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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 ...
How to measure gain from the use of intelligent inference? How can the complexity of the recognition / classification task be estimated? What is the type of evidence which best suits an.inference mech...
The idea of assessing the damages to roads network after earthquake strikes has been referred as a matter of importance for performing every systematically planned activity in the affected region. Whe...
Infinite order vector autoregressive (VAR) models have been used in a number of applications ranging from spectral density estimation, impulse response analysis, tests for cointegration and uni...
We consider a dynamic panel AR(1) model with fixed effects when both n and T are large. Under the “T fixed n large” asymptotic approximation, the ordinary least squares (OLS) or Gau...
The inference of the radiative forcing of soot and dust in snow has taken on importance in recent years because of the realization of the climate effects that they have (Hansen and Nazarenko, 2004). ...
Understanding inference–evidence relationships in recognition tasks is fundamental for developing methods utilizing Artificial Intelligence. Recognition of geographical phenomena in wide areas from r...

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