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Join Dr. Muhammad A. Khan from the Department of Mathematics and Computer Science, University of Lethbridge, as he speaks in the Optimization Seminar and explores
A Data Analytic Approach to Software Modularity
Abstract: There is a consensus in the software engineering community that modularity is a key feature of good software design. Typically, modularity is defined in terms of static dependencies between the elements of a software product. We take a dynamic approach and measure modularity using software evolution data extracted from commit logs. Our methodology produces a numerical as well as a visual representation of how the modularity of a software product changes over time, making it a useful tool for software project managers. We analyze the modularity of two real-life software systems: Bitcoin Core and GNU Octave over 10 and 25 years, respectively. As a test for validity, we demonstrate that our approach correctly identifies certain watershed moments in the Bitcoin and Octave life-cycles. This is joint work with Benkoczi, Gaur and Hossain to appear (in part) in the Proceedings of the 15th ACM/IEEE International Conference on Mining Software Repositories, May 28–29, 2018, Gothenburg, Sweden.
When: Wednesday April 11, 2018 · 2:00 pm
Where: D630, University Hall, University of Lethbridge
Everyone is welcome!
Contact:
Muhammad Khan | ma.khan@uleth.ca | (403) 329-2130 | directory.uleth.ca/users/ma.khan
