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The premise behind developing powerful declarative database languages is compelling: by enabling users to specify their queries (and their integrity constraints) in a clear, non-operational way, they make the user's task easier, and provide the database system with more opportunities for optimization. Relational database systems offer a striking proof that this premise is indeed valid. The most popular relational query language, SQL, is based upon relational algebra and calculus, i.e., a small fragment of first-order logic, and the ease of writing queries in SQL (in comparison to more navigational languages) has been an important factor in the commercial success of relational databases. It is well-known that SQL has some important limitations, in spite of its success and popUlarity. Notably, the query language is non-recursive, and support for integrity constraints is limited. Indeed, recognizing these problems, the latest standard, SQL-92, provides increased support for integrity constraints, and it is anticipated that the successor to the SQL-92 standard, called SQL3, RECURSIVE UNION operation [1]. Logic database systems have will include a concentrated on these extensions to the relational database paradigm, and some systems (e.g., Bull's DEL prototype) have even incorporated object-oriented features (another extension likely to appear in SQL3).

The premise behind developing powerful declarative database languages is compelling: by enabling users to specify their queries (and their integrity constraints) in a clear, non-operational way, they make the user's task easier, and provide the database system with more opportunities for optimization. Relational database systems offer a striking proof that this premise is indeed valid. The most popular relational query language, SQL, is based upon relational algebra and calculus, i.e., a small fragment of first-order logic, and the ease of writing queries in SQL (in comparison to more navigational languages) has been an important factor in the commercial success of relational databases. It is well-known that SQL has some important limitations, in spite of its success and popUlarity. Notably, the query language is non-recursive, and support for integrity constraints is limited. Indeed, recognizing these problems, the latest standard, SQL-92, provides increased support for integrity constraints, and it is anticipated that the successor to the SQL-92 standard, called SQL3, RECURSIVE UNION operation [1]. Logic database systems have will include a concentrated on these extensions to the relational database paradigm, and some systems (e.g., Bull's DEL prototype) have even incorporated object-oriented features (another extension likely to appear in SQL3).

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CONTENTS
PREFACE = xv
 REFERENCES = xxii
1 APPLICATIONS OF DEDUCTIVE OBJECT-ORIENTED DATABASES USING DEL / Oris D. Friesen ; Gilles Gauthier-Villars ; Laurent Vieille = 1
 1 Introduction = 1
 2 Architecture and Language = 2
 3 Data Mining = 7
 4 Regulatory Applications = 12
 5 Concurrent Engineering = 17
 6 Conclusion = 21
 REFERENCES = 22
2 Q-DATA : USING DEDUCTIVE DATABASE TECHNOLOGY TO IMPROVE DATA QUALITY / Amit Sheth ; Christopher Wood ; Vipul Kashyap = 23
 1 Introduction = 24
 2 Related Work = 27
 3 Example Application of Data Validation and Cleanup = 27
 4 System Architecture and Features = 33
 5 Pragmatic and Engineering Experiences = 42
 6 Conclusions = 53
 REFERENCES = 55
3 A DEDUCTIVE FRONT-END FOR RELATIONAL DATABASES / Brian Livezey ; Evangelos Simoudis = 57
 1 Introduction = 57
 2 Model Development Using Deductive Databases = 59
 3 IDEA = 60
 4 Applications = 74
 5 Related Work = 77
 6 Ongoing Work = 78
 7 Conclusions = 79
 REFERENCES = 80
4 AN ADITI IMPLEMENTATION OF A FLIGHTS DATABASE / James Harland ; Kotagiri Ramamohanarao = 83
 1 Introduction = 83
 2 Aditi = 85
 3 Flight Information = 88
 4 Assembling a Flight Schedule = 91
 5 Performance Results = 95
 6 Conclusion = 98
 REFERENCES = 99
5 USING LDL++ FOR SPATIO-TEMPORAL REASONING IN ATMOSPHERIC SCIENCE DATABASES / Richard R. Muntz ; Eddie Shek ; Carlo Zaniolo = 101
 1 Introduction = 101
 2 Geoscience Dataset = 102
 3 System Architecture = 105
 4 Spatio-Temporal Queries = 107
 5 Conclusion = 116
 REFERENCES = 117
6 MIMSY : A SYSTEM FOR STOCK MARKET ANALYSIS / William G. Roth ; Raghu Ramakrishnan ; Praveen Seshadri = 121
 1 Overview = 121
 2 The Language = 123
 3 The Translator = 127
 4 The Graphical Interface = 131
 5 Series Data = 134
 6 The Server = 135
 7 Extensibility = 137
 8 Conclusion = 139
 9 Appendix = 140
 REFERENCES = 141
7 EFFICIENT EVALUATION OF VISUAL QUERIES USING DEDUCTIVE DATABASES / Dimitra Vista ; Peter T. Wood = 143
 1 Introduction = 143
 2 An Overview of H$$ y^+ $$ = 145
 3 The GraphLog Visual Query Language = 147
 4 Translating GraphLog to Factored Datalog = 152
 5 Performance Comparisons = 156
 6 Conclusions = 158
 REFERENCES = 159
8 DEMAND INTERPROCEDURAL PROGRAM ANALYSIS USING LOGIC DATABASES / Thomas W. Reps = 163
 1 Introduction = 163
 2 Background and Assumptions = 167
 3 Interprocedural Dataflow Analysis Poblems = 168
 4 Interprocedural Slicing = 177
 5 Preliminary Experimental Results = 187
 6 Related Work = 189
 REFERENCES = 192
9 AMOS : A NATURAL LANGUAGE PARSER IMPLEMENTED AS A DEDUCTIVE DATABASE IN LOLA / Gunther Specht ; Burkhard Freitag = 197
 1 Introduction = 197
 2 Sketch of the Deductive Database System LOLA = 199
 3 Grammars as Logic Programs = 200
 4 The AMOS Parsing System = 206
 5 AMOS as a Tool for Linguistic Research = 212
 6 Conclusion = 214
 REFERENCES = 214
10 PROGRAMMING THE PTQ GRAMMAR IN XSB / David S. Warren = 217
 1 Introduction  = 218
 2 PTQ Syntax = 220
 3 PTQ Semantics = 225
 4 Evaluation and Statistics = 230
 5 Conclusion = 231
 REFERENCES = 233
11 QUERYING WITH GENERALIZED QUANTIFIERS / Antonio Badia ; Dirk Van Gucht ; Marc Gyssens = 235
 1 Introduction = 235
 2 Generalized Quantifiers = 238
 3 The Query Language ○○○○ = 245
 4 The Conjunctive Formulation Thesis = 248
 5 Generalized Quantifiers in Existing Query Languages = 250
 6 Conclusion = 256
 REFERENCES = 257
12 REQUIREMENTS FOR A DEDUCTIVE QUERY LANGUAGE IN A GENOME-MAPPING DATABASE / Nathan Goodman ; Steve Rozen ; Lincoln Stein = 259
 1 Overview and Requirements = 259
 2 MapBase Design = 261
 3 What We Want From a Query Facility = 265
 4 A Deductive Solution = 273
 REFERENCES = 275
INDEX = 279