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In 1996, USC switched its core two-semester software engineering coursefrom a hypothetical-project, homework-and-exam course based on the Bloom taxonomyof educational objectives (knowledge, comprehension, application, analysis,synthesis, and evaluation). The revised course is a real-client team-projectcourse based on the CRESST model of learning objectives (content understanding,problem solving, collaboration, communication, and self-regulation). We usedthe CRESST cognitive demands analysis to determine the necessary student skillsrequired for software risk management and the other major project activities,and have been refining the approach over the last 5 years of experience, includingrevised versions for one-semester undergraduate and graduate project courseat Columbia. This paper summarizes our experiences in evolving the risk management aspectsof the project course. These have helped us mature more general techniquessuch as risk-driven specifications, domain-specific simplifier and complicatorlists, and the schedule as an independent variable (SAIV) process model. Thelargely positive results in terms of review of pass/fail rates, client evaluations,product adoption rates, and hiring manager feedback are summarized as well. [ABSTRACT FROM AUTHOR]

Software pervades the growing web of computers and communications systems providing diverse services, personal, commercial, financial, public, and entertainment services. Providing timely, cost-effective, high-quality software for these diverse services requires the best possible technology and practice that the software engineering community can provide. The 1999 International Conference on Software Engineering (ICSE) was held in Los Angeles, California. Following the lead of previous ICSE conferences, the aim of ICSE held in the year 1999 was to bring together software engineering practitioners and researchers to present and discuss the most promising approaches for meeting the software challenges of the next century. The February 2001, issue of the journal IEEE Transactions on Software Engineering presents a special section with some of the best papers of the conference held in the year 1999. These papers were selected through an additional review process conducted after the conference. The ICSE '99 program committee selected a number of the best quality papers. The authors of these papers were invited to submit extended versions of their papers for consideration for journal publication.

Focuses on the agenda for the 1999 International Conference of Software Engineering in Los Angeles, California. Enhancement of the industrial presentation programs; List of participating research papers; Topics and writers for the research papers.

The Symposium on Foundations in Software Engineering is an annual conference sponsored by Association for Computing Machinery, a computer portal and dedicated to the presentation of innovative research results contributing to an engineering discipline for software systems. This special section of the July 1998 issue of the journal IEEE Transactions on Software Engineering features three of the best papers from the fourth symposium, held in October 1996 in San Francisco, California. During its first half-decade, research results presented at this conference have covered engineering research topics. However, a number of distinguishing properties tend to characterize the best of the papers and have helped set the standards for high-quality software engineering research. The three papers in this special section illustrate these properties. One of the critical challenges for software engineering research is to find practical tools that help system builder restructure existing systems. Mark Moriconi was general chair for the symposium and deserves considerable credit for its success.

The Third International Conference on Data Engineering was held in Los Angeles, California on February 2 to 6, 1987. The conference was designed as an international forum for bringing together researchers, developers, managers, strategic planners and other users with an interest in the research, design and development of data engineering methodologies, strategies and systems. Its scope includes computer science, artificial intelligence, electrical engineering, and computer engineering. It featured papers from all major areas of data engineering, including database design and modeling, performance evaluation, algorithms, integrity, security, fault tolerance, query language, artificial intelligence approaches, knowledge bases, database machines, distributed databases and data engineering applications.