Title: DPJizer: A Tool for Automated Java to DPJ Transformation
Abstract: Effect systems are important for reasoning about the side effects of a program. Although effect systems have been around for decades, they have not been widely adopted in practice because of the large number of annotations that they require. A tool that infers effects automatically can make effect systems practical. We present an effect inference algorithm and an Eclipse plug-in, DPJizer, which alleviate the burden of writing effect annotations for a language called Deterministic Parallel Java (DPJ). The key novel feature of the algorithm is the ability to infer effects on nested heap regions. Our experience shows that DPJizer is both useful and effective: (i) inferring effect annotations automatically saves significant programming burden; and (ii) inferred effects are more precise than those written manually, and are fine-grained enough to enable the compiler to prove determinism of the program.
Bio: Mohsen Vakilian is a PhD student in computer science at the University of Illinois at Urbana-Champaign. His research lies within the fields of software engineering and programming languages. He is particularly interested in automated program transformations that assist developers in writing parallel programs. Mohsen got his M.S. from University of Illinois at Urbana-Champaign in 2009. Before coming to Illinois, he got a BS in computer engineering from University of Tehran in 2007.
This is joint work with Danny Dig, Robert Bocchino, Jeffrey Overbey, Vikram Adve, and Ralph Johnson.
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