Can Empirical Software Engineering be Adapted to Computational Science?
Dr. Timothy Menzies, Professor of Computer Science at NC State University, has been awarded $592,129 by the National Science Foundation to support his research proposal entitled “Can Empirical SE be Adapted to Computational Science?”.
The award will run from October 1, 2019 to September 30, 2022.
Abstract – Standard methods in empirical software engineering (SE) needs to be adapted before it can be safely deployed in other domains like computational science. But what adaption methods are useful/useless? Are they cost effective? Do they work effectively across multiple data sets? We have some preliminary results suggesting that the work for (a) defect prediction but can we also adapt other tasks such as (b) test case prioritization, (c) effort estimation, (d) learning to avoid spurious false negatives from static code analysis, etc. Why is this important? Well, building software is hard. Building good software is even harder when developers have not formally studied SE (i.e. as in the case of many developers of computational science software developers). How can we capture and maintain expertise about software development, then make that expertise more widely available?
For more information on Dr. Menzies, click here.
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