Deductive Program Repair, Computer Aided Verification

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Covariance Estimation for Random Surfaces beyond Separability

This thesis focuses on non-parametric covariance estimation for random surfaces, i.e.~functional data on a two-dimensional domain. Non-parametric covariance estimation lies at the heart of functional data analysis, and considerations of statistical and com ...

EPFL2022

Performance Estimation of High-Level Dataflow Program on Heterogeneous Platforms

Marco Mattavelli, Simone Casale Brunet, Aurélien François Gilbert Bloch

The performance of programs written in languages following the dataflow model of computation (MoC) largely depends on the configuration (partitioning, mapping, scheduling, buffer dimensioning) chosen during the synthesis stages. Furthermore, this programmi ...

2022

Testing For The Rank Of A Covariance Operator

Victor Panaretos

How can we discern whether the covariance operator of a stochastic pro-cess is of reduced rank, and if so, what its precise rank is? And how can we do so at a given level of confidence? This question is central to a great deal of methods for functional dat ...

INST MATHEMATICAL STATISTICS-IMS2022

Proving and Disproving Equivalence of Functional Programming Assignments

Viktor Kuncak, Dragana Milovancevic

We present an automated approach to verify the correctness of programming assignments, such as the ones that arise in a functional programming course. Our approach takes as input student submissions and reference solutions, and uses equivalence checking to ...

2023

Trust as a Programming Primitive

Adrien Ghosn

Programming has changed; programming languages have not. Modern software embraced reusable software components, i.e., public libraries, and runs in the cloud, on machines that co-locate applications from various origins. This new programming paradigm leads ...

EPFL2021

Functional registration and local variations: Identifiability, rank, and tuning

Victor Panaretos, Anirvan Chakraborty

We develop theory and methodology for the problem of nonparametric registration of functional data that have been subjected to random deformation (warping) of their time scale. The separation of this phase variation ("horizontal" variation) from the amplit ...

2021

Representing Monads with Capabilities

Martin Odersky, Aleksander Slawomir Boruch-Gruszecki, Jonathan Immanuel Brachthäuser

Programming with monads can be advantageous even in imperative languages with builtin support for side effects. However, in these languages composing monadic programs is different from composing side effecting imperative programs. This does not need to be ...

2021

Software Support for Non-Volatile Memory (NVM) Programming

David Teksen Aksun

Non-Volatile Memory (NVM) is an emerging type of memory device that provides fast, byte-addressable, and high-capacity durable storage. NVM sits on the memory bus and allows durable data structures designs similar to the in-memory equivalent ones. Expensiv ...

EPFL2021

A Coarse-mesh Methodology for the Analysis of One and Two-phase Nuclear Reactor Thermal-hydraulics in a Multi-physics Context

Stefan Radman

The analysis of nuclear reactors for performance and safety assessment benefits from the use of computational tools. In this context, this work aims at the development and application of a thermal-hydraulics methodology and related software that respond to ...

EPFL2021

Verification of Software Network Functions with No Verification Expertise

Arseniy Zaostrovnykh

Software network functions (NFs), such as a network address translator, load balancer, or proxy, promise to bring flexibility and rapid innovation to computer networks and to reduce operational costs. However, continuous updates and flexibility typically c ...

EPFL2020

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A Coarse-mesh Methodology for the Analysis of One and Two-phase Nuclear Reactor Thermal-hydraulics in a Multi-physics Context

Stefan Radman

EPFL2021

Proving and Disproving Equivalence of Functional Programming Assignments

Viktor Kuncak, Dragana Milovancevic

2023