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Evaluating Software testability can assist software managers in optimizing testing budgets and identifying opportunities for refactoring. In this paper, we abandon the traditional approach of pursuing testability measurements based on the…

Software Engineering · Computer Science 2021-02-23 Luca Guglielmo , Andrea Riboni , Giovanni Denaro

One major problem in maintaining a software system is to understand how many functional features in the system and how these features are implemented. In this paper a novel approach for locating features in code by semantic and dynamic…

Software Engineering · Computer Science 2015-12-15 Ren Wu

Process mining is a scientific discipline that analyzes event data, often collected in databases called event logs. Recently, uncertain event logs have become of interest, which contain non-deterministic and stochastic event attributes that…

Artificial Intelligence · Computer Science 2022-04-05 Marco Pegoraro , Bianka Bakullari , Merih Seran Uysal , Wil M. P. van der Aalst

Axiomatization has been widely used for testing logical implications. This paper suggests a non-axiomatic method, the chase, to test if a new dependency follows from a given set of probabilistic dependencies. Although the chase computation…

Artificial Intelligence · Computer Science 2013-02-18 Michael S. K. M. Wong

Language model (LM) "reasoning", commonly described as Chain-of-Thought or test-time scaling, often improves benchmark performance, but the dynamics underlying this process remain poorly understood. We study these dynamics through the lens…

We propose a new type of entropic descriptor that is able to quantify the statistical complexity (a measure of complex behaviour) by taking simultaneously into account the average departures of a system's entropy S from both its maximum…

Statistical Mechanics · Physics 2015-05-13 R. Piasecki , A. Plastino

In this paper, we establish an iterative data-driven approach to derive guaranteed bounds on nonlinearity measures of unknown nonlinear systems. In this context, nonlinearity measures quantify the strength of the nonlinearity of a dynamical…

Systems and Control · Electrical Eng. & Systems 2020-08-13 Tim Martin , Frank Allgöwer

This paper proposes a new class of nonparametric tests for the correct specification of models based on conditional moment restrictions, paying particular attention to generalized propensity score models. The test procedure is based on two…

Econometrics · Economics 2023-04-18 Pedro H. C. Sant'Anna , Xiaojun Song

Model checking is the process of deciding whether a system satisfies a given specification. Often, when the setting comprises multiple processes, the specifications are over sets of input and output signals that correspond to individual…

Logic in Computer Science · Computer Science 2020-07-24 Shaull Almagor

We introduce estimation and test procedures through divergence minimization for models satisfying linear constraints with unknown parameter. Several statistical examples and motivations are given. These procedures extend the empirical…

Statistics Theory · Mathematics 2008-11-24 Michel Broniatowski , Amor Keziou

The problem of checking a logged event trace against a temporal logic specification arises in many practical cases. Unfortunately, known algorithms for an expressive logic like MTL (Metric Temporal Logic) do not scale with respect to two…

Software Engineering · Computer Science 2015-08-27 Marcello M. Bersani , Domenico Bianculli , Carlo Ghezzi , Srdan Krstic , Pierluigi San Pietro

This paper proposes new parametric model adequacy tests for possibly nonlinear and nonstationary time series models with noncontinuous data distribution, which is often the case in applied work. In particular, we consider the correct…

Statistics Theory · Mathematics 2021-08-10 Igor Kheifets , Carlos Velasco

Aleatoric uncertainty quantification seeks for distributional knowledge of random responses, which is important for reliability analysis and robustness improvement in machine learning applications. Previous research on aleatoric uncertainty…

Machine Learning · Computer Science 2022-06-10 Ziyi Huang , Henry Lam , Haofeng Zhang

Measurements performed on distant parts of an entangled quantum state can generate correlations incompatible with classical theories respecting the assumption of local causality. This is the phenomenon known as quantum non-locality that,…

Quantum Physics · Physics 2018-02-28 S. G. A. Brito , B. Amaral , R. Chaves

We introduce an algorithm for the uniform generation of infinite runs in concurrent systems under a partial order probabilistic semantics. We work with trace monoids as concurrency models. The algorithm outputs on-the-fly approximations of…

Combinatorics · Mathematics 2017-12-07 Samy Abbes , Vincent Jugé

We propose three test criteria each of which is appropriate for testing, respectively, the equivalence hypotheses of symmetry, of homogeneity, and of independence, with multivariate data. All quantities have the common feature of involving…

Methodology · Statistics 2023-11-09 Feifei Chen , Simos G. Meintanis , Lixing Zhu

Most analyses of randomised trials with incomplete outcomes make untestable assumptions and should therefore be subjected to sensitivity analyses. However, methods for sensitivity analyses are not widely used. We propose a mean score…

Methodology · Statistics 2020-07-21 Ian R. White , James Carpenter , Nicholas J. Horton

The scattering formulation of characteristic mode decomposition is utilized to extend modal analysis to lossless scatterers breaking time-reversal symmetry. This enables characteristic modes analysis on devices containing gyrotropic or…

In order to deal with the systematic verification with uncertain infromation in possibility theory, Li and Li \cite{li12} introduced model checking of linear-time properties in which the uncertainty is modeled by possibility measures. Xue,…

Logic in Computer Science · Computer Science 2014-01-21 Yongming Li , Yali Li , Zhanyou Ma

Non-deterministic measurements are common in real-world scenarios: the performance of a stochastic optimization algorithm or the total reward of a reinforcement learning agent in a chaotic environment are just two examples in which…

Machine Learning · Statistics 2022-08-31 Etor Arza , Josu Ceberio , Ekhiñe Irurozki , Aritz Pérez
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