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.     

An experiment on the role of graphical elements in architecture visualization

The evolution and maintenance of large-scale software systems requires first an understanding of its architecture before delving into lower-level details. Tools facilitating the architecture comprehension tasks by visualization provide different sets of configurable, graphical elements to present information to their users. We conducted a controlled experiment that exemplifies the critical role of such graphical elements when aiming at understanding the architecture. In our setting, a different configuration of graphical elements had significant influence on program comprehension tasks. In particular, a 63% gain in effectiveness in architectural analysis tasks was achieved simply by changing the configuration of the graphical elements of the same tool. Based on the results, we claim that significant effort should be spent on the configuration of architecture visualization tools and that configurability should be a requirement for such tools.

The internal consistency and precedence of key process areas in the capability maturity model for software

Evaluating the reliability of maturity level (ML) ratings is crucial for providing confidence in the results of software process assessments. This study investigates the dimensions underlying the maturity construct in the Capability Maturity Model (CMM) for Software (SW-CMM) and estimates the internal consistency of each dimension. The results suggest that SW-CMM maturity is a three-dimensional construct, with “Project Implementation” representing the ML 2 key process areas (KPAs), “Organization Implementation” representing the ML 3 KPAs, and “Quantitative Process Implementation” representing the KPAs at MLs 4 and 5. The internal consistency for each of the three dimensions as estimated by Cronbach’s alpha exceeds the recommended value of 0.9. Based on those results, this study builds and tests a theoretical model which posits that the achievement of lower ML KPAs sustains the implementation of higher ML KPAs. Results of path analysis using partial least squares (PLS) support the theoretical model and provide detailed understanding of the process improvement path. The analysis is based on 676 CMM-Based Appraisal for Internal Process Improvement (CBA IPI) assessments.

Developing new processes for COTS-based systems

Although commercial off-the-shelf (COTS) products are becoming increasingly popular, little information is available on how they affect existing software development processes or what new processes are needed. At Carnegie Mellon University's Software Engineering Institute (SEI), we are developing a process framework for working with COTS-based systems     

The importance of generalizability for anomaly detection

In security-related areas there is concern over novel “zero-day” attacks that penetrate system defenses and wreak havoc. The best methods for countering these threats are recognizing “nonself” as in an Artificial Immune System or recognizing “self” through clustering. For either case, the concern remains that something that appears similar to self could be missed. Given this situation, one could incorrectly assume that a preference for a tighter fit to self over generalizability is important for false positive reduction in this type of learning problem. This article confirms that in anomaly detection as in other forms of classification a tight fit, although important, does not supersede model generality. This is shown using three systems each with a different geometric bias in the decision space. The first two use spherical and ellipsoid clusters with a k-means algorithm modified to work on the one-class/blind classification problem. The third is based on wrapping the self points with a multidimensional convex hull (polytope) algorithm capable of learning disjunctive concepts via a thresholding constant. All three of these algorithms are tested using the Voting dataset from the UCI Machine Learning Repository, the MIT Lincoln Labs intrusion detection dataset, and the lossy-compressed steganalysis domain. Gilbert “Bert” Peterson is an Assistant Professor of Computer Engineering at the Air Force Institute of Technology. Dr. Peterson received a BS degree in Architecture, and an M.S. and Ph.D. in Computer Science at the University of Texas at Arlington. He teaches and conducts research in digital forensics and artificial intelligence. Brent McBride is a Communications and Information Systems officer in the United States Air Force. He received a B.S. in Computer Science from Brigham Young University and an M.S. in Computer Science from the Air Force Institute of Technology. He currently serves as Senior Software Engineer at the Air Force Wargaming Institute.     

Dual-coding representations for robot vision programming in Tekkotsu

We describe complementary iconic and symbolic representations for parsing the visual world. The iconic pixmap representation is operated on by an extensible set of “visual routines” (Ullman, 1984; Forbus et al., 2001). A symbolic representation, in terms of lines, ellipses, blobs, etc., is extracted from the iconic encoding, manipulated algebraically, and re-rendered iconically. The two representations are therefore duals, and iconic operations can be freely intermixed with symbolic ones. The dual-coding approach offers robot programmers a versatile collection of primitives from which to construct application-specific vision software. We describe some sample applications implemented on the Sony AIBO. David S. Touretzky is a Research Professor in the Computer Science Department and the Center for the Neural Basis of Cognition at Carnegie Mellon University. He earned his B.A. in Computer Science from Rutgers University in 1978, and his M.S. (1979) and Ph.D. (1984) in Computer Science from Carnegie Mellon. Dr. Touretzky’s research interests are in computational neuroscience, particularly representations of space in the rodent hippocampus and related structures, and high level primitives for robot programming. He is presently developing an undergraduate curriculum in cognitive robotics based on the Tekkotsu software framework described in this article. Neil S. Halelamien earned a B.S. in Computer Science and a B.S. in Cognitive Science at Carnegie Mellon University in 2004, and is currently pursuing his Ph.D. in the Computation & Neural Systems program at the California Institute of Technology. His research interests are in studying vision from both a computational and biological perspective. He is currently using transcranial magnetic stimulation to study visual representations and information processing in visual cortex. Ethan J. Tira-Thompson is a graduate student in the Robotics Institute at Carnegie Mellon University. He earned a B.S. in Computer Science and a B.S. in Human-Computer Interaction in 2002, and an M.S. in Robotics in 2004, at Carnegie Mellon. He is interested in a wide variety of computer science topics, including machine learning, computer vision, software architecture, and interface design. Ethan’s research has revolved around the creation of the Tekkotsu framework to enable the rapid development of robotics software and its use in education. He intends to specialize in mobile manipulation and motion planning for the completion of his degree. Jordan J. Wales is completing a Master of Studies in Theology at the University of Notre Dame. He earned a B.S. in Engineering (Swarthmore College, 2001), an M.Sc. in Cognitive Science (Edinburgh, UK, 2002), and a Postgraduate Diploma in Theology (Oxford, UK, 2003). After a year as a graduate research assistant in Computer Science at Carnegie Mellon, he entered the master’s program in Theology at Notre Dame and is now applying to doctoral programs. His research focus in early and medieval Christianity is accompanied by an interest in medieval and modern philosophies of mind and their connections with modern cognitive science. Kei Usui is a masters student in the Robotics Institute at Carnegie Mellon University. He earned his B.S. in Physics from Carnegie Mellon University in 2005. His research interests are reinforcement learning, legged locomotion, and cognitive science. He is presently working on algorithms for humanoid robots to maintain balance against unexpected external forces.     

Generation of Discrete Bicubic G^1 B-Spline Ship Hullform Surfaces from a Given Curve Network Using Virtual Iso-Parametric Curves

We propose a method that automatically generates discrete bicubic G^1 continuous B-spline surfaces that interpolate the curve network of a ship huliform.First,the curves in the network are classified into two types;boundary curves and ＂reference curves＂,The boundary curves correspond to a set of rectangular（or triangular）topological type that can be representes with tensot-product （or degenerate）B-spline surface patches.Next,in the interior of the patches,surface fitting points and cross boundary derivatives are estimated from the reference curves by constructing ＂virtual＂isoparametric curves.Finally,a discrete G^1 continuous B-spline surface is gencrated by a surface fitting algorithm.Several smooth ship hullform surfaces generated from curve networks corresponding to actual ship hullforms demonstrate the quality of the method.     

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.     

Evaluating the CMM Level 3 KPA of Intergroup Coordination: A theory-based approach

This paper examines the Intergroup Coordination key process area (KPA) for theoretical significance and measurability. The Software Engineering Institute (SEI) has developed a framework called the Capability Maturity Model (CMM) which enables organizations to measure their “maturity” in doing software engineering. The CMM is not theoretically derived. It is, however, a result of years of anecdotal evidence collected from practitioners. This paper compares the Intergroup Coordination KPA to the body of literature on coordination and measures it using theoretically derived determinants. These determinants are then evaluated for possible relationships to productivity factors that indicate business process support. This revised version was published online in July 2006 with corrections to the Cover Date.     

Comparative analysis of function approximation methods applied to image processing

Application of nonlinear methods of multivariate regression approximation (neural networks, functions linear in fitting parameters, and hierarchical approximation) is considered to problems of image filtering based on a priori information in the form of matched pairs of images (“ideal” and “degraded”). The methods are compared with regard to their efficiency. Vasilii N. Kopenkov. Born 1978. Graduated from the Samara State Aerospace University (SSAU) in 2001. Assistant Professor at the Chair of Geoinformatics, SSAU, and a Junior Researcher at the Institute of Image Processing Systems, Russian Academy of Sciences. Scientific interests: image processing and pattern recognition. Author of four papers. Member of the Russian Federation Association for Pattern Recognition and Image Analysis. Andrei V. Chernov. Born 1975. Graduated from the Samara State Aerospace University (SSAU) in 1998. Received candidate’s degree (Cand. Sc. (Eng.)) in 2004. Assistant Professor at the Chair of Geoinformatics, SSAU, and a Researcher at the Institute of Image Processing Systems, Russian Academy of Sciences. Scientific interests: image processing, pattern recognition, and geoinformation systems. Author of more than 50 publications, including 11 papers in journals, and a co-author of a monograph. Member of the Russian Federation Association for Pattern Recognition and Image Analysis. Vladislav V. Sergeev. Born 1951. Graduated from the Kuibyshev Aviation Institute (now, the Samara State Aerospace University). Received doctoral degree (Dr. Sc. (Eng.)) in 1993. Head of Laboratory of Mathematical Methods of Image Processing, Institute of Image Processing Systems, Russian Academy of Sciences. Scientific interests: digital signal processing, image analysis, pattern recognition, and geoinformatics. Author of more than 150 publications, including about 40 papers in journals, and a co-author of 2 monographs. Chair of the Volga-region Branch of the Russian Federation Association for Pattern Recognition and Image Analysis. Corresponding Member of the Russian Ecological Academy and the Russian Academy of Engineering, member of SPIE (The International Society for Optical Engineering), a winner of the Samara District Award for Science and Engineering.     

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).     

基于COM+的信息系统软件体系结构设计的市场模式

基于组件的多层客户服务器结构信息系统软件体系结构设计是信息系统开发中的新问题,它不同于面向对象系统的软件体系结构设计,更不同于结构化方法中软件模块结构设计。该文提出了一种基于COM+组件的信息系统软件体系结构设计模式———市场模式,并详细地论述了市场模式在信息系统体系结构各层次上应用的基本原理和方法。     

A grid-oriented genetic algorithm framework for bioinformatics

In this paper, we propose a framework for enabling for researchers of genetic algorithms (GAs) to easily develop GAs running on the Grid, named “Grid-Oriented Genetic algorithms (GOGAs)”, and actually “Gridify” a GA for estimating genetic networks, which is being developed by our group, in order to examine the usability of the proposed GOGA framework. We also evaluate the scalability of the “Gridified” GA by applying it to a five-gene genetic network estimation problem on a grid testbed constructed in our laboratory. Hiroaki Imade: He received his B.S. degree in the department of engineering from The University of Tokushima, Tokushima, Japan, in 2001. He received the M.S. degree in information systems from the Graduate School of Engineering, The University of Tokushima in 2003. He is now in Doctoral Course of Graduate School of Engineering, The University of Tokushima. His research interests include evolutionary computation. He currently researches a framework to easily develop the GOGA models which efficiently work on the grid. Ryohei Morishita: He received his B.S. degree in the department of engineering from The University of Tokushima, Tokushima, Japan, in 2002. He is now in Master Course of Graduate School of Engineering, The University of Tokushima, Tokushima. His research interest is evolutionary computation. He currently researches GA for estimating genetic networks. Isao Ono, Ph.D.: He received his B.S. degree from the Department of Control Engineering, Tokyo Institute of Technology, Tokyo, Japan, in 1994. He received Ph.D. of Engineering at Tokyo Institute of Technology, Yokohama, in 1997. He worked as a Research Fellow from 1997 to 1998 at Tokyo Institute of Technology, and at University of Tokushima, Tokushima, Japan, in 1998. He worked as a Lecturer from 1998 to 2001 at University of Tokushima. He is now Associate Professor at University of Tokushima. His research interests include evolutionary computation, scheduling, function optimization, optical design and bioinformatics. He is a member of JSAI, SCI, IPSJ and OSJ. Norihiko Ono, Ph.D.: He received his B.S. M.S. and Ph.D. of Engineering in 1979, 1981 and 1986, respectively, from Tokyo Institute of Technology. From 1986 to 1989, he was Research Associate at Faculty of Engineering, Hiroshima University. From 1989 to 1997, he was an associate professor at Faculty of Engineering, University of Tokushima. He was promoted to Professor in the Department of Information Science and Intelligent Systems in 1997. His current research interests include learning in multi-agent systems, autonomous agents, reinforcement learning and evolutionary algorithms. Masahiro Okamoto, Ph.D.: He is currently Professor of Graduate School of Systems Life Sciences, Kyushu University, Japan. He received his Ph.D. degree in Biochemistry from Kyushu University in 1981. His major research field is nonlinear numerical optimization and systems biology. His current research interests cover system identification of nonlinear complex systems by using evolutional computer algorithm of optimization, development of integrated simulator for analyzing nonlinear dynamics and design of fault-tolerant routing network by mimicking metabolic control system. He has more than 90 peer reviewed publications.     

Platitudes and attitudes

In October 2002 I attended the Ninth Monterey Software Engineering workshop held in Venice, Italy. This year’s theme was titled “Radical Innovations of Software and Systems Engineering in the Future.” In preparing my talk for the workshop, I thought hard about what I could possibly say on this topic that would not sound stupid. I certainly thought it would be awfully presumptious of me to predict how people will or should be developing software in the future. More easily, I could imagine what the systems of tomorrow will look like and who will be developing them, though anything I would say would sound like platitudes. I could also state some strong opinions about what matters and what doesn’t in the process of software development. Stating such attitudes would at least provoke some discussion. Hence, what follows captures some of what I said at the workshop. Published online: 10 April 2003     

Secure software infrastructure in the internet age

The rapid growth and penetration of the Internet are now leading us to a world where networks are ubiquitous and everything is connected. Breaking the distance barrier by the ubiquitous connection, however, is a two-edged sword. Our network infrastructure today is still fragile and thus “everything is connected” may simply mean “everything can be attacked from whatever place on the earth.” In this paper, we first point out the importance and inherent problems of software systems that underlay open and extensible networks, especially the Internet. We put emphasis on software since software vulnerabilities account for most attacks, incidents, or even disasters on the Internet today. Next we present general ideas of promising techniques in defense of software systems, including theoretical, language-based, and runtime solutions. Finally, we show our experience in developing a secure mail system. Etsuya Shibayama, D.Sc.: He is a professor of the Graduate School of Information Science and Engineering at Tokyo Institute of Technology. He received B.Sc. and M.Sc. in mathematical sciences from Kyoto University in 1981 and 1983, respectively, and D.Sc. in information science from the University of Tokyo in 1991. He is interested in various topics in software including design and implementation of textual and visual programming languages, system software, and user interface software. Recently, he has been doing research on language-based software security and methodologies for building secure software. Akinori Yonezawa, Ph.D.: He is a Professor of computer science at Department of Computer Science, the University of Tokyo. He received his Ph.D. in Computer Science form the Massachusetts Institute of Technology in 1977. His current major research interests are in the areas of concurrent/parallel computation models, programming languages, object-oriented computing and distributed computing. He is the designer of and object-oriented concurrent language ABCL/1 and the editor of several books and served as an associate editor of ACM Transaction of Programming Language and Systems (TOPLAS). Since 1998, he has been an ACM Fellow.     

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 Interactive Learning Algorithm for Acquisition of Concepts Represented as CFL

In this paper,an interactive learning algorithm of context-frmm language is presented.This algorithm is designed especially for system SAQ,which is a system for formal secification acquisition and verification.As the kernel of concept acquisition subsystem(SAQ/CL)of SAQ,the algorithm has been implemented on SUN SPARC workstation.The grammar to be obtained can represent sentence structure naturally.