This is the first book that attempts to provide a framework in which to embed an automatic programming system based on evolutionary learning (genetic programming) into a traditional software engineering environment. As such, it looks at how traditional software engineering knowledge can be integrated with an evolutionary programming process in a symbiotic way.

In architecting dependable systems, what is required to improve the overall system robustness is fault tolerance. Many methods have been proposed to this end, the solutions are usually considered late during the design and implementation phases of the software life-cycle (e.g., Java and Windows NT exception handling), thus reducing the effectiveness error and fault handling. Since the system design typically models only normal behaviour of the system while ignoring exceptional ones, the implementation of the system is unable to handle abnormal events. Consequently, the system may fail in unexpected ways due to faults.It has been argued that fault tolerance management during the entire life-cycle improves the overall system robustness and that different classes of threats need to be identified for and dealt with at each distinct phase of software development, depending on the abstraction level of the software system being modelled.This book builds on this trend and investigates how fault tolerance mechanisms can be applied when engineering a software system. In particular, it identifies the new problems arising in this area, introduces the new models to be applied at different abstraction levels, defines methodologies for model-driven engineering of such systems and outlines the new technologies and validation and verification environments supporting this.

Machine learning deals with the issue of how to build computer programs that improve their performance at some tasks through experience. Machine learning algorithms have proven to be of great practical value in a variety of application domains. Not surprisingly, the field of software engineering turns out to be a fertile ground where many software development and maintenance tasks could be formulated as learning problems and approached in terms of learning algorithms. This book deals with the subject of machine learning applications in software engineering. It provides an overview of machine learning, summarizes the state-of-the-practice in this niche area, gives a classification of the existing work, and offers some application guidelines. Also included in the book is a collection of previously published papers in this research area.

Over the years, a variety of software process models have been designed to structure, describe and prescribe the software systems construction process. More recently, software process modelling is increasingly dealing with new challenges raised by the tests that the software industry has to face. This book addresses these new trends in software process modeling related to: . OCo Processes for open source software;. OCo Systems dynamics to model and simulate the software process;. OCo Peopleware: the importance of people in the software development and by extension in the software process. One new software development trend is the development of open source projects. As such projects are a recent creation, the process model governing this type of developments is unfamiliar. This book deals with process modeling for open source software. It also deals with software process simulation applied to the management of software projects and improves the software development process capability according to CMM (Capability Maturity Model). Software development is a conjunction of: the organizational environment, the social environment and the technological environment. The inclusion of these environments will make it possible to output software process models that meet the specified organizational, cultural and technological requirements, providing an exhaustive analysis of the people in the software process, as well as supporting people-oriented software development. This book deals with the development of software by means of people-oriented process models that have proven to be very beneficial. Sample Chapter(s). Chapter 1: Discovering, Modeling, and Re-Enacting Open Source Software Development Processes: A Case Study (316 KB). Contents: Discovering, Modeling, and Re-enacting Open Source Software Development Processes: A Case Study (C Jensen & W Scacchi); Software Process Dynamics: Modeling, Simulation and Improvement (M Ruiz et al.); Software Process Simulation with System Dynamics OCo A Tool for Learning and Decision Support (D Pfahl et al.); High Level Software Project Modeling with System Dynamics (M De Oliveira Barros et al.); People-Oriented Capture, Display, and Use of Process Information (J Heidrich et al.); Requirements and Validation of the E3 Process Modeling System (L Jaccheri). Readership: Researchers, students and professionals of software process and development."

Over the years, a variety of software process models have been designed to structure, describe and prescribe the software systems construction process. More recently, software process modelling is increasingly dealing with new challenges raised by the tests that the software industry has to face.This book addresses these new trends in software process modeling related to:• Processes for open source software;• Systems dynamics to model and simulate the software process;• Peopleware: the importance of people in the software development and by extension in the software process.One new software development trend is the development of open source projects. As such projects are a recent creation, the process model governing this type of developments is unfamiliar. This book deals with process modeling for open source software. It also deals with software process simulation applied to the management of software projects and improves the software development process capability according to CMM (Capability Maturity Model).Software development is a conjunction of: the organizational environment, the social environment and the technological environment. The inclusion of these environments will make it possible to output software process models that meet the specified organizational, cultural and technological requirements, providing an exhaustive analysis of the people in the software process, as well as supporting people-oriented software development. This book deals with the development of software by means of people-oriented process models that have proven to be very beneficial.

This volume emphasizes the primary role played by images in computer science. In the last two decades images have replaced written texts; the enormous possibilities of the image language have overcome written language in an ever-more-restricted ambit.An image is better than one thousand words; so it was straightforward to apply visual language in the field of computer science. Nowadays everything that appears on a computer screen is an image, regardless of whether it is a word or a picture. Is it possible to realize an e-learning program without working in terms of images? The answer is undoubtedly no, even if several problems arise in this context: the qualitative and quantitative content of the image we need to use for a specific task; the psychological effect on the user, including the level of attention and the correct perception of the image significance. Most of these problems form the basis of image-understanding techniques.Widespread use of images requires organization of the information in the databank or database, whose dimensions are sometimes so wide as to be too complex to manage; therefore information retrieval techniques arise from this need. The new instruments used in image and/or remote diagnosis, image transmission, the respect of the law in force and the ever-more-relevant image storage capacity required for this task imply the use of techniques of visual language and information retrieval.The proceedings have been selected for coverage in: ? Index to Scientific & Technical Proceedings? (ISTP? / ISI Proceedings)? Index to Scientific & Technical Proceedings (ISTP CDROM version / ISI Proceedings)

This volume emphasizes the primary role played by images in computer science. In the last two decades images have replaced written texts; the enormous possibilities of the image language have overcome written language in an ever-more-restricted ambit.An image is better than one thousand words; so it was straightforward to apply visual language in the field of computer science. Nowadays everything that appears on a computer screen is an image, regardless of whether it is a word or a picture. Is it possible to realize an e-learning program without working in terms of images? The answer is undoubtedly no, even if several problems arise in this context: the qualitative and quantitative content of the image we need to use for a specific task; the psychological effect on the user, including the level of attention and the correct perception of the image significance. Most of these problems form the basis of image-understanding techniques.Widespread use of images requires organization of the information in the databank or database, whose dimensions are sometimes so wide as to be too complex to manage; therefore information retrieval techniques arise from this need. The new instruments used in image and/or remote diagnosis, image transmission, the respect of the law in force and the ever-more-relevant image storage capacity required for this task imply the use of techniques of visual language and information retrieval.The proceedings have been selected for coverage in:• Index to Scientific & Technical Proceedings® (ISTP® / ISI Proceedings)• Index to Scientific & Technical Proceedings (ISTP CDROM version / ISI Proceedings)