SRC Grand Finalists 2017

Kazem Cheshmi, Rutgers University
"Decoupling Symbolic from Numeric in Sparse Matrix Computations" (CGO 2017)

Sympiler is a domain-speci c code generator that optimizes sparse matrix computations by decoupling the symbolic analysis phase from the numerical manipulation stage in sparse codes. The computation patterns in sparse numerical methods are guided by the input sparsity structure and the sparse algorithm itself.... [Read more]

Omid Abari, Massachusetts Institute of Technology
"Cutting the Cord in Virtual Reality" (MobiCom 2016)

Today’s virtual reality (VR) headsets require a cable connection to a PC or game console. This cable significantly limits the player’s mobility and hence her VR experience... [Read more]

Calvin Loncaric, University of Washington
"Cozy: Synthesizing Collection Data Structures" (FSE 2016)

Many applications require specialized data structures not found in standard libraries. Implementing new data structures is tedious and error-prone. To alleviate this difficulty, we built a tool that does so automatically: it synthesizes efficient data structures from short, simple, declarative specifications.... [Read more]

Victor Lanvin, ENS Paris Saclay
"Gradual Set-Theoretic Types" (POPL 2017)

A static type system can be an extremely powerful tool for a programmer, providing early error detection, and offering strong compile-time guarantees on the behavior of a program. However, compared to dynamic typing, static typ- ing often comes at the expense of development speed and flexibility, as statically-typed code might be more difficult to adapt to changing requirements. Gradual typing is a recent and promising approach that tries to get the best of both worlds [16].... [Read more]

Jennifer Vaccaro, Olin College of Engineering
"Applying Computer Modeling to Post-Silicon Electrical Validation" (ICCAD 2016)

Because the post-silicon validation process requires a high amount of effort from engineers, we propose the use of a variety of modeling techniques to tune the silicon. Black-box models interpolate measured physical data (Kriging), while white-box models generate simplified simulation data with some correlation to the physical data. .... [Read more]

Martin Kellogg, University of Washington
"Combining Bug Detection and Test Case Generation" (FSE 2016)

Detecting bugs in software is an important software engineering activity. Static bug finding tools can assist in detecting bugs automatically, but they suffer from high false positive rates. .... [Read more]