This thesis brings novel ideas to the software optimization domain. It illustrates methodological and practical contributions that advance the state of the art for performance profiling techniques and adaptive runtime designs, backed by promising experimental results on industrial-strength benchmarks. Part of the results has been presented in flagship programming language venues.
Daniele Cono D’Elia holds a Ph.D. in Engineering in Computer Science (2016). He is currently post-doc with Sapienza, working on software and systems security topics.