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Tool Support For Software Process Data Management In Software Engineering Education And Industry Training

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2007 Annual Conference & Exposition


Honolulu, Hawaii

Publication Date

June 24, 2007

Start Date

June 24, 2007

End Date

June 27, 2007



Conference Session

Software Engineering Topics

Tagged Division

Software Engineering Constituent Committee

Page Count


Page Numbers

12.1496.1 - 12.1496.11



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Paper Authors


Mark Sebern Milwaukee School of Engineering

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MARK J. SEBERN is a Professor in the Electrical Engineering and Computer Science Department at the Milwaukee School of Engineering (MSOE), and was the founding program director for MSOE's undergraduate software engineering program. He has served as an ABET program evaluator for software engineering and computer engineering.

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Mark Hornick Milwaukee School of Engineering

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MARK L. HORNICK has been an Assistant Professor in the Electrical Engineering and Computer Science Department at the Milwaukee School of Engineering (MSOE) since 2004. Prior to that, he worked in private industry for 20 years, implementing and managing the incorporation of standard practices and processes into the development of industrial software products.

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NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract

Tool Support for Software Process Data Management in Software Engineering Education and Industry Training Mark J. Sebern, PhD, PE Mark L. Hornick, PhD Milwaukee School of Engineering Milwaukee School of Engineering Abstract Data management tools are necessary for effective support of disciplined software processes that make use of historical data for planning and process improvement. This paper reports describes two such tools and how they have been applied in an undergraduate software engineering program and to support software process improvement initiatives in industry. One of the tools, an open-source development project, has recently added new capabilities that may make it an attractive choice for both educators and practitioners. Introduction Software engineering programs generally incorporate courses and other learning experiences that are designed to provide breadth and depth of coverage across the discipline, addressing both practice and process. Software engineering practice deals with what software engineers do, and includes topics such as requirements analysis and specification, architecture and design, verification, and implementation. Software engineering process is concerned with how software engineers work, embracing subjects that include planning, team functioning, quality management, continuous improvement, and integration of development teams, management, and functional groups in an organization. A variety of capable and cost-effective tools have been available to support software engineering practice, such as integrated development environments, modeling tools, and testing frameworks. Until recently, however, similar high-quality tool support for software engineering process implementation has been lacking. This has been especially true for processes that include a focus on process and product metrics, such as the Personal Software Process (PSP) and the Team Software Process (TSP) developed by the Software Engineering Institute (SEI) at Carnegie Mellon University. Reliable and complete measurement data is critical to effective planning and process improvement, but data gathering and analysis that is burdensome and labor intensive will simply not be done. The SEI has developed several tools to support the PSP and TSP, but the availability of these tools has often been limited to the SEI’s commercial partners. Although some PSP tools are available for academic use10, the SEI’s definition of “academic” generally excludes industry training, use in on-line courses or off-campus programs, or with students not enrolled in a degree program. For this reason, some educators who serve multiple constituencies have been reluctant to adopt these tools. A number of other educators and researchers have surveyed available process data management support tools, or have proposed alternative methods of gathering and analyzing process data12,16,22, often with the goal of making data gathering completely invisible to the individual software developer. These surveys generally fail to identify a satisfactory tool, while the automated methods seem to encourage the use of data that is easy to gather.

Proceedings of the 2007 American Society for Engineering Education Annual Conference & Exposition Copyright © 2007, American Society for Engineering Education

Sebern, M., & Hornick, M. (2007, June), Tool Support For Software Process Data Management In Software Engineering Education And Industry Training Paper presented at 2007 Annual Conference & Exposition, Honolulu, Hawaii. 10.18260/1-2--2277

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