and CIND(p)s, taken separately or together. These are important for, e.g. deciding whether data quality rules are dirty themselves, and for removing redundant rules. We show that despite the increased expressive power, the static analyses of CFD(p)s and CIND(p)s retain the same complexity as their CFDs and CINDs counterparts. (b) The other concerns validation of CFD(p)s and CIND(p)s. We show that given a set Sigma of CFD(p)s and CIND(p)s on a database D, a set of SQL queries can be automatically generated that, when evaluated against D, return all tuples in D that violate some dependencies in Sigma. We also experimentally verified the efficiency and effectiveness of our SQL based error detection techniques, using real-life data. This provides commercial DBMS with an immediate capability to detect errors based on CFD(p)s and CIND(p)s.973 program [2014CB340300, 2012CB316200, 2014CB340302]; NSFC [61322207, 61133002]; Guangdong Innovative Research Team Program [2011D005]; Shenzhen Peacock Program [1105100030834361]; EPSRC [EP/J015377/1, EP/M025268/1]; NSF III [1302212]; Google Faculty Research Award; [ERC-2014-AdG 652976]SCI(E)[email protected]; [email protected]; [email protected]; [email protected]; [email protected]

Specifying Logic Programs in Controlled Natural Language

Writing specifications for computer programs is not easy since one has to take into account the disparate conceptual worlds of the application domain and of software development. To bridge this conceptual gap we propose controlled natural language as a declarative and application-specific specification language. Controlled natural language is a subset of natural language that can be accurately and efficiently processed by a computer, but is expressive enough to allow natural usage by non-specialists. Specifications in controlled natural language are automatically translated into Prolog clauses, hence become formal and executable. The translation uses a definite clause grammar (DCG) enhanced by feature structures. Inter-text references of the specification, e.g. anaphora, are resolved with the help of discourse representation theory (DRT). The generated Prolog clauses are added to a knowledge base. We have implemented a prototypical specification system that successfully processes the specification of a simple automated teller machine.Comment: 16 pages, compressed, uuencoded Postscript, published in Proceedings CLNLP 95, COMPULOGNET/ELSNET/EAGLES Workshop on Computational Logic for Natural Language Processing, Edinburgh, April 3-5, 199

Improving Prolog programs: Refactoring for Prolog

Refactoring is an established technique from the object-oriented (OO) programming community to restructure code: it aims at improving software readability, maintainability and extensibility. Although refactoring is not tied to the OO-paradigm in particular, its ideas have not been applied to Logic Programming until now. This paper applies the ideas of refactoring to Prolog programs. A catalogue is presented listing refactorings classified according to scope. Some of the refactorings have been adapted from the OO-paradigm, while others have been specifically designed for Prolog. The discrepancy between intended and operational semantics in Prolog is also addressed by some of the refactorings. In addition, ViPReSS, a semi-automatic refactoring browser, is discussed and the experience with applying ViPReSS to a large Prolog legacy system is reported. The main conclusion is that refactoring is both a viable technique in Prolog and a rather desirable one.Comment: To appear in Theory and Practice of Logic Programming (TPLP