Analyzing Software Development using data science and analytic tools
Yesterday I had the pleasure to host Markus Harrer who gave a talk about analyzing software code using data science, which he describe in details in his blog . There is often a communication gap between software developers and management. While good developers can see the big picture of the code, and timely identify a need to restructure or even rewrite the code, they often miss to see the risks of both, time and cost, of such an operation. The management on the other hand, while being able to identify risks of getting into an adventure of rewriting a legacy system, often fail to understand the outcome and the risks of lack of maintenance. The solution to overcome this 'gap of ignorance' is communicating using data science and analytics. Using Jupyter notebooks, for example, to combine both textual explanations as well as analytics and diagrams can easily communicate the risks of a software to the management. For using data science on software code, one should decide