Filipe / Shishkov / Helfert Software and Data Technologies

First International Conference, ICSOFT 2006, Setúbal, Portugal, September 11-14, 2006, Revised Selected Papers
1. Auflage 2008
ISBN: 978-3-540-70621-2
Verlag: Springer Berlin Heidelberg
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 10, 390 Seiten

Reihe: Communications in Computer and Information Science

This book constitutes the best papers of the First International Conference on Software and Data Technologies, ICSOFT 2006, held in Setúbal, Portugal, September 11-14, 2006. The 25 revised full papers presented together with 5 invited papers were carefully reviewed and selected from 187 submissions. The papers are organized in topical sections on programming languages, software engineering, distributed and parallel systems, information systems and data management, as well as knowledge engineering.

Autoren/Hrsg.

Filipe, Joaquim

Shishkov, Boris

Helfert, Markus

Inhaltsverzeichnis

1;Preface;5
2;Organization;6
3;Table of Contents;9
4;Invited Papers;12
4.1;Adaptive Integration of Enterprise and B2B Applications;13
4.1.1;Introduction;13
4.1.2;Development or Integration?;14
4.1.3;Classifying Integration;15
4.1.4;Assuring Adaptive Integration;17
4.1.4.1;Defining Adaptiveness;17
4.1.4.2;Delivering Adaptiveness;21
4.1.4.3;Verifying Adaptiveness;23
4.1.5;Summary;24
4.1.6;References;25
4.2;Ambient Intelligence: Basic Concepts and Applications;26
4.2.1;Introduction;26
4.2.2;Ambient Intelligence;27
4.2.3;Smart Homes;29
4.2.4;Other Environments and Applications for AmI;31
4.2.5;SystemFlow;31
4.2.6;AmI Scenarios;32
4.2.7;Are We There Yet...?;34
4.2.8;Conclusions;35
4.2.9;References;35
4.3;How to Quantify Quality: Finding Scales of Measure;37
4.3.1;Finding and Developing Scales of Measure and Meters;37
4.3.1.1;Reference Library for Scales of Measure;37
4.3.1.2;Reference Library for Meters;38
4.3.2;Managing ‘What’ You Measure;38
4.3.3;Practical Example: Scale Definition;39
4.3.4;Language Core: Scale Definition;42
4.3.5;Principles: Scale Specification;44
4.3.6;Conclusions;46
4.3.7;References;46
4.4;Metamodeling as an Integration Concept;47
4.4.1;Introduction;47
4.4.2;Modeling and Metamodeling;49
4.4.3;Metamodels in Action: Design and Integration;50
4.4.3.1;Design;53
4.4.3.2;Integration;54
4.4.4;Semantic Integration and Interoperability Using Metamodels and Ontologies;55
4.4.5;Conclusions and Outlook;57
4.4.6;References;58
4.5;Engineering Object and Agent Methodologies;61
4.5.1;Methodologies and Method Engineering;61
4.5.2;Existing OO Method Fragments in the Open Repository;62
4.5.3;The Fame Project: New AO Method Fragments and a New Metamodel;63
4.5.3.1;AO Fragments;63
4.5.3.2;A New Metamodel;65
4.5.4;Summary;67
4.5.5;References;67
5;PART I Programming Languages;69
5.1;From Static to Dynamic Process Types;70
5.1.1;Introduction;70
5.1.2;Static Process Types;71
5.1.3;Dynamic Tokens;73
5.1.4;Dynamic Typing;74
5.1.5;Race-Free Programs;77
5.1.6;Discussion, RelatedWork;79
5.1.7;Conclusions;80
5.1.8;References;81
5.2;Aspectboxes: Controlling the Visibility of Aspects;83
5.2.1;Introduction;83
5.2.2;Motivation;84
5.2.3;Example Analysis;85
5.2.4;Scoping Aspects with Aspectboxes;86
5.2.4.1;Aspectboxes in a Nutshell;86
5.2.4.2;Namespace for Classes and Aspects;86
5.2.4.3;Executing Code in an Aspectbox;88
5.2.4.4;Absolute Isolation of Aspects;89
5.2.5;Implementation;89
5.2.6;Related Work;90
5.2.7;Conclusions;91
5.2.8;References;91
5.3;On State Classes and Their Dynamic Semantics;93
5.3.1;Introduction;93
5.3.2;An Example;94
5.3.3;A Calculus for STATEJ;95
5.3.3.1;Syntax;95
5.3.3.2;Operational Semantics;97
5.3.4;From STATEJ to JAVA;100
5.3.5;Related Work;103
5.3.6;Future Work;103
5.3.7;References;104
5.4;Software Implementation of the IEEE 754R Decimal Floating-Point Arithmetic;106
5.4.1;Introduction;106
5.4.2;IEEE 754R Decimal Floating-Point;107
5.4.3;Conversions between Decimal and Binary Formats;108
5.4.4;Decimal Floating-Point Addition;110
5.4.5;Decimal Floating-Point Multiplication;113
5.4.6;Decimal Floating-Point Division;114
5.4.7;Decimal Floating-Point Square Root;116
5.4.8;Conclusions;117
5.4.9;References;118
6;PART II Software Engineering;119
6.1;Bridging between Middleware Systems: Optimisations Using Downloadable Code;120
6.1.1;Introduction;120
6.1.2;Bridging;121
6.1.3;Downloadable Code;122
6.1.4;Optimising Transport-Level Bridging;123
6.1.5;Service Cache Manager;124
6.1.6;Optimising Service-Level Bridging;125
6.1.7;Device-Level Bridging;126
6.1.8;Optimising Device-Level Bridging;127
6.1.9;Event Handling;128
6.1.10;Implementation of Optimised Jini-UPnP Bridging;128
6.1.11;Assessment;129
6.1.11.1;Transport-Level Optimisation;129
6.1.11.2;Service-Level Optimisation;130
6.1.11.3;Device-Level Optimisation;130
6.1.11.4;Generality;131
6.1.12;Value of Work;131
6.1.13;Conclusions;132
6.1.14;References;132
6.2;MDE for BPM: A Systematic Review;134
6.2.1;Introduction;134
6.2.2;Systematic Reviews;136
6.2.3;Review Results;137
6.2.3.1;Studies Selection;137
6.2.3.2;Classification of Studies;138
6.2.4;Findings and Analysis;138
6.2.5;Conclusions and Future Work;141
6.2.6;References;142
6.3;Exploring Feasibility of Software Defects Orthogonal Classification;143
6.3.1;Introduction;143
6.3.1.1;Related Works;144
6.3.1.2;Study Motivations and View;144
6.3.2;Goal and Experiment Hypotheses;145
6.3.3;Experiment Planning and Operation;146
6.3.3.1;Independent Variables: Parameters, Blocking Variables and Factors;146
6.3.3.2;Dependent Variables;147
6.3.4;Results and Data Analysis;148
6.3.4.1;Descriptive Statistics;149
6.3.4.2;Hypothesis Testing;154
6.3.5;Discussion;156
6.3.5.1;Experiment Results;156
6.3.5.2;Threats to Validity;158
6.3.6;Conclusions and Future Works;158
6.3.7;References;159
6.4;Mapping Medical Device Standards Against the CMMI for Configuration Management;160
6.4.1;Introduction;160
6.4.2;Medical Device Industry;161
6.4.3;CMMED Development;162
6.4.4;Guideline Mapping;163
6.4.4.1;Goal 1: Establish Baselines;163
6.4.4.2;Goal 2: Track and Control Changes;166
6.4.4.3;Goal 3: Establish Integrity;167
6.4.5;Preliminary Feedback;169
6.4.6;Summary and Conclusions;170
6.4.7;References;171
6.5;A Systematic Review Measurement in Software Engineering: State-of-the-Art in Measures;172
6.5.1;Introduction;172
6.5.2;Systematic Reviews;173
6.5.2.1;The Systematic Review Process;174
6.5.3;Systematic Review about Software Measures;175
6.5.4;Result Analysis;176
6.5.5;Conclusions and Further Work;181
6.5.6;References;182
6.6;Engineering a Component Language: CompJava;184
6.6.1;Introduction;184
6.6.2;Language Requirements;185
6.6.3;CompJava Overview;188
6.6.4;Component Types;189
6.6.5;Low-Level Components;190
6.6.5.1;Implementing Provided Ports;190
6.6.5.2;Accessing Required Ports;191
6.6.6;Component Composition;192
6.6.6.1;Subcomponents;192
6.6.6.2;Connecting Ports with Plugs;192
6.6.6.3;Factoring Out SourceHandling;194
6.6.7;Dynamic Architectures;195
6.6.8;Conclusions;198
6.6.9;References;198
7;PART III Distributed and Parallel Systems;199
7.1;Towards a Quality Model for Grid Portals;200
7.1.1;Introduction;200
7.1.2;Quality Model for Grid Portals;201
7.1.2.1;Adaptation of the PQM Dimensions;201
7.1.2.2;Inserting New Dimensions;203
7.1.2.3;Definitive Model (G-PQM);203
7.1.3;Applying G-PQM;204
7.1.3.1;GridPort Demo Portal;204
7.1.3.2;OGCE Portal;205
7.1.4;Conclusions and Future Work;207
7.1.5;References;207
7.2;Algorithmic Skeletons for Branch and Bound;209
7.2.1;Introduction;209
7.2.2;Branch and Bound;210
7.2.3;Branch and Bound Skeletons;212
7.2.3.1;Design with a CentralizedWork Pool Manager;212
7.2.3.2;Distributed Work Pool;214
7.2.3.3;Load Distribution and Knowledge Sharing;216
7.2.3.4;Termination Detection;217
7.2.4;Experimental Results;218
7.2.5;Conclusions;222
7.2.6;References;222
7.3;A Hybrid Topology Architecture for P2P File Sharing Systems;225
7.3.1;Introduction;225
7.3.2;P2P Overlay Networks;226
7.3.3;Description of the System;227
7.3.3.1;Obtaining the Identifiers and Joining the General Network;228
7.3.3.2;Joining the Sub-group;228
7.3.3.3;Management of the Hierarchy;228
7.3.3.4;Management of the Rendez-Vous Nodes;228
7.3.3.5;Registering the Shared Files;229
7.3.3.6;Search;229
7.3.4;Advantages of the System;229
7.3.5;Simulations;229
7.3.6;Conclusions;233
7.3.7;References;233
7.4;Parallel Processing of “Group-By Join” Queries on Shared Nothing Machines;235
7.4.1;Introduction;235
7.4.2;The BSP Cost Model;237
7.4.3;Computation of “Group-By Join” Queries;238
7.4.4;Presented Algorithm;239
7.4.5;Conclusions;244
7.4.6;References;245
7.5;Impact of Wrapped System Call Mechanism on Commodity Processors;247
7.5.1;Introduction;247
7.5.2;Scheduling Mechanisms in CEFOS;248
7.5.2.1;CEFOS for Fine-GrainedMultithreading;248
7.5.2.2;Display Requests and Data (DRD) Mechanism;249
7.5.2.3;WSC Mechanism;250
7.5.3;Evaluation: System Call Overhead;251
7.5.3.1;Estimation of the Effectiveness ofWSC;251
7.5.3.2;Performance Evaluation Using getpid();253
7.5.4;Evaluation: Locality of Reference;254
7.5.4.1;cp Program;254
7.5.4.2;Performance Evaluation;256
7.5.5;Conclusions;257
7.5.6;References;258
8;PART IV Information Systems and Data Management;259
8.1;Adding More Support for Associations to the ODMG Object Model;260
8.1.1;Introduction;260
8.1.2;ORN and Related Work;262
8.1.3;Adding ORN to ODL;263
8.1.3.1;Associations in ODL;263
8.1.3.2;Adding ORN Syntax;264
8.1.3.3;ORN Semantics in ODL Context;266
8.1.4;Implementing ORN;268
8.1.5;Conclusions;270
8.1.6;References;271
8.2;Measuring Effectiveness of Computing Facilities in Academic Institutes: A New Solution for a Difficult Problem;273
8.2.1;Introduction;273
8.2.2;Proposed Model;274
8.2.3;Model Validation;275
8.2.3.1;Data Collection;276
8.2.3.2;Data Analysis and Results;276
8.2.3.3;Hypotheses;277
8.2.4;Conclusions;279
8.2.5;References;279
8.3;Combining Information Extraction and Data Integration in the ESTEST System;282
8.3.1;Introduction;282
8.3.2;Background;283
8.3.3;The ESTEST System;284
8.3.3.1;Integrate Data Sources;285
8.3.3.2;CreateMetadata to Assist the IE Process;288
8.3.3.3;Information Extraction Component;290
8.3.3.4;Integrate Results of IE;291
8.3.3.5;Remaining ESTEST Phases;291
8.3.4;Experiments with Road Traffic Accident Data;291
8.3.5;Related Work;292
8.3.6;Conclusions and Future Work;293
8.3.7;References;294
8.4;Introducing a Change-Resistant Framework for the Development and Deployment of Evolving Applications;296
8.4.1;Introduction;296
8.4.2;Defining the Puzzle;299
8.4.3;MDA and Microsoft Software Factories;299
8.4.4;Rethinking MDA;301
8.4.5;The Proposed Framework;302
8.4.5.1;Domain Model;303
8.4.5.2;Application Model;305
8.4.5.3;Operation Model;306
8.4.5.4;Discussion;307
8.4.6;Conclusions and Further Research;307
8.4.7;References;309
8.5;Smart Business Objects for Web Applications: A New Approach to Model Business Objects;310
8.5.1;Introduction;310
8.5.2;Related Work;312
8.5.3;Smart Business Object;313
8.5.3.1;High-Level Architecture of Smart Business Object;314
8.5.3.2;The Smart Business Object Schema;315
8.5.3.3;Smart Business Object Modelling Language;317
8.5.3.4;Creating Web Applications Using Smart Business Object;321
8.5.3.5;Creating a Customer Relationship Management (CRM) Application;322
8.5.4;Conclusions;324
8.5.5;References;324
8.6;A Data Mining Approach to Learning Probabilistic User Behavior Models from Database Access Log;326
8.6.1;Introduction;326
8.6.2;Problem Definition;327
8.6.3;Our Approach;329
8.6.4;Experiments;332
8.6.5;Conclusions;334
8.6.6;References;335
9;PART V Knowledge Engineering;336
9.1;Approximate Reasoning to Learn Classification Rules;337
9.1.1;Introduction;337
9.1.2;The Supervised Learning Method Sucrage;338
9.1.2.1;Rules Generation;338
9.1.2.2;Basic Inference Engine;340
9.1.3;Approximate Reasoning;340
9.1.3.1;Proximity between Observation and Premise;341
9.1.3.2;Approximate Inference;342
9.1.4;Approximate Reasoning to Learn New Rules;343
9.1.4.1;Method with a Constant Number of Rules;343
9.1.4.2;Method with Addition of Rules;344
9.1.5;Tests and Results;345
9.1.5.1;Results of the Method with a Constant Number of Rules;345
9.1.5.2;Results of the Method with Addition of Rules;346
9.1.6;Conclusions;347
9.1.7;References;348
9.2;Combining Metaheuristics for the Job Shop Scheduling Problem with Sequence Dependent Setup Times;350
9.2.1;Introduction;350
9.2.2;Problem Formulation;351
9.2.3;Genetic Algorithm for the SDJSS Problem;352
9.2.3.1;Decoding Algorithm;354
9.2.4;Local Search;355
9.2.4.1;Feasibility Checking;357
9.2.4.2;Makespan Estimation;358
9.2.5;Experimental Study;358
9.2.6;Conclusions;361
9.2.7;References;362
9.3;A Description Clustering Data Mining Technique for Heterogeneous Data;363
9.3.1;Introduction;363
9.3.1.1;Overview of Our Proposal;365
9.3.2;Formal Definitions;366
9.3.3;Finding Interesting Subdescriptions;368
9.3.4;Extracting Association Rules;369
9.3.5;Preliminary Results;371
9.3.6;Conclusions and Future Work;373
9.3.7;References;374
9.4;A Pattern Selection Algorithm in Kernel PCA Applications;376
9.4.1;Introduction;376
9.4.2;Algorithm;378
9.4.2.1;PCA Algorithm;378
9.4.2.2;KPCA Algorithms;380
9.4.2.3;KPCA Pattern Selection Algorithm;381
9.4.3;Data;383
9.4.4;Results;384
9.4.5;Discussion and Conclusions;387
9.4.6;References;388
10;Author Index;390