The programming languages research community often develops ideas whose worth is evaluated empirically. Compiler optimizations, static and dynamic analyses, program synthesizers, testing tools, memory management algorithms, new language features, and other research developments each depend on some empirical evidence to demonstrate their effectiveness. This reality raises some important questions. What kind of empirical evidence yields the most reliable conclusions? What are the best practices for putting together an empirical evaluation in PL research? Do PL research papers published in top venues always follow these best practices?
To answer these questions, in August of 2017 the SIGPLAN Executive Committee formed the ad hoc committee on Programming Language Research Empirical Evaluations. The committee is chaired by Steve Blackburn, and its members include Matthias Hauswirth, Emery Berger, and Michael Hicks. Shriram Krishnamurthi has acted as an external collaborator. The committee brings together expertise on empirical evaluation methodology, experience in running workshops and publishing papers on that topic, experience introducing artifact evaluation into SIGPLAN conferences, and experience chairing the PCs of major SIGPLAN conferences.
Since its formation, the committee has examined the literature to identify common forms of empirical evaluation applied to the various kinds of PL research. This examination has identified inadequacies that regularly arise, even in papers published recently in highly regarded venues, including PLDI, POPL, ASPLOS, OOPSLA, and ICFP.
The committee has organized and categorized its findings, producing a 1-page best-practices checklist.
The goal of the checklist is to help authors produce stronger scholarship, and to help reviewers evaluate such scholarship more consistently. The committee’s hope is that this checklist can put all members of the community literally on the same page.
The current checklist (as of January 1, 2018) should be viewed as beta quality. We are now, and will be into the future, requesting feedback and suggestions for improvement. We are particularly interested in