Code Delay in Legacy Software Systems: Measurement, Models, and Statistical Strategies

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This research program is directed toward key problems regarding a massive, but largely unappreciated problem -- decay of computer software. Three key problems to be investigated include describing code decay, identifying factors that cause code decay, and evaluating effects of reductions in code decay. The research team, which represents a partnership between AT&T and the National Institute of Statistical Sciences, will develop indices (measures) of code decay that reflect key behavioral and managerial characteristics in the software development process. Changes in controllable (for example, organizational) factors will change the indices, which in turn impact key responses: cost, time and quality. By incorporating adequate behavioral and organizational factors, as well as code characteristics, we will develop techniques to identify relevant factors and evaluate their effects on code decay. The research team is cross-disciplinary, including experts in software engineering, behavioral issues, organizational theory, management and statistics. Statistics -- especially measurement, modeling, prediction, and experimentation -- serves as the `glue` and enabling technology for progress on problems of code decay, and as the means to apply paradigms from the traditional sciences to software engineering. Statistic strategies will be developed and used to model and control the effects of design decisions, software architecture and organizational factors. The products will be the basis for management tools for achieving reductions in cost and development interval, increases in software quality and enhanced capability to predict cost, interval and quality.