A purely reactive navigation scheme for dynamic environments using Case-Based Reasoning

This paper presents a new sonar based purely reactive navigation technique for mobile platforms. The method relies on Case-Based Reasoning to adapt itself to any robot and environment through learning, both by observation and self experience. Thus, unlike in other reactive techniques, kinematics or dynamics do not need to be explicitly taken into account. Also, learning from different sources allows combination of their advantages into a safe and smooth path to the goal. The method has been succesfully implemented on a Pioneer robot wielding 8 Polaroid sonar sensors. Cristina Urdiales is a Lecturer at the Department of Tecnología Electrónica (DTE) of the University of Málaga (UMA). She received a MSc degree in Telecommunication Engineering at the Universidad Politécnica de Madrid (UPM) and her Ph.D. degree at University of Málaga (UMA). Her research is focused on robotics and computer vision. E.J. Pérez was born in Barcelona, Spain, in 1974. He received his title of Telecommunication Engineering from the University of Málaga, Spain, in 1999. During 1999 he worked in a research project under a grant by the Spanish CYCIT. From 2000 to the present day he has worked as Assistant Professor in the Department of Tecnología Electrónica of the University of Málaga. His research is focused on robotics and artificial vision. Javier Vázquez-Salceda is an Associate Researcher of the Artificial Intelligence Section of the Software Department (LSI), at the Technical University of Catalonia (UPC). Javier obtained an MSc degree in Computer Science at UPC. After his master studies he became research assistant in the KEMLg Group at UPC. In 2003 he presented his Ph.D. dissertation (with honours), which has been awarded with the 2003 ECCAI Artificial Intelligence Dissertation Award. The dissertation has been also recently published as a book by Birkhauser-Verlag. From 2003 to 2005 he was researcher in the Intelligent Systems Group at Utrecht University. Currently he is again member of the KEMLg Group at UPC. His research is focused on theoretical and applied issues of Normative Systems, software and physical agents' autonomy and social control, especially in distributed applications for complex domains such as eCommerce or Medicine. Miquel Sànchez-Marrè (Barcelona, 1964) received a Ph.D. in Computer Science in 1996 from the Technical University of Catalonia (UPC). He is Associate Professor in the Computer Software Department (LSI) of the UPC since 1990 (tenure 1996). He was the head of the Artificial Intelligence section of LSI (1997–2000). He is a pioneer member of International Environmental Modelling and Software Society (IEMSS) and a board member of IEMSS also, since 2000. He is a member of the Editorial Board of International Journal of Applied Intelligence, since October 2001. Since October 2004 he is Associate Editor of Environmental Modelling and Software journal. His main research topics are case-based reasoning, machine learning, knowledge acquisition and data mining, knowledge engineering, intelligent decision-support systems, and integrated AI architectures. He has an special interest on the application of AI techniques to Environmental Decision Support Systems. Francisco Sandoval was born in Spain in 1947. He received the title of Telecommunication Engineering and Ph.D. degree from the Technical University of Madrid, Spain, in 1972 and 1980, respectively. From 1972 to 1989 he was engaged in teaching and research in the fields of opto-electronics and integrated circuits in the Universidad Politécnica de Madrid (UPM) as an Assistant Professor and a Lecturer successively. In 1990 he joined the University of Málaga as Full Professor in the Department of Tecnología Electrónica. He is currently involved in autonomous systems and foveal vision, application of Artificial Neural Networks to Energy Management Systems, and in Broad Band and Multimedia Communication.     

Tradeoff and Sensitivity Analysis in Software Architecture Evaluation Using Analytic Hierarchy Process

Software architecture evaluation involves evaluating different architecture design alternatives against multiple quality-attributes. These attributes typically have intrinsic conflicts and must be considered simultaneously in order to reach a final design decision. AHP (Analytic Hierarchy Process), an important decision making technique, has been leveraged to resolve such conflicts. AHP can help provide an overall ranking of design alternatives. However it lacks the capability to explicitly identify the exact tradeoffs being made and the relative size of these tradeoffs. Moreover, the ranking produced can be sensitive such that the smallest change in intermediate priority weights can alter the final order of design alternatives. In this paper, we propose several in-depth analysis techniques applicable to AHP to identify critical tradeoffs and sensitive points in the decision process. We apply our method to an example of a real-world distributed architecture presented in the literature. The results are promising in that they make important decision consequences explicit in terms of key design tradeoffs and the architecture's capability to handle future quality attribute changes. These expose critical decisions which are otherwise too subtle to be detected in standard AHP results. Liming Zhu is a PHD candidate in the School of Computer Science and Engineering at University of New South Wales. He is also a member of the Empirical Software Engineering Group at National ICT Australia (NICTA). He obtained his BSc from Dalian University of Technology in China. After moving to Australia, he obtained his MSc in computer science from University of New South Wales. His principle research interests include software architecture evaluation and empirical software engineering. Aybüke Aurum is a senior lecturer at the School of Information Systems, Technology and Management, University of New South Wales. She received her BSc and MSc in geological engineering, and MEngSc and PhD in computer science. She also works as a visiting researcher in National ICT, Australia (NICTA). Dr. Aurum is one of the editors of “Managing Software Engineering Knowledge”, “Engineering and Managing Software Requirements” and “Value-Based Software Engineering” books. Her research interests include management of software development process, software inspection, requirements engineering, decision making and knowledge management in software development. She is on the editorial boards of Requirements Engineering Journal and Asian Academy Journal of Management. Ian Gorton is a Senior Researcher at National ICT Australia. Until Match 2004 he was Chief Architect in Information Sciences and Engineering at the US Department of Energy's Pacific Northwest National Laboratory. Previously he has worked at Microsoft and IBM, as well as in other research positions. His interests include software architectures, particularly those for large-scale, high-performance information systems that use commercial off-the-shelf (COTS) middleware technologies. He received a PhD in Computer Science from Sheffield Hallam University. Dr. Ross Jeffery is Professor of Software Engineering in the School of Computer Science and Engineering at UNSW and Program Leader in Empirical Software Engineering in National ICT Australia Ltd. (NICTA). His current research interests are in software engineering process and product modeling and improvement, electronic process guides and software knowledge management, software quality, software metrics, software technical and management reviews, and software resource modeling and estimation. His research has involved over fifty government and industry organizations over a period of 15 years and has been funded from industry, government and universities. He has co-authored four books and over one hundred and twenty research papers. He has served on the editorial board of the IEEE Transactions on Software Engineering, and the Wiley International Series in Information Systems and he is Associate Editor of the Journal of Empirical Software Engineering. He is a founding member of the International Software Engineering Research Network (ISERN). He was elected Fellow of the Australian Computer Society for his contribution to software engineering research.     

MLP-based radar detectors for Swerling 1 targets

This paper deals with the application of Multilayer Perceptrons to radar detection. The dependence of the neural detector performance on the network size and on the signal-to-noise ratio selected for training is considered. Multilayer Perceptrons with different numbers of neurons in the hidden layer have been trained using different values of the signal-to-noise ratio to minimize the mean square error using the error back-propagation algorithm. Results show that the higher the number of hidden neurons, the closer the neural detector to the Neyman-Pearson optimum detector and the lower the dependence of the Multilayer Perceptron performance on the signal-to-noise ratio selected for training. Due to its practical interest, the very low probability of false alarm values has been considered. To estimate the probability of a false alarm, importance sampling techniques have been used in order to reduce the computational cost of maintaining a low relative error. The text was submitted by the authors in English. Maria Pilar Jarabo-Amores. Year of birth: 1971. Year in which an academic degree was awarded: Telecomunication Engineer, Polythecnic University of Madrid, 1997. Affiliation: Signal Theory and Communications Department, Polytechnic School, Alcalá University (Spain). Position: Associate Professor. Area of research: Signal Processing, Signal Detection, Radar Systems. Number of publications (monographs and articles): 21 journal articles, 8 book chapters, 31 conference contributions, 2 books. Membership to academies, scientific societies, and editorial boards and journals: IEEE member. Awards and prizes for achievements in research or applications: Best PhD. Thesis in Telecommunications Engineering at Alcalá University. Roberto Gil-Pita. Year of birth: 1978. Year in which an academic degree was awarded: Telecomunication Engineer, Alcalá University, 2001. Affiliation: Signal Theory and Communications Department, Polytechnic School, Alcalá University (Spain). Position: Associate Professor. Area of research: Signal Processing and Radar applications. Number of publications (monographs and articles): 23 journal articles, 5 book chapters, 18 conference contributions. Membership to academies, scientific societies, and editorial boards and journals: IEEE Member. Manuel Rosa-Zurera. Year of birth: 1968. Year in which an academic degree was awarded: Telecomunication Engineer, Polythecnic University of Madrid, 1995. Affiliation: Signal Theory and Communications Department, Polytechnic School, Alcalá University (Spain). Position: Associate Professor and Head of the Department. Area of research: Signal Processing, Signal Detection, Radar Systems. Number of publications (monographs and articles): 37 journal articles, 14 book chapters, 61 conference contributions, 2 books. Membership to academies, scientific societies, and editorial boards and journals: IEEE member. Francisco López-Ferreras. Year of birth: 1948. Year in which an academic degree was awarded: Telecomunication Engineer, Polytechnic University of Madrid, 1970. Affiliation: Signal Theory and Communications Department, Polytechnic School, Alcalá University (Spain). Position: Associate Professor and Dean. Area of research: Signal Processing. Number of publications (monographs and articles): 41 journal articles, 16 book chapters, 92 conference contributions, 10 books. Membership to academies, scientific societies, and editorial boards and journals: IEEE member. Raúl Vicen-Bueno. Year of birth: 1977. Year in which an academic degree was awarded: Telecomunication Engineer, Alcalá University, 2002. Affiliation: Signal Theory and Communications Department, Polytechnic School, Alcalá University (Spain). Position: Assistant Professor. Area of research: Signal Processing and Radar applications. Number of publications (monographs and articles): 14 journal articles, 3 book chapters, 5 conference contributions, 1 book. Awards and prizes for achievements in research or applications: Second place in the “Liberalization de las Telecomunicaciones” awards, given by the “Colegio Oficial de Ingenieros Tecnicos de Telecomunicacion” (COITT) of Spain.     

Early Estimation of Users’ Perception of Software Quality

This paper presents a methodology for estimating users’ opinion of the quality of a software product. Users’ opinion changes with time as they progressively become more acquainted with the software product. In this paper, we study the dynamics of users’ opinion and offer a method for assessing users’ final perception, based on measurements in the early stages of product release. The paper also presents methods for collecting users’ opinion and from the derived data, shows how their initial belief state for the quality of the product is formed. It adapts aspects of Belief Revision theory in order to present a way of estimating users’ opinion, subsequently formed after their opinion revisions. This estimation is achieved by using the initial measurements and without having to conduct surveys frequently. It reports the correlation that users tend to infer among quality characteristics and represents this correlation through a determination of a set of constraints between the scores of each quality characteristic. Finally, this paper presents a fast and automated way of forming users’ new belief state for the quality of a product after examining their opinion revisions. Dimitris Stavrinoudis received his degree in Computer Engineering from Patras University and is a Ph.D. student of Computer Engineering and Informatics Department. He worked as a senior computer engineer and researcher at the R.A. Computer Technology Institute. He has participated in research and development projects in the areas of software engineering, databases and educational technologies. Currently, he works at the Hellenic Open University. His research interests include software quality, software metrics and measurements. Michalis Xenos received his degree and Ph.D. in Computer Engineering from Patras University. He is a Lecturer in the Informatics Department of the School of Sciences and Technology of the Hellenic Open University. He also works as a researcher in the Computer Technology Institute of Patras and has participated in over 15 research and development projects in the areas of software engineering and IT development management. His research interests include, inter alia, Software Engineering and Educational Technologies. He is the author of 6 books in Greek and over 30 papers in international journals and conferences. Pavlos Peppas received his B.Eng. in Computer Engineering from Patras University (1988), and his Ph.D. in Computer Science from Sydney University (1994). He joined Macquarie University, Sydney, as a lecturer in September 1993, and was promoted to a senior lecturer in October 1998. In January 2000, he took up an appointment at Intrasoft, Athens, where he worked as a senior specialist in the Data Warehousing department. He joint Athens Information Technology in February 2003 as a senior researcher, and since November 2003 he is an associate professor at the Dept of Business Administration at the University of Patras. He also holds an adjunct associate professorship at the School of Computer Science and Engineering at the University of New South Wales. His research interests lie primarily within the area of Artificial Intelligence, and more specifically in logic-based approaches to Knowledge Representation and Reasoning with application in robotics, software engineering, organizational knowledge management, and the semantic web. Dimitris Christodoulakis received his degree in Mathematics from the University of Athens and his Ph.D. in Informatics from the University of Bonn. He was a researcher at the National Informatics Centre of Germany. He is a Professor and Vice President of Computer Engineering and Informatics Department of Patras University. Scientific Coordinator in many research and development projects in the followings sections: Knowledge and Data Base Systems, Very large volume information storage, Hypertext, Natural Language Technology for Modern Greek. Author and co-author in many articles published in international conferences. Editor in proceedings of conventions. Responsible for proofing tools development for Microsoft Corp. He is Vice Director in the Research Academic Computer Technology Institute (RACTI).     

Automated support for deriving test requirements from UML statecharts

Many statechart-based testing strategies result in specifying a set of paths to be executed through a (flattened) statechart. These techniques can usually be easily automated so that the tester does not have to go through the tedious procedure of deriving paths manually to comply with a coverage criterion. The next step is then to take each test path individually and derive test requirements leading to fully specified test cases. This requires that we determine the system state required for each event/transition that is part of the path to be tested and the input parameter values for all events and actions associated with the transitions. We propose here a methodology towards the automation of this procedure, which is based on a careful normalization and analysis of operation contracts and transition guards written with the Object Constraint Language (OCL). It is illustrated by one case study that exemplifies the steps of our methodology and provides a first evaluation of its applicability. The scope of the testing activity depends on what is modeled by the statechart. If the statechart models the behavior of a single class, then it can be used to support unit testing. If the behavior of a class-cluster, a subsystem or a component is modeled, then we are concerned with integration testing. If the whole system is modeled, then the focus of statechart-based testing is system testing. Lionel C. Briand is on the faculty of the Department of Systems and Computer Engineering, Carleton University, Ottawa, Canada, where he founded and leads the Software Quality Engineering Laboratory (http://www.sce.carleton.ca/Squall/ Squall.htm). He has been granted the Canada Research Chair in Software Quality Engineering and is also a visiting professor at the Simula laboratories, University of Oslo, Norway. Before that he was the software quality engineering department head at the Fraunhofer Institute for Experimental Software Engineering, Germany. Dr. Lionel also worked as a research scientist for the Software Engineering Laboratory, a consortium of the NASA Goddard Space Flight Center, CSC, and the University of Maryland. He has been on the program, steering, or organization committees of many international, IEEE conferences such as ICSE, ICSM, ISSRE, and METRICS. He is the coeditor-in-chief of Empirical Software Engineering (Springer) and is a member of the editorial board of Systems and Software Modeling (Springer). He was on the board of IEEE Transactions on Software Engineering from 2000 to 2004. His research interests include: object-oriented analysis and design, inspections and testing in the context of object-oriented development, quality assurance and control, project planning and risk analysis, and technology evaluation. Lionel received the BSc and MSc degrees in geophysics and computer systems engineering from the University of Paris VI, France. He received the PhD degree in computer science, with high honors, from the University of Paris XI, France. Yvan Labiche received the BSc in Computer System Engineering, from the graduate school of engineering: CUST (Centre Universitaire des Science et Techniques, Clermont-Ferrand), France. He completed a Master of fundamental computer science and production systems in 1995 (Université Blaise Pascal, Clermont Ferrand, France). While doing his Ph.D. in Software Engineering, completed in 2000 at LAAS/CNRS in Toulouse, France, Yvan worked with Aerospatiale Matra Airbus (now EADS Airbus) on the definition of testing strategies for safety-critical, on-board software, developed using object-oriented technologies. In January 2001, Dr. Yvan Labiche joined the Department of Systems and Computer Engineering at Carleton University, as an Assistant Professor. His research interests include: object-oriented analysis and design, software testing in the context of object-oriented development, and technology evaluation. He is a member of the IEEE. Jim (Jingfeng) Cui completed his BSc in Industrial Automation Control, from the School of Information and Engineering, Northeastern University, China. He received a Master of Applied Science (specialization in Software Engineering) in 2004 from the Ottawa-Carleton Institute of Electrical and Computer Engineering, Ottawa, Canada. While in his graduate study, he was awarded the Ontario Graduate Scholarship of Science and Technology. He is now a senior Software Architect in Sunyard System & Engineering Co.Ltd., China. His interest includes Object-Oriented Software Development, Quality Assurance, and Content Management System.     

A Framework for Design Tradeoffs

Designs almost always require tradeoffs between competing design choices to meet system requirements. We present a framework for evaluating design choices with respect to meeting competing requirements. Specifically, we develop a model to estimate the performance of a UML design subject to changing levels of security and fault-tolerance. This analysis gives us a way to identify design solutions that are infeasible. Multi-criteria decision making techniques are applied to evaluate the remaining feasible alternatives. The method is illustrated with two examples: a small sensor network and a system for controlling traffic lights. Dr. Anneliese Amschler Andrews is Professor and Chair of the Department of Computer Science at the University of Denver. Before that she was the Huie Rogers Endowed Chair in Software Engineering at Washington State University. Dr. Andrews is the author of a text book and over 130 articles in the area of Software Engineering, particularly software testing and maintenance. Dr. Andrews holds an MS and PhD from Duke University and a Dipl.-Inf. from the Technical University of Karlsruhe. She served as Editor-in-Chief of the IEEE Transactions on Software Engineering. She has also served on several other editorial boards including the IEEE Transactions on Reliability, the Empirical Software Engineering Journal, the Software Quality Journal, the Journal of Information Science and Technology, and the Journal of Software Maintenance. She was Director of the Colorado Advanced Software Institute from 1995 to 2002. CASI's mission was to support technology transfer research related to software through collaborations between industry and academia. Ed Mancebo studied software engineering at Milwaukee School of Engineering and computer science at Washington State University. His masters thesis explored applying systematic decision making methods to software engineering problems. He is currently a software developer at Amazon.com. Dr. Per Runeson is a professor in software engineering at Lund University, Sweden. His research interests include methods to facilitate, measure and manage aspects of software quality. He received a PhD from Lund University in 1998 and has industrial experience as a consulting expert. He is a member of the editorial board of Empirical Software Engineering and several program committees, and currently has a senior researcher position funded by the Swedish Research Council. Robert France is currently a Full Professor in the Department of Computer Science at Colorado State University. His research interests are in the area of Software Engineering, in particular formal specification techniques, software modeling techniques, design patterns, and domain-specific modeling languages. He is an Editor-in-Chief of the Springer journal on Software and System Modeling (SoSyM), and is a Steering Committee member and past Steering Committee Chair of the MoDELS/UML conference series. He was also a member of the revision task forces for the UML 1.x standards.     

An empirical study of predicting software faults with case-based reasoning

The resources allocated for software quality assurance and improvement have not increased with the ever-increasing need for better software quality. A targeted software quality inspection can detect faulty modules and reduce the number of faults occurring during operations. We present a software fault prediction modeling approach with case-based reasoning (CBR), a part of the computational intelligence field focusing on automated reasoning processes. A CBR system functions as a software fault prediction model by quantifying, for a module under development, the expected number of faults based on similar modules that were previously developed. Such a system is composed of a similarity function, the number of nearest neighbor cases used for fault prediction, and a solution algorithm. The selection of a particular similarity function and solution algorithm may affect the performance accuracy of a CBR-based software fault prediction system. This paper presents an empirical study investigating the effects of using three different similarity functions and two different solution algorithms on the prediction accuracy of our CBR system. The influence of varying the number of nearest neighbor cases on the performance accuracy is also explored. Moreover, the benefits of using metric-selection procedures for our CBR system is also evaluated. Case studies of a large legacy telecommunications system are used for our analysis. It is observed that the CBR system using the Mahalanobis distance similarity function and the inverse distance weighted solution algorithm yielded the best fault prediction. In addition, the CBR models have better performance than models based on multiple linear regression. Taghi M. Khoshgoftaar is a professor of the Department of Computer Science and Engineering, Florida Atlantic University and the Director of the Empirical Software Engineering Laboratory. His research interests are in software engineering, software metrics, software reliability and quality engineering, computational intelligence, computer performance evaluation, data mining, and statistical modeling. He has published more than 200 refereed papers in these areas. He has been a principal investigator and project leader in a number of projects with industry, government, and other research-sponsoring agencies. He is a member of the Association for Computing Machinery, the IEEE Computer Society, and IEEE Reliability Society. He served as the general chair of the 1999 International Symposium on Software Reliability Engineering (ISSRE’99), and the general chair of the 2001 International Conference on Engineering of Computer Based Systems. Also, he has served on technical program committees of various international conferences, symposia, and workshops. He has served as North American editor of the Software Quality Journal, and is on the editorial boards of the journals Empirical Software Engineering, Software Quality, and Fuzzy Systems. Naeem Seliya received the M.S. degree in Computer Science from Florida Atlantic University, Boca Raton, FL, USA, in 2001. He is currently a Ph.D. candidate in the Department of Computer Science and Engineering at Florida Atlantic University. His research interests include software engineering, computational intelligence, data mining, software measurement, software reliability and quality engineering, software architecture, computer data security, and network intrusion detection. He is a student member of the IEEE Computer Society and the Association for Computing Machinery.     

Robust detection and ordering of ellipses on a calibration pattern

The aim of this work is to accurately estimate from an image the parameters of some ellipses and their relative positions with respect to a given pattern. The process is characterized because it is fully automated and is robust against image noise and occlusions. We have built a calibrator pattern with two planes each containing several ordered circles in known 3D positions. Our method is able to estimate the position of every ellipse and to put them into correspondence with the original calibrator circles. The text was submitted by the authors in English. Luis álvarez received an MS in applied mathematics in 1985 and a PhD in mathematics in 1988, both from CompIntense University (Madrid, Spain). Between 1991 and 1992, he worked as a postdoctoral researcher at CEREMADE, Université Paris IX—Dauphine (France). Currently, he is with the Computer Science Department of the University of Las Palmas de Gran Canaria. His research interests are computer vision and partial differential equations. He is the scientific leader of computer vision group of the University of Las Palmas named AMI. Agustín Salgado received an MS in computer science in from the University of Las Palmas de Gran Canaria (Las Palmas, Spain). Currently, he holds a grant from the Computer Science Department of the University of Las Palmas de Gran Canaria, where he is working on his doctoral thesis under the direction of Javier Sánchez. Javier Sánchez received an MS in computer science in 1997 and a PhD in computer science in 2001, both from the University of Las Palmas de Gran Canaria (Las Palmas, Spain). Between 1997 and 1998, he attended some courses of the DBA 127 “Informatique: Systemes Intelligentes” at the Université Paris IX—Dauphine (France). Currently, he is a lecturer at the Computer Science Department of the University of Las Palmas de Gran Canaria. His research interests are computer vision and partial differential equations, specially applied to stereoscopic vision and optical flow estimation.     

Applying language modeling to session identification from database trace logs

A database session is a sequence of requests presented to the database system by a user or an application to achieve a certain task. Session identification is an important step in discovering useful patterns from database trace logs. The discovered patterns can be used to improve the performance of database systems by prefetching predicted queries, rewriting the current query or conducting effective cache replacement.In this paper, we present an application of a new session identification method based on statistical language modeling to database trace logs. Several problems of the language modeling based method are revealed in the application, which include how to select values for the parameters of the language model, how to evaluate the accuracy of the session identification result and how to learn a language model without well-labeled training data. All of these issues are important in the successful application of the language modeling based method for session identification. We propose solutions to these open issues. In particular, new methods for determining an entropy threshold and the order of the language model are proposed. New performance measures are presented to better evaluate the accuracy of the identified sessions. Furthermore, three types of learning methods, namely, learning from labeled data, learning from semi-labeled data and learning from unlabeled data, are introduced to learn language models from different types of training data. Finally, we report experimental results that show the effectiveness of the language model based method for identifying sessions from the trace logs of an OLTP database application and the TPC-C Benchmark. Xiangji Huang joined York University as an Assistant Professor in July 2003 and then became a tenured Associate Professor in May 2006. Previously, he was a Post Doctoral Fellow at the School of Computer Science, University of Waterloo, Canada. He did his Ph.D. in Information Science at City University in London, England, with Professor Stephen E. Robertson. Before he went into his Ph.D. program, he worked as a lecturer for 4 years at Wuhan University. He also worked in the financial industry in Canada doing E-business, where he was awarded a CIO Achievement Award, for three and half years. He has published more than 50 refereed papers in journals, book chapter and conference proceedings. His Master (M.Eng.) and Bachelor (B.Eng.) degrees were in Computer Organization & Architecture and Computer Engineering, respectively. His research interests include information retrieval, data mining, natural language processing, bioinformatics and computational linguistics. Qingsong Yao is a Ph.D. student in the Department of Computer Science and Engineering at York University, Toronto, Canada. His research interests include database management systems and query optimization, data mining, information retrieval, natural language processing and computational linguistics. He earned his Master's degree in Computer Science from Institute of Software, Chinese Academy of Science in 1999 and Bachelor's degree in Computer Science from Tsinghua University. Aijun An is an associate professor in the Department of Computer Science and Engineering at York University, Toronto, Canada. She received her Bachelor's and Master's degrees in Computer Science from Xidian University in China. She received her PhD degree in Computer Science from the University of Regina in Canada in 1997. She worked at the University of Waterloo as a postdoctoral fellow from 1997 to 1999 and as a research assistant professor from 1999 to 2001. She joined York University in 2001. She has published more than 60 papers in refereed journals and conference proceedings. Her research interests include data mining, machine learning, and information retrieval.     

Climbing Robots’ Mobility for Inspection and Maintenance of 3D Complex Environments

For complex climbing robots, which work in difficult 3D outdoor environments, the gravity force has an important influence with respect the robots changes during its motion. This type of climbing robots is self-supported in the complex 3D structures (bridges, skeleton of the buildings, etc.) which require periodic, manually performed inspections and maintenance. The use of non-conventional climbing robots for this type of operation is highly appropriate. Their locomotion system commonly comprises arms/legs that permit the robots 3D mobility (gait). These mechanisms also enable the robot to support itself and guarantee its stability. This paper presents the main features of non-conventional climbing robots mobility on complex 3D environments: power supply, number of DOFs, lightweight structure, gait, speed, secure grasp, etc. It also covers the general theory underlying the design of climbing robots, their kinematics, with its specific, unconventional mobility. The paper not only describes the climbing robot mobility theory but also provides several examples taken from the ROMA and MATS robots families. The developed robots have high degree of autonomy with totally on-board control system. These autonomous robots demonstrate in the course of real experimentation that the criteria for design, control strategy and path planning are accurate. Finally, the paper examines trends in climbing robot technology.Carlos Balaguer received his Ph.D. in Automation from the Polytechnic University of Madrid (UPM), Spain in 1983. From 1983–1994 he was with the Department of Systems Engineering and Automation of the UPM as Associated Professor. Since 1994, he has been a Full Professor of the Robotics Lab at the University Carlos III of Madrid. Prof. Balaguers research has included robot design and development, robot control, path & task planning, force-torque control, assistive and service robots, climbing robots, legged and humanoid robots, and human-robot interaction. He has published more than 120 papers in journals and conference proceedings, and several books in the field of robotics. He is a member of IEEE and IFAC, and former President of IAARC.Antonio Gimenez studied Electrical Engineering at the Polytechnic University of Madrid and received his PhD from the University Carlos III of Madrid in 2000. Currently he is Associated Professor at the Robotics Lab atthe University Carlos III of Madrid. He participated in numerous national and international R&D projects in robotics and automation. His research interest includes design and robot development, rehabilitation robots, climbing robots, and automation in construction. Recently he is very active in the field of computer-aided mechatronics design. He has published numerous refereed publications in international journals, and conference proceedings.Alberto Jardón Huete is currently finishing his Ph.D. degree in Automation Engineering. He received his B.Sc. in electronics engineering (1998) and is graduated in Electrical Engineering (2002) at University Carlos III of Madrid. He is an active member of the Robotics Lab since 1997, and has collaborated in the development of the climbing robots ROMA I, ROMA II, and other research projects of relevance. Currently he is focused in the design and development of light weight service robots. His interests include assistive robotic design, mechatronics, robotic research, the development of tools to perform this research and the transfer of robotics technology to industry.     

Empirical evaluation of optimization algorithms when used in goal-oriented automated test data generation techniques

Software testing is an essential process in software development. Software testing is very costly, often consuming half the financial resources assigned to a project. The most laborious part of software testing is the generation of test-data. Currently, this process is principally a manual process. Hence, the automation of test-data generation can significantly cut the total cost of software testing and the software development cycle in general. A number of automated test-data generation approaches have already been explored. This paper highlights the goal-oriented approach as a promising approach to devise automated test-data generators. A range of optimization techniques can be used within these goal-oriented test-data generators, and their respective characteristics, when applied to these situations remain relatively unexplored. Therefore, in this paper, a comparative study about the effectiveness of the most commonly used optimization techniques is conducted.

A Metamodel for Assessable Software Development Methodologies

Software development methodologies usually contain guidance on what steps to follow in order to obtain the desired product. At the same time, capability assessment frameworks usually assess the process that is followed on a project in practice in the context of a process reference model, defined separately and independently of any particular methodology. This results in the need for extra effort when trying to match a given process reference model with an organisation’s enacted processes. This paper introduces a metamodel for the definition of assessable methodologies, that is, methodologies that are constructed with assessment in mind and that contain a built-in process reference model. Organisations using methodologies built from this metamodel will benefit from automatically ensuring that their executed work conforms to the appropriate assessment model. Cesar Gonzalez-Perez is a post-doctoral research fellow in the Faculty of Information Technology at UTS, where he is currently researching with Professor Henderson-Sellers in object-oriented methodologies, with particular emphasis on metamodelling and component-based, assessable methodologies. He is the founder and former technical director of Neco, a company based in Spain specializing in software development support services, which include the deployment and use of the OPEN/Metis methodology at small and mid-sized organizations. He has also worked for the University of Santiago de Compostela in Spain as a researcher in computing & archaeology, and received his Ph.D. in this topic in 2000. Tom McBride has more than twenty years in the computer industry in positions ranging from computer operator, developer, project manager to QA manager. He is significantly involved in standards development, both locally in Australia and internationally for the International Standards Organisation. Tom is Chairman of the Australian Computer Society National Standards Committee and is assisting the development of the OOSPICE Component Based Development methodology. He is also a lecturer in software development-related subjects at the University of Technology, Sydney and is currently enrolled as a Ph.D.student investigating coordination in software development. Brian Henderson-Sellers is Director of the Centre for Object Technology Applications and Research and Professor of Information Systems at UTS. He is author of eleven books on object technology and is well-known for his work in OO methodologies (MOSES, COMMA, OPEN, OOSPICE) and in OO metrics. Brian has been Regional Editor of Object-Oriented Systems, a member of the editorial board of Object Magazine/Component Strategies and Object Expert for many years and is currently on the editorial board of Journal of Object Technology and Software and Systems Modelling. He was the Founder of the Object-Oriented Special Interest Group of the Australian Computer Society (NSW Branch) and Chairman of the Computerworld Object Developers’ Awards committee for ObjectWorld 94 and 95 (Sydney). He is a frequent, invited speaker at international OT conferences. In 1999, he was voted number 3 in the Who’s Who of Object Technology (Handbook of Object Technology, CRC Press, Appendix N). He is currently a member of the Review Panel for the OMG’s Software Process Engineering Model (SPEM) standards initiative and is a member of the UML 2.0 review team. In July 2001, Professor Henderson-Sellers was awarded a Doctor of Science (D.Sc.) from the University of London for his research contributions in object-oriented methodologies.     

A practical approach to testing GUI systems

GUI systems are becoming increasingly popular thanks to their ease of use when compared against traditional systems. However, GUI systems are often challenging to test due to their complexity and special features. Traditional testing methodologies are not designed to deal with the complexity of GUI systems; using these methodologies can result in increased time and expense. In our proposed strategy, a GUI system will be divided into two abstract tiers—the component tier and the system tier. On the component tier, a flow graph will be created for each GUI component. Each flow graph represents a set of relationships between the pre-conditions, event sequences and post-conditions for the corresponding component. On the system tier, the components are integrated to build up a viewpoint of the entire system. Tests on the system tier will interrogate the interactions between the components. This method for GUI testing is simple and practical; we will show the effectiveness of this approach by performing two empirical experiments and describing the results found.

The pairwise attribute noise detection algorithm

Analyzing the quality of data prior to constructing data mining models is emerging as an important issue. Algorithms for identifying noise in a given data set can provide a good measure of data quality. Considerable attention has been devoted to detecting class noise or labeling errors. In contrast, limited research work has been devoted to detecting instances with attribute noise, in part due to the difficulty of the problem. We present a novel approach for detecting instances with attribute noise and demonstrate its usefulness with case studies using two different real-world software measurement data sets. Our approach, called Pairwise Attribute Noise Detection Algorithm (PANDA), is compared with a nearest neighbor, distance-based outlier detection technique (denoted DM) investigated in related literature. Since what constitutes noise is domain specific, our case studies uses a software engineering expert to inspect the instances identified by the two approaches to determine whether they actually contain noise. It is shown that PANDA provides better noise detection performance than the DM algorithm. Jason Van Hulse is a Ph.D. candidate in the Department of Computer Science and Engineering at Florida Atlantic University. His research interests include data mining and knowledge discovery, machine learning, computational intelligence and statistics. He is a student member of the IEEE and IEEE Computer Society. He received the M.A. degree in mathematics from Stony Brook University in 2000, and is currently Director, Decision Science at First Data Corporation. Taghi M. Khoshgoftaar is a professor at the Department of Computer Science and Engineering, Florida Atlantic University, and the director of the Empirical Software Engineering and Data Mining and Machine Learning Laboratories. His research interests are in software engineering, software metrics, software reliability and quality engineering, computational intelligence, computer performance evaluation, data mining, machine learning, and statistical modeling. He has published more than 300 refereed papers in these subjects. He has been a principal investigator and project leader in a number of projects with industry, government, and other research-sponsoring agencies. He is a member of the IEEE, the IEEE Computer Society, and IEEE Reliability Society. He served as the program chair and general chair of the IEEE International Conference on Tools with Artificial Intelligence in 2004 and 2005, respectively. Also, he has served on technical program committees of various international conferences, symposia, and workshops. He has served as North American editor of the Software Quality Journal, and is on the editorial boards of the journals Empirical Software Engineering, Software Quality, and Fuzzy Systems. Haiying Huang received the M.S. degree in computer engineeringfrom Florida Atlantic University, Boca Raton, Florida, USA, in 2002. She is currently a Ph.D. candidate in the Department of Computer Science and Engineering at Florida Atlantic University. Her research interests include software engineering, computational intelligence, data mining, software measurement, software reliability, and quality engineering.     

A study of the model and algorithms for handling location-dependent continuous queries

Advances in wireless and mobile computing environments allow a mobile user to access a wide range of applications. For example, mobile users may want to retrieve data about unfamiliar places or local life styles related to their location. These queries are called location-dependent queries. Furthermore, a mobile user may be interested in getting the query results repeatedly, which is called location-dependent continuous querying. This continuous query emanating from a mobile user may retrieve information from a single-zone (single-ZQ) or from multiple neighbouring zones (multiple-ZQ). We consider the problem of handling location-dependent continuous queries with the main emphasis on reducing communication costs and making sure that the user gets correct current-query result. The key contributions of this paper include: (1) Proposing a hierarchical database framework (tree architecture and supporting continuous query algorithm) for handling location-dependent continuous queries. (2) Analysing the flexibility of this framework for handling queries related to single-ZQ or multiple-ZQ and propose intelligent selective placement of location-dependent databases. (3) Proposing an intelligent selective replication algorithm to facilitate time- and space-efficient processing of location-dependent continuous queries retrieving single-ZQ information. (4) Demonstrating, using simulation, the significance of our intelligent selective placement and selective replication model in terms of communication cost and storage constraints, considering various types of queries. Manish Gupta received his B.E. degree in Electrical Engineering from Govindram Sakseria Institute of Technology & Sciences, India, in 1997 and his M.S. degree in Computer Science from University of Texas at Dallas in 2002. He is currently working toward his Ph.D. degree in the Department of Computer Science at University of Texas at Dallas. His current research focuses on AI-based software synthesis and testing. His other research interests include mobile computing, aspect-oriented programming and model checking. Manghui Tu received a Bachelor degree of Science from Wuhan University, P.R. China, in 1996, and a Master's Degree in Computer Science from the University of Texas at Dallas 2001. He is currently working toward the Ph.D. degree in the Department of Computer Science at the University of Texas at Dallas. Mr. Tu's research interests include distributed systems, wireless communications, mobile computing, and reliability and performance analysis. His Ph.D. research work focuses on the dependent and secure data replication and placement issues in network-centric systems. Latifur R. Khan has been an Assistant Professor of Computer Science department at University of Texas at Dallas since September 2000. He received his Ph.D. and M.S. degrees in Computer Science from University of Southern California (USC) in August 2000 and December 1996, respectively. He obtained his B.Sc. degree in Computer Science and Engineering from Bangladesh University of Engineering and Technology, Dhaka, Bangladesh, in November of 1993. Professor Khan is currently supported by grants from the National Science Foundation (NSF), Texas Instruments, Alcatel, USA, and has been awarded the Sun Equipment Grant. Dr. Khan has more than 50 articles, book chapters and conference papers focusing in the areas of database systems, multimedia information management and data mining in bio-informatics and intrusion detection. Professor Khan has also served as a referee for database journals, conferences (e.g. IEEE TKDE, KAIS, ADL, VLDB) and he is currently serving as a program committee member for the 11th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD2005), ACM 14th Conference on Information and Knowledge Management (CIKM 2005), International Conference on Database and Expert Systems Applications DEXA 2005 and International Conference on Cooperative Information Systems (CoopIS 2005), and is program chair of ACM SIGKDD International Workshop on Multimedia Data Mining, 2004. Farokh Bastani received the B.Tech. degree in Electrical Engineering from the Indian Institute of Technology, Bombay, and the M.S. and Ph.D. degrees in Computer Science from the University of California, Berkeley. He is currently a Professor of Computer Science at the University of Texas at Dallas. Dr. Bastani's research interests include various aspects of the ultrahigh dependable systems, especially automated software synthesis and testing, embedded real-time process-control and telecommunications systems and high-assurance systems engineering. Dr. Bastani was the Editor-in-Chief of the IEEE Transactions on Knowledge and Data Engineering (IEEE-TKDE). He is currently an emeritus EIC of IEEE-TKDE and is on the editorial board of the International Journal of Artificial Intelligence Tools, the International Journal of Knowledge and Information Systems and the Springer-Verlag series on Knowledge and Information Management. He was the program cochair of the 1997 IEEE Symposium on Reliable Distributed Systems, 1998 IEEE International Symposium on Software Reliability Engineering, 1999 IEEE Knowledge and Data Engineering Workshop, 1999 International Symposium on Autonomous Decentralised Systems, and the program chair of the 1995 IEEE International Conference on Tools with Artificial Intelligence. He has been on the program and steering committees of several conferences and workshops and on the editorial boards of the IEEE Transactions on Software Engineering, IEEE Transactions on Knowledge and Data Engineering and the Oxford University Press High Integrity Systems Journal. I-Ling Yen received her B.S. degree from Tsing-Hua University, Taiwan, and her M.S. and Ph.D. degrees in Computer Science from the University of Houston. She is currently an Associate Professor of Computer Science at University of Texas at Dallas. Dr. Yen's research interests include fault-tolerant computing, security systems and algorithms, distributed systems, Internet technologies, E-commerce and self-stabilising systems. She has published over 100 technical papers in these research areas and received many research awards from NSF, DOD, NASA and several industry companies. She has served as Program Committee member for many conferences and Program Chair/Cochair for the IEEE Symposium on Application-Specific Software and System Engineering & Technology, IEEE High Assurance Systems Engineering Symposium, IEEE International Computer Software and Applications Conference, and IEEE International Symposium on Autonomous Decentralized Systems. She has also served as a guest editor for a theme issue of IEEE Computer devoted to high-assurance systems.     

A metamodel for modeling system features and their refinement, constraint and interaction relationships

This paper presents a metamodel for modeling system features and relationships between features. The underlying idea of this metamodel is to employ features as first-class entities in the problem space of software and to improve the customization of software by explicitly specifying both static and dynamic dependencies between system features. In this metamodel, features are organized as hierarchy structures by the refinement relationships, static dependencies between features are specified by the constraint relationships, and dynamic dependencies between features are captured by the interaction relationships. A first-order logic based method is proposed to formalize constraints and to verify constraints and customization. This paper also presents a framework for interaction classification, and an informal mapping between interactions and constraints through constraint semantics. Hong Mei received the BSc and MSc degrees in computer science from the Nanjing University of Aeronautics and Astronautics (NUAA), China, in 1984 and 1987, respectively, and the PhD degree in computer science from the Shanghai Jiao Tong University in 1992. He is currently a professor of Computer Science at the Peking University, China. His current research interests include Software Engineering and Software Engineering Environment, Software Reuse and Software Component Technology, Distributed Object Technology, and Programming Language. He has published more than 100 technical papers. Wei Zhang received the BSc in Engineering Thermophysics and the MSc in Computer Science from the Nanjing University of Aeronautics and Astronautics (NUAA), China, in 1999 and 2002, respectively. He is currently a PhD student at the School of Electronics Engineering and Computer Science of the Peking University, China. His research interests include feature-oriented requirements modeling, feature-driven software architecture design and feature-oriented software reuse. Haiyan Zhao received both the BSc and the MSc degree in Computer Science from the Peking Univeristy, China, and the Ph.D degree in Information Engineering from the University of Tokyo, Japan. She is currently an associate professor of Computer Science at the Peking University, China. Her research interests include Software Reuse, Domain Engineering, Domain Specific Languange and Program Transformation.     

Chance discovery and scenario analysis

Scenario analysis is often used to identify possible chance events. However, no formal, computational theory yet exists for scenario analysis. In this paper, we commence development of such a theory by defining a scenario in an argumentation context, and by considering the question of when two scenarios are the same. Peter McBurney, Ph.D.: He is a lecturer in the Department of Computer Science at the University of Liverpool, UK. He has a first degree in Pure Mathematics and Statistics from the Australian National University, Canberra, and a Ph.D in Artificial Intelligence from the University of Liverpool. His Ph.D research concerned the design of protocols for rational interaction between autonomous software agents, and he has several publications in this area. Prior to completing his Ph.D he worked as a consultant to major telecommunications network operating companies, primarily in mobile and satellite communications, where his work involved strategic marketing programming. Simon Parsons, Ph.D.: He is currently visiting the Sloan School of Management at Massachusetts Institute of Technology (MIT) and is a Visiting Professor at the University of Liverpool, UK. He holds a first degree in Engineering from Cambridge University, and an MSc and Ph.D in Artificial Intelligence from the University of London. In 1998, he was awarded the Young Engineer Achievement Medal of the British Institution of Electrical Engineers (IEE), the largest professional engineering society in Europe. He has published 4 books and over 100 articles on autonomous agents and multi-agent systems, uncertainty formalisms, risk and decision-making.     

Hiding a halftone secret image in two camouflaged halftone images

In this paper, we shall propose a method to hide a halftone secret image into two other camouflaged halftone images. In our method, we adjust the gray-level image pixel value to fit the pixel values of the secret image and two camouflaged images. Then, we use the halftone technique to transform the secret image into a secret halftone image. After that, we make two camouflaged halftone images at the same time out of the two camouflaged images and the secret halftone image. After overlaying the two camouflaged halftone images, the secret halftone image can be revealed by using our eyes. The experimental results included in this paper show that our method is very practicable. The text was submitted by the authors in English. Wei-Liang Tai received his BS degree in Computer Science in 2002 from Tamkang University, Tamsui, Taiwan, and his MS degree in Computer Science and Information Engineering in 2004 from National Chung Cheng University, Chiayi, Taiwan. He is currently a PhD student of Computer Science and Information Engineering at National Chung Cheng University. His research fields are image hiding, digital watermarking, and image compression. Chi-Shiang Chan received his BS degree in Computer Science in 1999 from National Cheng Chi University, Taipei, Taiwan, and his MS degree in Computer Science and Information Engineering in 2001 from National Chung Cheng University, Chiayi, Taiwan. He is currently a PhD student of Computer Science and Information Engineering at National Chung Cheng University. His research fields are image hiding and image compression. Chin-Chen Chang received his BS degree in Applied Mathematics in 1977 and his MS degree in Computer and Decision Sciences in 1979, both from National Tsing Hua University, Hsinchu, Taiwan. He received his PhD in Computer Engineering in 1982 from National Chiao Tung University, Hsinchu, Taiwan. During the academic years of 1980–1983, he was on the faculty of the Department of Computer Engineering at National Chiao Tung University. From 1983–1989, he was on the faculty of the Institute of Applied Mathematics, National Chung Hsing University, Taichung, Taiwan. From 1989 to 2004, he has worked as a professor in the Institute of Computer Science and Information Engineering at National Chung Cheng University, Chiayi, Taiwan. Since 2005, he has worked as a professor in the Department of Information Engineering and Computer Science at Feng Chia University, Taichung, Taiwan. Dr. Chang is a fellow of the IEEE, a fellow of the IEE, and a member of the Chinese Language Computer Society, the Chinese Institute of Engineers of the Republic of China, and the Phi Tau Phi Society of the Republic of China. His research interests include computer cryptography, data engineering, and image compression.     

Applying and combining three different aspect Mining Techniques

Understanding a software system at source-code level requires understanding the different concerns that it addresses, which in turn requires a way to identify these concerns in the source code. Whereas some concerns are explicitly represented by program entities (like classes, methods and variables) and thus are easy to identify, crosscutting concerns are not captured by a single program entity but are scattered over many program entities and are tangled with the other concerns. Because of their crosscutting nature, such crosscutting concerns are difficult to identify, and reduce the understandability of the system as a whole. In this paper, we report on a combined experiment in which we try to identify crosscutting concerns in the JHotDraw framework automatically. We first apply three independently developed aspect mining techniques to JHotDraw and evaluate and compare their results. Based on this analysis, we present three interesting combinations of these three techniques, and show how these combinations provide a more complete coverage of the detected concerns as compared to the original techniques individually. Our results are a first step towards improving the understandability of a system that contains crosscutting concerns, and can be used as a basis for refactoring the identified crosscutting concerns into aspects. M. Ceccato is a PhD student in ITC-irst in Trento, Italy. He received his degree in Software Engineering from the University of Padova, Italy, in 2003. The master thesis concerned the Re-engineering of an existing big-sized data warehouse application. The project was developed in the Information Technology department in Alcoa Servizi. His research interests are on source code analysis and manipulation, especially for the the migration of object-oriented code to aspect-oriented programming. He collaborates with King’s College London and Loyola College in Maryland on the automatic support for this migration process. He has been involved in the organization and in the program committee of a number of AOP-related events, such as Late Workshop, in Chicago (2005) and in Bonn, Germany (2006), held within the major Aspect Oriented Programming conference (AOSD) and 3rd European Workshop on Aspects in Software (EWAS’06) in Enschede, The Netherlands. Marius Marin is a Ph.D. researcher in the Software Evolution Reseach Laboratory at Delft University of Technology, the Netherlands. He was granted an engineering degree by the Technical University of Civil Engineering, Bucharest, in 2000, and Licentiate in Economic Computer Science from the Academy of Economic Studies, Bucharest, in 2002. Before starting his Ph.D. studies, he worked as a software engineer in industry. His main research interests are in the area of reverse engineering, software modularization and modeling, and aspect-oriented software development. He is the main author of the publicly available aspect mining tool FINT and he publishes at international conferences in the aforementioned topics. He has been involved in program- and organizing committees of several workshops related to aspect mining. Kim Mens obtained his Ph.D. in Computer Science at the Vrije Universiteit Brussel, on “architectural conformance checking,” for which he used a declarative meta-programming approach. After his Ph.D. he became a full-time professor (chargé de cours) at the Université catholique de Louvain-la-Neuve (UCL). In addition to his current interest in logic meta-programming and intensional views, Kim Mens is one of the originators of the reuse contracts technique for automatically detecting conflicts in evolving software. He has been formally involved in several research networks related to software evolution. He has a strong interest in object-oriented and aspect-oriented software development and has actively participated in the organization of several workshops and conferences on those topics. He combines all these different research interests under the common denominator of co-evolution (between source code and earlier life-cycle software artifacts). Other research topics that fit this common theme and in which he is interested are software architecture, software maintenance, reverse engineering, software transformation, software restructuring and renovation, aspect mining and evolution of aspect programs. L. Moonen is an assistant professor in the Software Evolution Research Lab at Delft University of Technology and a researcher at the Centre for Mathematics and Computer Science (CWI), the Netherlands. His research interests are the design and development of advanced program analysis tools and techniques that support development, maintenance and evolution of large software systems. Concrete topics include the reverse engineering and exploration of views on software systems and their use for understanding and assessing software quality attributes such as evolvability, reliability and security. Dr. Moonen received an MSc (cum laude, Computer Science, 1996) and PhD (Computer Science, 2002) from the University of Amsterdam. He is one of the founders of the Software Improvement Group, a company that specializes in tools and consultancy to help organizations solve their legacy problems. He publishes regularly at, and serves on organizing-, steering- and program committees of, international workshops and conferences on reverse engineering (WCRE), source code analysis (SCAM), software maintenance (ICSM), program understanding (ICPC), reengineering (CSMR), aspect mining (Dagstuhl 06302, TEAM) and software security (CoBaSSA). Paolo Tonella is a senior researcher at ITC-irst, Trento, Italy. He received his laurea degree cum laude in Electronic Engineering from the University of Padova, Italy, in 1992, and his Ph.D. degree in Software Engineering from the same University, in 1999, with the thesis “Code Analysis in Support to Software Maintenance.” Since 1994 he has been a full time researcher of the Software Engineering group at ITC-irst. He participated in several industrial and European Community projects on software analysis and testing. He is the author of “Reverse Engineering of Object Oriented Code,” Springer, 2005. His current research interests include reverse engineering, aspect oriented programming, empirical studies, Web applications and testing. Tom Tourwé obtained the degree of Licentiate in Computer Science in 1997 and Ph.D. in Science in 2002 at the Vrije Universiteit Brussel. He is currently associated to the Centrum voor Wiskunde en Informatica, based in Amsterdam, The Netherlands, where he works as a post- doctoral researcher in the Ideals project. His main research interests lie in the broad area of software engineering, and include aspect-oriented software evolution and re-engineering in particular. He published several peer-reviewed articles on these topics in international journals and conferences, and organised a number of workshops on those themes.