ICS2002-07-01: Supporting development of highly dependable software through continous, automated, in-process, and individualized software measurement validation, P. Johnson
Highly dependable software is, by nature, predictable. For example, one can predict with confidence the circumstances under which the software will work and the circumstances under which it will fail. Empirically-based approaches to creating predictable software are based on two assumptions:(1) historical data can be used to develop and calibrate models that generate empirical predictions, and (2) there exists relationships between internal attributes of the software (i.e. immediately measurable process and product attributes such as size, effort, defects, complexity,and so forth) and external attributes of the software (i.e. abstract and/or non-immediately measurable attributes, such as "quality", the time and circumstances of a specific component's failure in the field, and so forth). Software measurement validation is the process of determining a predictive relationship between available internal attributes and correspondingly useful external attributes and the conditions under which this relationship holds.
This report proposes research whose general objective is to design, implement, and validate software measures within a development infrastructure that supports the development of highly dependable software systems. The measures and infrastructure are designed to support dependable software development in two ways: (1) They will support identification of modules at risk for being fault-prone, enabling more efficient and effective allocation of quality assurance resources, and (2) They will support incremental software development through continuous monitoring,notifications, and analyses. Empirical assessment of these methods and measures during use on the Mission Data System project at Jet Propulsion Laboratory will advance the theory and practice of dependable computing and software measurement validation and provide new insight into the technological and methodological problems associated with the current state of the art.
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