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Software Maintenance: Predicting cost/effort of changes

Software code bases evolve over time with changes
resulting from bug fixes, new functionalities, infrastructure upgrades, or new standards.  One of the major challenges in the maintenance of evolving software is accurately estimating the resources required and the cost for validating changes and their effects. These estimates are crucial for planning project schedules, allocating resources, software reliability, monitoring and control.
Cost models estimating maintenance effort and development effort have been developed in the past. Nevertheless, these models cannot be used for predicting cost of validating and testing changes.
This project will look at defining cost models that accurately estimate the cost of regression testing using a combination of static analysis and past project history.  The project will empirically evaluate the accuracy of estimates from this cost model.

Potential Supervisor: Ajitha Rajan

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