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Verifying partial (i.e., termination-insensitive) equivalence of programs has significant practical applications in software development and education. Conventional equivalence verifiers typically rely on a combination of given relational…

Programming Languages · Computer Science 2017-05-10 Qi Zhou , David Heath , William Harris

Static alias analysis of different type of programming languages has been drawing researcher attention. However most of the results of existing techniques for alias analysis are not precise enough compared to needs of modern compilers.…

Programming Languages · Computer Science 2014-05-20 Mohamed A. El-Zawawy , Mohammad N. Alanazi

Program verification is to develop the program's proof system, and to prove the proof system soundness with respect to a trusted operational semantics of the program. However, many practical program verifiers are not based on operational…

Logic in Computer Science · Computer Science 2021-02-09 ShangBei Wang

Runtime efficiency and termination are crucial properties in the studies of program verification. Instead of dealing with these issues in an ad hoc manner, it would be useful to develop a robust framework in which such properties are…

Programming Languages · Computer Science 2026-04-06 Weijun Chen , Yuxi Fu , Huan Long

Herein we define a measure of similarity between classification distributions that is both principled from the perspective of statistical pattern recognition and useful from the perspective of machine learning practitioners. In particular,…

We introduce new inference procedures for counterfactual and synthetic control methods for policy evaluation. We recast the causal inference problem as a counterfactual prediction and a structural breaks testing problem. This allows us to…

Econometrics · Economics 2022-01-26 Victor Chernozhukov , Kaspar Wüthrich , Yinchu Zhu

Encodings or the proof of their absence are the main way to compare process calculi. To analyse the quality of encodings and to rule out trivial or meaningless encodings, they are augmented with quality criteria. There exists a bunch of…

Logic in Computer Science · Computer Science 2015-08-28 Kirstin Peters , Rob van Glabbeek

Relational properties arise in many settings: relating two versions of a program that use different data representations, noninterference properties for security, etc. The main ingredient of relational verification, relating aligned pairs…

Logic in Computer Science · Computer Science 2016-11-29 Anindya Banerjee , David A. Naumann , Mohammad Nikouei

Recursive calls over recursive data are useful for generating probability distributions, and probabilistic programming allows computations over these distributions to be expressed in a modular and intuitive way. Exact inference is also…

Programming Languages · Computer Science 2023-03-28 David Chiang , Colin McDonald , Chung-chieh Shan

We introduce equivalence testing procedures for linear regression analyses. Such tests can be very useful for confirming the lack of a meaningful association between a continuous outcome and a continuous or binary predictor. Specifically,…

Methodology · Statistics 2023-05-17 Harlan Campbell

In considering the reliability of numerical programs, it is normal to "limit our study to the semantics dealing with numerical precision" (Martel, 2005). On the other hand, there is a great deal of work on the reliability of programs that…

Symbolic Computation · Computer Science 2014-04-25 James H. Davenport , Russell Bradford , Matthew England , David Wilson

Context: Software engineering has a problem in that when we empirically evaluate competing prediction systems we obtain conflicting results. Objective: To reduce the inconsistency amongst validation study results and provide a more formal…

Software Engineering · Computer Science 2021-01-15 Martin Shepperd , Stephen G. MacDonell

There is a well-known problem in Null Hypothesis Significance Testing: many statistically significant results fail to replicate in subsequent experiments. We show that this problem arises because standard `point-form null' significance…

Methodology · Statistics 2025-02-06 Fintan Costello , Paul Watts

Forecast evaluations aim to choose an accurate forecast for making decisions by using loss functions. However, different loss functions often generate different ranking results for forecasts, which complicates the task of comparisons. In…

Applications · Statistics 2018-07-17 Yu-Min Yen , Tso-Jung Yen

Binary code similarity comparison is a methodology for identifying similar or identical code fragments in binary programs. It is indispensable in fields of software engineering and security, which has many important applications (e.g.,…

Cryptography and Security · Computer Science 2019-07-03 Yikun Hu , Hui Wang , Yuanyuan Zhang , Bodong Li , Dawu Gu

This thesis explores proofs by coupling from the perspective of formal verification. Long employed in probability theory and theoretical computer science, these proofs construct couplings between the output distributions of two…

Logic in Computer Science · Computer Science 2017-11-02 Justin Hsu

This dissertation is concerned with the study of program equivalence and algebraic effects as they arise in the theory of programming languages. Algebraic effects represent impure behaviour in a functional programming language, such as…

Programming Languages · Computer Science 2019-02-14 Cristina Matache

Process equivalences are formal methods that relate programs and system which, informally, behave in the same way. Since there is no unique notion of what it means for two dynamic systems to display the same behaviour there are a multitude…

Logic in Computer Science · Computer Science 2012-10-10 Martin Lange , Etienne Lozes , Manuel Vargas Guzmán

In the framework of semiparametric distribution regression, we consider the problem of comparing the conditional distribution functions corresponding to two samples. In contrast to testing for exact equality, we are interested in the (null)…

Econometrics · Economics 2025-06-12 Holger Dette , Kathrin Möllenhoff , Dominik Wied

Uncertainty sampling is a prevalent active learning algorithm that queries sequentially the annotations of data samples which the current prediction model is uncertain about. However, the usage of uncertainty sampling has been largely…

Machine Learning · Computer Science 2026-04-08 Shang Liu , Xiaocheng Li