Logic Program Synthesis from Incomplete Information

Program synthesis is a solution to the software crisis. If we had a program that develops correct programs from specifications, then program validation and maintenance would disappear from the software life-cycle, and one could focus on the more creative tasks of specification elaboration, validation, and maintenance, because replay of program development would be less costly.
This monograph describes a novel approach to Inductive Logic Programming (ILP), which cross-fertilizes logic programming and machine learning. Aiming at the synthesis of recursive logic programs only, and this from incomplete information, we take a software engineering approach that is more appropriate than a pure artificial intelligence approach.
This book is suitable as a secondary text for graduate level courses in software engineering and artificial intelligence, and as a reference for practitioners of program synthesis.

Inhalt

Lists of Logic Algorithms, Figures, and Tables. Foreword. Preface. I: State of the Art. 1. Automatic Programming. 2. Deductive Inference in Automatic Programming. 3. Inductive Inference in Automatic Programming. 4. A Logic Program Development Methodology. 5. Objectives. II: Building Blocks. 6. A Specification Approach. 7. A Framework for Stepwise Logic Algorithm Synthesis. 8. Algorithm Analysis and Algorithm Schemata. 9. The Proofs-as-Programs Method. 10. The Most-Specific-Generalization Method. III: A Logic Algorithm Synthesis Mechanism. 11. Overview of the Synthesis Mechanism. 12. The Expansion Phase. 13. The Reduction Phase. 14. Conclusion. Appendix: Conventions, Abbreviations, and Symbols. References. Subject Index.