Browsing by Author "Chappell, Bryan L."
Now showing 1 - 2 of 2
Results Per Page
Sort Options
- Definition and validation of software complexity metrics for AdaChappell, Bryan L. (Virginia Tech, 1989-11-05)One of the major goals of software engineering is to control the development and maintenance of software products. With the growing use and importance of the Ada programming language, control over the software life cycle of Ada systems is becoming even more important. Software complexity metrics have been developed to aid software engineers in the design and development of software systems. This research defines metrics for Ada and uses an automated analysis tool to calculate them. This tool can be used by the software engineer to help maintain control over Ada software products. The validation of this tool was performed by analyzing a medium-sized commercial Ada product. The flow of control and flow of information through the use of Ada packages can be measured. The results show that software complexity metrics can be applied to Ada and produce meaningful results.
- Measurement of ADA Throughout the Software Development Life CycleChappell, Bryan L.; Henry, Sallie M.; Mayo, Kevin A. (Department of Computer Science, Virginia Polytechnic Institute & State University, 1989)Quality enhancement has now become a major factor in software production. Software metrics have demonstrated their ability to predict source code complexity at design time and to predict maintainability of a software system from source code. Obviously metrics can assist software developers in the enhancement of quality. Tools which automatically generate metrics for Ada are increasing in popularity. This paper describes an existing tool which produces software metrics for Ada that may be used throughout the software development life cycle. This tool, while calculating established metrics, also calculates a new structure metric that is designed to capture communication interface complexity. Measuring designs written using Ada as a PDL allows designers early feedback on possible problem areas in addition to giving direction on testing strategies.