Summary In observational causal inference, exact covariate matching plays two statistical roles: (i) it effectively controls for bias due to measured confounding; (ii) justifies assumption-free inference based on randomization tests. this paper we show that inexact does not always play these same roles. We find often leaves behind statistically meaningful bias, and renders standard tests asympt...

Abstract Fortran is widely used in computational science, engineering, and high performance computing. This paper presents an extension to the CIVL verification framework check correctness properties of programs. Unlike previous work that translates C, LLVM IR, or other intermediate formats before verification, our allows directly consume source files. We extended parsing, translation, analysis...