This volume focuses on current and future trends in the interplay between software engineering and artificial intelligence.This interplay is now critical to the success of both disciplines, and it also affects a wide range of subject areas. The articles in this volume survey the significant work that has been accomplished, describe the state of the art, analyze the current trends, and predict which future directions have the most potential for success. Areas covered include requirements engineering, real-time systems, reuse technology, development environments and meta-environments, process representations, safety-critical systems, and metrics and measures for processes and products.

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 book is useful for readers who want to visualize graphs as representing structural knowledge in a variety of fields. It gives an outline of the whole field, describes in detail the representative methods for drawing graphs, explains extensions such as fisheye and dynamic drawing, presents many practical applications, and discusses ways of evaluation. It makes the intuitive understanding of these easier by using examples and diagrams, and provides a wealth of references for those readers who wish to know more.

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.

Empirical verification of knowledge is one of the foundations for developing any discipline. As far as software construction is concerned, the empirically verified knowledge is not only sparse but also not very widely disseminated among developers and researchers. This book aims to spread the idea of the importance of empirical knowledge in software development from a highly practical viewpoint. It has two goals: (1) Define the body of empirically validated knowledge in software development so as to advise practitioners on what methods or techniques have been empirically analysed and what the results were; (2) as empirical tests have traditionally been carried out by universities or research centres, propose techniques applicable by industry to check on the software development technologies they use. Contents: Limitations of Empirical Testing Technique Knowledge (N Juristo et al.); Replicated Studies: Building a Body of Knowledge about Software Reading Techniques (F Shull et al.); Combining Data from Reading Experiments in Software Inspections OCo A Feasibility Study (C Wholin et al.); External Experiments OCo A Workable Paradigm for Collaboration Between Industry and Academia (F Houdek); (Quasi-)Experimental Studies in Industrial Settings (O Laitenberger & D Rombach); Experimental Validation of New Software Technology (M V Zelkowitz et al.). Readership: Researchers, academics and professionals in software engineering."

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.

This is a textbook for a course in object-oriented software engineering at advanced undergraduate and graduate levels, as well as for software engineers. It contains more than 120 exercises of diverse complexity.The book discusses fundamental concepts and terminology on object-oriented software development, assuming little background on software engineering, and emphasizes design and maintenance rather than programming.It also presents up-to-date and easily understood methodologies and puts forward a software life cycle model which explicitly encourages reusability during software development and maintenance.

This book covers the principles and recent research results in intelligent image database systems design. Special emphasis is placed on spatial reasoning and the techniques for image indexing and retrieval, mainly based on the Theory of Symbolic Projection. In addition, applications of the theory and techniques to intelligent image database systems design are also discussed.

This is an excellent, up-to-date and easy-to-use text on data structures and algorithms that is intended for undergraduates in computer science and information science. The thirteen chapters, written by an international group of experienced teachers, cover the fundamental concepts of algorithms and most of the important data structures as well as the concept of interface design. The book contains many examples and diagrams. Whenever appropriate, program codes are included to facilitate learning.This book is supported by an international group of authors who are experts on data structures and algorithms, through its website at http: //www.cs.pitt.edu/ jung/GrowingBook/, so that both teachers and students can benefit from their expertise