Programming Uncertain <T>hings

Presented as part of the 2016 HCSS conference.

ABSTRACT
Innovation flourishes with good abstractions.  For instance, codification of the IEEE Floating Point standard in 1985 was critical to the subsequent success of scientific computing.  Programming languages currently lack appropriate abstractions for uncertain data. Applications already use estimates from sensors, machine learning, big data, humans, and approximate algorithms, but most programming languages do not help developers address correctness, programmability, and optimization problems due to estimates.

To address these problems, we propose a new programming abstraction called Uncertain<T> embedded into languages, such as C#, C++, Java, Python, and JavaScript. Applications use familiar discrete operations for estimates with Uncertain<T>.  Overloaded conditional operators specify hypothesis tests and applications use them to control false positives and negatives. A simple compositional operator expresses domain knowledge. We carefully restrict expressiveness such that we can build a runtime that implements correct statistical reasoning at conditionals.  Our system relieves developers of the need to implement or deeply understand statistics. We demonstrate substantial programmability, correctness, and efficiency benefits of this programming model for GPS sensor navigation, approximate computing,machine learning, and xBox.

We encourage the community to develop and use abstractions for estimates.

BIO
Kathryn S. McKinley is a Principal Research at Microsoft.  Her research interests span programming languages, compilers, runtime systems, architecture, performance, and energy with a recent focus on programming models for estimates.  She and her collaborators have produced several widely used tools: the DaCapo Java Benchmarks (30,000+ downloads),  TRIPS Compiler, Hoard memory manager, MMTk memory management toolkit, and Immix garbage collector. Her awards include the ACM SIGPLAN Programming Languages Software Award; ACM SIGPLAN Distinguished Service Award; and best & test of time paper awards from ASPLOS, OOPSLA, ICS, SIGMETRICS, IEEE Top Picks, SIGPLAN Research Highlights, and CACM Research Highlights.  She served as program chair for ASPLOS, PACT, PLDI, ISMM, and CGO.  She is currently CRA and CRA-W Board member.  Dr. McKinley was honored to testify to the House Science Committee (Feb. 14, 2013). She is honored to be among the IEEE and ACM Fellows and to have graduated 22 PhD students. She and her husband have three sons.