Automatic Re-engineering of Software Using Genetic Programming

Softcover Nachdruck of the original 1. Auflage 2000
ISBN: 978-1-4613-7094-9
Verlag: Springer US

Buch, Englisch, Band 2, 140 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 254 g

Reihe: Genetic Programming

describes the application of Genetic Programming to a real world application area - software re-engineering in general and automatic parallelization specifically. Unlike most uses of Genetic Programming, this book evolves sequences of provable transformations rather than actual programs. It demonstrates that the benefits of this approach are twofold: first, the time required for evaluating a population is drastically reduced, and second, the transformations can subsequently be used to prove that the new program is functionally equivalent to the original.
shows that there are applications where it is more practical to use GP to assist with software engineering rather than to entirely replace it. It also demonstrates how the author isolated aspects of a problem that were particularly suited to GP, and used traditional software engineering techniques in those areas for which they were adequate.
is an excellent resource for researchers in this exciting new field.

Zielgruppe

Research

Autoren/Hrsg.

Ryan, Conor

Fachgebiete

• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Software Engineering
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Compiler
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz

Inhaltsverzeichnis

1. Introduction.- 1.1 Software Re-Engineering.- 1.2 Auto-parallelization.- 1.3 Genetic Programming.- 1.4 Outline.- 2. Genetic Programming.- 2.1 Introduction.- 2.2 Evolution and Natural Selection.- 2.3 Evolutionary Algorithms.- 2.4 The Simple Genetic Algorithm.- 2.5 Genetic Programming.- 2.6 Other Evolutionary Algorithms.- 2.7 Advanced topics in Evolutionary Algorithms.- 2.8 Evolution and Learning.- 2.9 Summary.- 3. Software Re-Engineering.- 3.1 Introduction.- 3.2 Auto-parallelization.- 3.3 Parallel Programming.- 3.4 Parallelization Problems.- 3.5 Parallel Compilers.- 3.6 On using Genetic Programming.- 3.7 An Automatic Parallelization System.- 3.8 Summary.- 4. Multi-Objective Problems.- 4.1 Introduction.- 4.2 Example Problem — Sorting Networks.- 4.3 Maintaining Diversity In Artificial Evolution.- 4.4 Pygmies And Civil Servants.- 4.5 Gender or Race?.- 4.6 Multi-modal Functions.- 4.7 Conclusion.- 5. Paragen I.- 5.1 Introduction.- 5.2 Problem Statement.- 5.3 Paragen — The First Results.- 5.4 Paragen and Races.- 5.5 Engineering vs. Re-Engineering.- 5.6 Conclusion.- 6. Practical Considerations.- 6.1 Provability.- 6.2 Scalability.- 6.3 Loop Complexity.- 6.4 Communication and Scheduling.- 6.5 Multiprocessor Scheduling.- 6.6 Genetic Algorithms.- 6.7 Conclusions.- 7. Paragen II.- 7.1 Transformations.- 7.2 Atoms and Loops.- 7.3 Atoms, loops and modes.- 7.4 Genetic Structure.- 7.5 Example Individual.- 7.6 Conclusion.- 8. Conclusions.- 8.1 Future Work.- 8.2 Recommendations.- References.