VTechWorks staff will be away for the Thanksgiving holiday beginning at noon on Wednesday, November 27, through Friday, November 29. We will resume normal operations on Monday, December 2. Thank you for your patience.

Browsing by Author "Wake, Steven A."

Now showing 1 - 7 of 7
  • Thumbnail Image
    A Grassroots Approach to Graduate Teaching Assistant Mentoring
    Mayo, Kevin A.; Wake, Steven A. (Department of Computer Science, Virginia Polytechnic Institute & State University, 1993)
    Graduate students, whether master's or doctoral candidates, benefit greatly from their academic experiences. However, graduate school is not limited to course work and research, but it also includes teaching experiences as graduate teaching assistants (GTAs). Although GTAs are technically proficient in course materials, other factors can cause teaching experiences to go awry for them, their students, or the course supervisor. These factors arise out of a need for quality training on issues including pedagogy, interaction resolution, organizational concerns, and professional matters. This paper provides a grassroots approach to improve teachine techniques through GTA mentoring. GTAs are encouraged, with materials supplied here, to seek out and consult with more experienced GTAs who will serve as their mentors.
  • Thumbnail Image
    A Model Based on Software Quality Factors which Predicts Maintainability
    Wake, Steven A.; Henry, Sallie M. (Department of Computer Science, Virginia Polytechnic Institute & State University, 1988-05-01)
    Computer scientists are continually attempting to improve software system development. Systems are developed in a top-down fashion for better modularity and understandability. Performance enhancements are implemented for more speed. One area in which a great deal of effort is being devoted is software maintenance. Brooks estimates that fifty percent of the development cost of a software system is for maintenance activities [BROF82]. Since a large portion of the effort of a system is devoted to maintenance, it is reasonable to assume that driving down maintenance costs would drive down the overall cost of the system. Measuring the complexity of a software system could aid in this attempt. By lowering the complexity of the system or of subsystems within the system, it may be possible to reduce the amount of maintenance necessary. Software quality metrics were developed to measure the complexity of software systems. This study relates the complexity of the system as measured by software metrics to the amount of maintenance necessary to that system. We have developed a model which uses several software quality metrics as parameters to predict maintenance activity.
  • Thumbnail Image
    Predicting maintainability with software quality metrics
    Wake, Steven A. (Virginia Tech, 1988-09-15)
    Maintenance of software makes up a large fraction of the time and money spent in the software life cycle. By reducing the need for maintenance these costs can also be reduced. Predicting where maintenance is likely to occur can, help to reduce maintenance by prevention. This thesis details a study of the use of software quality;metrics to determine high complexity components in a software system. By the use of a history of maintenance done on a particular system, it is shown that a predictor equation can be developed to identify components which needed maintenance activities. This same equation can also be used to determine which components are likely to need maintenance in the future. Through the use of.these predictions and software metric complexities it should be possible to reduce the likelihood of a component needing maintenance. This might be accomplished by reducing the complexity of that component through further decomposition.
  • Thumbnail Image
    Predicting Maintainability with Software Quality Metrics
    Henry, Sallie M.; Wake, Steven A. (Department of Computer Science, Virginia Polytechnic Institute & State University, 1988)
    Maintenance of software makes up a large fraction of the time and money spent in the software life cycle. By reducing the need for maintenance these costs can also be reduced. Predicting where maintenance is likely to occur can help to reduce maintenance by prevention. This paper details a study of the use of software quality metrics to determine high complexity components in a software system. By the use of a history of maintenance done on a particular system, it is shown that a predictor equation can be developed to identify components which needed maintenance activities. This same equation can also be used to determine which components are likely to need maintenance in the future. Through the use of these predictions and software metric complexities it should be possible to reduce the likelihood of a component needing maintenance. This might be accomplished by reducing the complexity of that component through further decomposition. Even though this is only one study, this methodology of developing maintenance predictors could be applied in any environment.
  • Thumbnail Image
    A Reliability Model Incorporating Software Quality Factors
    Henry, Sallie M.; Kafura, Dennis G.; Mayo, Kevin A.; Yerneni, A.; Wake, Steven A. (Department of Computer Science, Virginia Polytechnic Institute & State University, 1988-05-01)
    In this paper we describe our initial work on a long-term project to develop and validate a reliability model and a new class of software complexity metrics which are related to this model. In contrast to previous "black box" approaches, the reliability model is novel because it incorporates knowledge about the system in the form of quantitative software complexity metrics. While the initial model uses existing software metrics a parallel effort in this project is investigating new classes of metrics, interface and dynamic metrics, which are useful in their own right but are also of particular relevance to the reliability model. The initial definitions of both the model and the metrics are given along with a description of the next research milestones.
  • Thumbnail Image
    Static and Dynamic Software Quality Metric Tools
    Mayo, Kevin A.; Wake, Steven A.; Henry, Sallie M. (Department of Computer Science, Virginia Polytechnic Institute & State University, 1990)
    The ability to detect and predict poor software quality is of major importance to software engineers, managers, and quality assurance organizations. Poor software quality leads to increased development costs and expensive maintenance. With so much attention on exacerbated budgetary constraints, a viable alternative is necessary. Software quality metrics are designed for this purpose. Metrics measure aspects of code or PDL representations, and can be collected and used throughout the life cycle [RAMC85].
  • Thumbnail Image
    The Use of Complexity Metrics Throughout the Software Lifecycle
    Henry, Sallie M.; Wake, Steven A.; Li, Wei (Department of Computer Science, Virginia Polytechnic Institute & State University, 1992-05-01)
    Software metrics attempt to uncover difficult or complex components of a software system. The hypothesis is that complex components are more difficult to understand, hence they are hard to maintain and more prone to error. Discovery of these complex components can aid the software developer in selecting which components to redesign, direct the testing effort, and indicate the maintenance effort required. Previous studies have demonstrated two main concepts: (1) there exists a high correlation between design complexity and source code complexity, and (2) metrics applied to source code have a high correlation to the maintenance activity needed. This previous research motivates us to develop a methodology which uses complexity metrics throughout the software life cycle. Programmer productivity may be increased and software development cost may be reduced if error prone software is discovered early in the life cycle.