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We present a type inference system for FL based on an operational, rather than a denotational, formulation of types. The essential elements of the system are a type language based on regular trees and...
We present a general algorithm for solving systems of inclusion constraints over type expressions.The constraint language includes function types, constructor types, and liberal intersection and union...
Dynamic typing is a program analysis targeted at removing runtime tagging and untagging operations in dynamically typed languages. This paper shows that dynamic typing at least as powerful as Henglein...
Refined Type Inference for ML     Refined Type Inference  ML       2016/5/24
Inclusion constraints over set-expressions [1, 4] provide a general formalism to express a large class of program analyses. Over the past two years, we have experimented with inclusion constraints to ...
Barrier Inference     Barrier Inference       2016/5/24
Many parallel programs are written in SPMD style, i.e.by running the same sequential program on all processes.SPMD programs include synchronization, but it is easy to write incorrect synchronization p...
Inconsistency checking is a method for detecting software errors that relies only on examining multiple uses of a value. We propose that inconsistency inference is best understood as a variant of the ...
When program verification tools fail to verify a program, either the program is buggy or the report is a false alarm. In this situation, the burden is on the user to manually classify the report, but ...
We describe a general framework c2i for generating an invariant inference procedure from an invariant checking procedure. Given a checker and a language of possible invariants, c2i generates an infere...
We present a framework for computing context-free language reachability properties when parts of the program are missing. Our framework infers candidate specifications for missing program pieces that ...
We consider statistical inference for regression when data are grouped into clusters, with regression model errors independent across clusters but correlated within clusters. Examples include data on ...
The development of a general inferential theory for nonlinear models with cross-sectionally or spatially dependent data has been hampered by a lack of appropriate limit theorems. To facilitate a gener...
During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and mark...
Presence-only data abounds in ecology, often accompanied by a background sample. Although many interesting aspects of the species’ distribution can be learned from such data, one cannot learn the over...
Consider the following three important problems in statistical inference, namely, constructing confidence intervals for (1) the error of a high-dimensional (p > n) regression estimator, (2) the linear...
A novel algorithm was developed to convert raw 2-dimensional endoscope videos into 3-dimensional view. Minimally invasive surgeries aided with 3D view of the invivo site have shown to reduce errors an...

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