by Emery D. Berger, Stephen M. Blackburn, Matthias Hauswirth, Michael W. Hicks on Aug 28, 2019 | Tags: Artifact evaluation, Measurements, Methodology
To avoid an empirical replication crisis in programming languages research, PL researchers should employ the best scientific practices for empirical evaluation. A SIGPLAN empirical evaluation committee has assembled a checklist to help.
Read more...
by Eran Yahav on Aug 22, 2019 | Tags: code completion, machine learning, neural networks, program synthesis, programming, static analysis
The wealth of code now available on-line is fertile ground to enable machine learning to be applied to programming tasks. This post discusses the promise of and some progress on the problem “deep code.” It is the first in a series.
Read more...
by Andrew Myers on Aug 14, 2019 | Tags: conferences, publication process, scientific journals
Journals broaden the impact of PL. One way to make journals a more attractive publication vehicle is to allow presentations of journal papers at PL conferences, as TOPLAS does.
Read more...
by Ilya Sergey on Aug 7, 2019 | Tags: abstract interpretation, concurrency, dynamic analysis, soundness, static analysis, testing
The purpose of a program analysis is to infer whether a certain property of a program execution can be observed at runtime. The notion of an analysis’ soundness defines how much confidence one should put in its results. The notion is not uniform and is determined by whether the analysis is intended to be used as a testing or as a verification tool.
Read more...