Lecture Notes in Computer Science : Constraint Debugging - Pierre Deransart

Instant online reading.
Don't wait for delivery!

Lecture Notes in Computer Science

Constraint Debugging

By: Pierre Deransart (Editor), M.V. Hermenegildo (Editor), J. Maluszynski (Editor)

Write A Review

Paperback | 27 September 2000

At a Glance

Paperback
392 Pages

Dimensions(cm)
22.86 x 15.24 x 1.27

Paperback

$84.99

or 4 interest-free payments of $21.25 with

Ships in 5 to 7 business days

Coordinating production across a supply chain, designing a new VLSI chip, allocating classrooms or scheduling maintenance crews at an airport are just a few examples of complex (combinatorial) problems that can be modeled as a set of decision variables whose values are subject to a set of constraints. The decision variables may be the time when production of a particular lot will start or the plane that a maintenance crew will be working on at a given time. Constraints may range from the number of students you can ?t in a given classroom to the time it takes to transfer a lot from one plant to another.Despiteadvancesincomputingpower,manyformsoftheseandother combinatorial problems have continued to defy conventional programming approaches. Constraint Logic Programming (CLP) ?rst emerged in the mid-eighties as a programming technique with the potential of signi?cantly reducing the time it takes to develop practical solutions to many of these problems, by combining the expressiveness of languages such as Prolog with the compu- tional power of constrained search. While the roots of CLP can be traced to Monash University in Australia, it is without any doubt in Europe that this new software technology has gained the most prominence, bene?ting, among other things, from sustained funding from both industry and public R&D programs over the past dozen years. These investments have already paid o?, resulting in a number of popular commercial solutions as well as the creation of several successful European startups.

Shipping

	Standard Shipping	Express Shipping
Metro postcodes:	$9.99	$14.95
Regional postcodes:	$9.99	$14.95
Rural postcodes:	$9.99	$14.95

Orders over $89.00 qualify for free shipping.

How to return your order

At Booktopia, we offer hassle-free returns in accordance with our returns policy. If you wish to return an item, please get in touch with Booktopia Customer Care.

Additional postage charges may be applicable.

Defective items

If there is a problem with any of the items received for your order then the Booktopia Customer Care team is ready to assist you.

For more info please visit our Help Centre.

You Can Find This Book In

Non-Fiction Computing & I.T.Computer Programming & Software Development Object-Oriented Programming or OOP Medicine Medicine in General Software Engineering Programming & Scripting Languages Compilers & Interpreters Mathematics Mathematical Foundation Mathematical Logic

Computer Science Artificial Intelligence Systems Analysis & Design Mathematical Theory of Computation

Introduction	p. 1
Correctness Debugging
An Assertion Language for Constraint Logic Programs	p. 23
Introduction	p. 23
Assertions in Program Validation and Debugging	p. 27
Assertion Schemas for Execution States	p. 29
An Assertion Schema for Success States	p. 30
Adding Preconditions to the Success Schema	p. 31
An Assertion Schema for Call States	p. 32
An Assertion Schema for Query States	p. 33
Program-Point Assertions	p. 34
Logic Formulae about Execution States	p. 35
An Assertion Schema for Declarative Semantics	p. 37
Assertion Schemas for Program Completeness	p. 38
Status of Assertions	p. 40
An Assertion Schema for Computations	p. 44
Logic Formulae about Computations	p. 45
Defining Property Predicates	p. 46
Declaring Property Predicates	p. 47
Defining Property Predicates for Execution States	p. 48
Defining Property Predicates for Computations	p. 50
Approximating Property Predicates	p. 51
Syntax of and Extensions to the Assertion Language	p. 52
Syntax of the Assertion Language	p. 53
Grouping Assertions: Compound Assertions	p. 54
Some Additional Syntactic Sugar	p. 56
Discussion	p. 58
References	p. 59
A Generic Preprocessor for Program Validation and Debugging	p. 63
Introduction	p. 63
Design of the Preprocessor	p. 64
Chapter Outline	p. 68
Architecture and Operation of the Preprocessor	p. 69
The Syntax Checker	p. 69
The Static Analysers	p. 72
Consistency of the Analysis Results	p. 73
The Assertion Normaliser	p. 74
The Assertion Comparator	p. 75
Assertions for System Predicates	p. 75
Assertions for User-Defined Predicates	p. 77
Compile-Time Checking	p. 79
Run-Time Checking	p. 85
Evaluating Atomic Logic Formulae	p. 86
A Program Transformation for Assertion Checking 89
Customising the Preprocessor for a CLP System: The CiaoPP and CHIPRE Tools	p. 93
Describing Built-Ins Using Assertions	p. 94
System Dependent Code for Run-Time Checking	p. 97
A Sample Debugging Session with the Ciao System	p. 98
Some Practical Hints on Debugging with Assertions	p. 103
References	p. 104
Assertions with Constraints for CLP Debugging	p. 109
Introduction	p. 109
Form of Assertions	p. 110
Syntax and Meaning of Assertions	p. 110
The Basic Constructs	p. 111
Correctness Proofs	p. 112
Implementation	p. 112
Example of a Verification	p. 113
Incompleteness Introduced by the Solvers	p. 114
Full Example	p. 115
Samples of Compilations	p. 116
Run-Time Checking	p. 118
Conclusion	p. 119
References	p. 120
Locating Type Errors in Untyped CLP Programs	p. 121
Introduction	p. 121
The Specification Language	p. 124
Calls and Successes of a CLP Program	p. 124
Describing Sets of Constrained Atoms	p. 126
An Example Diagnosis Session	p. 128
The Diagnosis Method	p. 133
Correct and Incorrect Clauses	p. 134
Incorrectness Diagnosis	p. 137
Delays	p. 138
The Diagnosis Tool	p. 141
Limitations of the Approach	p. 143
Related Work	p. 146
Conclusions and Future Work	p. 148
References	p. 149
Declarative Diagnosis in the CLP Scheme	p. 151
Introduction	p. 151
Basic Notions of Symptom and Error	p. 154
Connection between Symptom and Error via Proof-Trees	p. 156
Diagnosis Algorithm	p. 160
Abstract Proof-Trees	p. 163
Implementation	p. 167
A Diagnosis Session	p. 170
Conclusion	p. 172
References	p. 173
Performance Debugging
Visual Tools to Debug Prolog IV Programs	p. 177
Introduction	p. 177
Presentation of the Execution Tree Viewer	p. 178
The Box Model	p. 178
Execution Trees	p. 179
The Prolog IV Execution Tree Viewer	p. 183
Textual Information in the Canvas	p. 184
Viewer Functions Description	p. 184
Colouring Boxes	p. 185
Replay Mode	p. 186
"Replay-Left Mode" Option	p. 186
"Show all Tries" Option	p. 187
Miscellaneous	p. 187
Working with the Debugger	p. 187
Setting a Temporary Break-Point	p. 188
Replaying the Execution	p. 188
About Implementation	p. 189
Conclusion	p. 190
References	p. 190
Search-Tree Visualisation	p. 191
Introduction	p. 191
Related Work	p. 192
Principles of Operation	p. 193
Program Structure	p. 193
Symptoms	p. 193
Operating Mode	p. 194
System Requirements	p. 195
Interface	p. 195
Views	p. 197
Types of Views	p. 197
Tree View	p. 198
Variable Views	p. 201
Constraint Views	p. 203
Propagation View	p. 205
Current State and Further Development	p. 206
Conclusion	p. 207
References	p. 208
Towards a Language for CLP Choice-Tree Visualisation	p. 209
Introduction	p. 209
CLP: Syntax, Semantics and State Properties	p. 211
Syntax	p. 211
Constraint Domains	p. 212
Constrained Predication and D-Atom	p. 212
Operational Semantics	p. 213
CLP Search-Tree	p. 214
Labelling	p. 216
State Properties	p. 217
Tree Pruning and CLP Choice-Tree	p. 219
Unique Minimal Pruned Tree	p. 219
Minimal Pruned Tree Construction	p. 221
CLP Choice-Tree	p. 223
A Language to Specify Views	p. 224
Node Selection	p. 225
Arc Selection	p. 225
Node and Arc Selection Using Differential Information	p. 226
View Specification	p. 227
Implementation and Examples	p. 227
Displaying the Full Concrete Choice-Tree	p. 228
A General Criterion for a More Synthetic View	p. 229
View of the Labelling	p. 230
Use of State Properties	p. 232
Comparison of Labelling Strategies	p. 232
Conclusion	p. 234
References	p. 236
Tools for Search-Tree Visualisation: The APT Tool	p. 237
Introduction	p. 237
Visualising Control	p. 238
The Programmed Search as a Search Tree	p. 239
Representing the Enumeration Process	p. 240
Coupling Control Visualisation with Assertions	p. 241
The APT Tool	p. 242
Event-Based and Time-Based Depiction of Control	p. 245
Abstracting Control	p. 248
Conclusions	p. 250
References	p. 251
Tools for Constraint Visualisation: The VIFID/TRIFID Tool	p. 253
Introduction	p. 253
Displaying Variables	p. 254
Depicting Finite Domain Variables	p. 254
Depicting Herbrand Terms	p. 258
Depicting Intervals or Reals	p. 258
Representing Constraints	p. 259
Abstraction	p. 263
Abstracting Values	p. 263
Domain Compaction and New Dimensions	p. 264
Abstracting Constraints	p. 268
Conclusions	p. 270
References	p. 270
Debugging Constraint Programs by Store Inspection	p. 273
Introduction	p. 273
Constraint Logic Programming in a Nutshell	p. 274
Arising Difficulties when Debugging Constraint Programs	p. 276
Constraint Programming Efficiency	p. 276
Drawbacks of CP Expressiveness	p. 278
Visualising the Store	p. 278
Structuring the Store	p. 279
S-Boxes	p. 281
Presentation of the Debugger Prototype	p. 285
Implementation of the S-Box Based Debugger	p. 287
Modification of the Backtracking Process	p. 291
Modification of the Propagation Process	p. 291
Handling the S-Boxes	p. 293
Conclusion	p. 294
References	p. 296
Complex Constraint Abstraction: Global Constraint Visualisation	p. 299
Introduction	p. 299
Global Constraint Concepts	p. 301
Cumulative	p. 301
Diffn	p. 302
Cycle	p. 302
Among	p. 303
Principles of Operation	p. 303
Class Structure	p. 303
Callbacks	p. 305
API	p. 306
Interface to Search-Tree Tool	p. 307
Use Outside Search-Tree Tool	p. 308
Cumulative Visualisers	p. 308
Cumulative Resource	p. 308
Bin Packing	p. 311
Diffn Visualisers	p. 311
Placement 2D	p. 311
Placement Remains	p. 311
Cycle Visualiser	p. 313
Geographical Tour	p. 313
Graph Lines	p. 314
Interaction between Visualisers	p. 315
Conclusions	p. 315
References	p. 316
Test Cases
Using Constraint Visualisation Tools CHelmut Simonis	p. 321
Introduction	p. 321
Debugging Scenarios	p. 322
Finding New Variable/Value Orderings	p. 323
Comparing Two Heuristics	p. 328
Adding Redundant Constraints	p. 331
Discovering Structure in the Problem	p. 334
Identifying Weak Propagation	p. 336
Case Studies from Industry	p. 337
Scheduling Application Involving Setup Cost	p. 337
Tank Scheduling Application	p. 340
Layout of Mechanical Objects: Graph Colouring	p. 344
Layout of Mechanical Objects: Physical Layout	p. 348
Analysis and Possible Improvements	p. 351
Need for a Debugging Methodology	p. 351
Program Improvement Due to the Use of Debugging Tools	p. 351
General Conclusions on the CHIP Graphical Debugging Tools	p. 352
Suggestions for Extensions to the CHIP Debugging Tools	p. 353
Conclusions	p. 355
References	p. 356
Author Index	p. 357
Subject Index	p. 359
Table of Contents provided by Publisher. All Rights Reserved.

Lecture Notes in Computer Science

Constraint Debugging

At a Glance

Paperback

Shipping

How to return your order

Defective items

You Can Find This Book In

More in Mathematical Theory of Computation

Statistical Atlases and Computational Models of the Heart. Regular and CMRxRecon Challenge Papers

16th International Workshop, STACOM 2025, Held in Conjunction with MICCAI 2025, Daejeon, South Korea, September 27, 2025, Revised Selected Papers

AI Engineering

Building Applications with Foundation Models

Swim Training Patterns

1st Edition - Plan your Training Sessions with the Power of Mathematics

Algorithms in C, Parts 1-4

3rd Edition - Fundamentals, Data Structures, Sorting, Searching

Discrete Mathematics for Computing

Grassroots

Effective Machine Learning Teams

Best Practices for ML Practitioners

Beading With Algorithms

Cellular Automata In Peyote Stitch

Mathematical Foundations of Deep Learning

Theory and Algorithms

Mathematical Foundations of Deep Learning

Theory and Algorithms

Nonlinear Analysis for Human Movement Variability

Mining Complex Networks

Advances in Applied Mathematics

Mining Complex Networks

Advances in Applied Mathematics

Theory of Computation for Software Developers

Decentralized Futures

Navigating the Integration of Blockchain Technology with Artificial Intelligence

Zhang Time Discretization (ZTD) Formulas and Applications

Machine Learning Interviews

Kickstart Your Machine Learning and Data Career

Metaheuristic Algorithms

Theory and Practice

Introduction to Modern Cryptography

Revised Third Edition

Scientific Computing and Software

Go20 CSCS, Ghajnsielem, Malta, May 20-24, 2024

Python Essentials

Symbolic and Numeric Problem-Solving in Engineering

Linear Algebra with Applications in Machine Learning

From Intuitive Understanding to Python Coding

Guide to Graph Algorithms

Sequential, Parallel and Distributed

Introduction to Numerical Mathematics

Theory, Practice and Numerous Examples

Surveys in Combinatorics 2026

London Mathematical Society Lecture Note Series

This product is categorised by