A comprehensive guide to the art and science of analyzing software data, with best practices generated by leading data scientists, collected from their experience training software engineering students and practitioners on how to master data science.
The Art and Science of Analyzing Software Data: Analysis Patterns provides valuable information on the analysis methods that often transfer between projects, not only the algorithms derived from data analysis, but also the processes and structure that software engineers follow when using algorithms, giving users the foundation they need to extract models, data, or patterns that could be insightful for future projects. . This updated volume shares best practices in the field generated by leading data scientists, and collected from their experience training software engineering students and practitioners to master data science. Throughout, the editors highlight the methods that are most useful, and applicable, to the widest range of projects.
