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Related papers: Improvements to the Psi-SSA representation

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Static Single Assignment (SSA) is the workhorse of modern optimizing compilers for imperative programming languages. However, functional languages have been slow to adopt SSA and prefer to use intermediate representations based on minimal…

Programming Languages · Computer Science 2022-01-20 Siddharth Bhat , Tobias Grosser

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

Static single assignment form, or SSA, has been the dominant compiler intermediate representation for decades. In this paper, we give a type theory for a variant of SSA, including its equational theory, which are strong enough to validate a…

Programming Languages · Computer Science 2024-12-13 Jad Elkhaleq Ghalayini , Neel Krishnaswami

Structural operational semantics (SOS) is a technique for defining operational semantics for programming and specification languages. Because of its intuitive appeal and flexibility, SOS has found considerable application in the study of…

Logic in Computer Science · Computer Science 2010-08-12 Luca Aceto , Paweł Sobociński

The formal analysis of automated systems is an important and growing industry. This activity routinely requires new verification frameworks to be developed to tackle new programming features, or new considerations (bugs of interest). Often,…

Logic in Computer Science · Computer Science 2026-02-17 Paul Brunet

Modal parameter estimation of operational structures is often a challenging task when confronted with unwanted distortions (outliers) in field measurements. Atypical observations present a problem to operational modal analysis (OMA)…

Machine Learning · Statistics 2024-06-25 Brandon J. O'Connell , Timothy J. Rogers

Answer Set Programming (ASP) is a well-known declarative formalism in logic programming. Efficient implementations made it possible to apply ASP in many scenarios, ranging from deductive databases applications to the solution of hard…

Logic in Computer Science · Computer Science 2020-02-19 Bernardo Cuteri , Carmine Dodaro , Francesco Ricca , Peter Schüller

There is an increasing need in solving high-dimensional optimization problems under non-deterministic environment. The simultaneous perturbation stochastic approximation (SPSA) algorithm has recently attracted considerable attention for…

Optimization and Control · Mathematics 2020-12-15 Chen Wang

We introduce Scruff, a new framework for developing AI systems using probabilistic programming. Scruff enables a variety of representations to be included, such as code with stochastic choices, neural networks, differential equations, and…

Artificial Intelligence · Computer Science 2021-10-07 Avi Pfeffer , Michael Harradon , Joseph Campolongo , Sanja Cvijic

In this extended abstract, we discuss the opportunity to formally verify that inference systems for probabilistic programming guarantee good performance. In particular, we focus on hybrid inference systems that combine exact and approximate…

Programming Languages · Computer Science 2023-07-17 Eric Atkinson , Ellie Y. Cheng , Guillaume Baudart , Louis Mandel , Michael Carbin

Constraint automata (CA) constitute a coordination model based on finite automata on infinite words. Originally introduced for modeling of coordinators, an interesting new application of CAs is implementing coordinators (i.e., compiling CAs…

Programming Languages · Computer Science 2019-03-14 Sung-Shik T. Q. Jongmans , Farhad Arbab

Probabilistic programming is a powerful abstraction for statistical machine learning. Applying static analysis methods to probabilistic programs could serve to optimize the learning process, automatically verify properties of models, and…

Programming Languages · Computer Science 2019-09-12 Ryan Bernstein

Any optimization algorithm programming interface can be seen as a black-box function with additional free parameters. In this spirit, simulated annealing (SA) can be implemented in pseudo-code within the dimensions of a single slide with…

Software Engineering · Computer Science 2023-02-27 Rohit Goswami , Ruhila S. , Amrita Goswami , Sonaly Goswami , Debabrata Goswami

Psi-calculi is a parametric framework for process calculi similar to popular pi-calculus extensions such as the explicit fusion calculus, the applied pi-calculus and the spi calculus. Mechanised proofs of standard algebraic and congruence…

Logic in Computer Science · Computer Science 2023-06-22 Johannes Åman Pohjola

In earlier work, we introduced the framework of language-based decisions, the core idea of which was to modify Savage's classical decision-theoretic framework by taking actions to be descriptions in some language, rather than functions from…

Logic in Computer Science · Computer Science 2023-07-18 Adam Bjorndahl , Joseph Y. Halpern

Self-supervised adaptation (SSA) improves foundation model transfer to medical domains but is computationally prohibitive. Although parameter efficient fine-tuning methods such as LoRA have been explored for supervised adaptation, their…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Moein Sorkhei , Emir Konuk , Jingyu Guo , Chanjuan Meng , Christos Matsoukas , Kevin Smith

Dominance is a fundamental concept in compilers based on static single assignment (SSA) form. It underpins a wide range of analyses and transformations and defines a core property of SSA: every use must be dominated by its definition. We…

Programming Languages · Computer Science 2026-04-30 Roland Leißa , Johannes Griebler

A compiler's intermediate representation (IR) defines a program's execution plan by encoding its instructions and their relative order. Compiler optimizations aim to replace a given execution plan with a semantically-equivalent one that…

In this paper, we extend a bio-inspired algorithm called the porcellio scaber algorithm (PSA) to solve constrained optimization problems, including a constrained mixed discrete-continuous nonlinear optimization problem. Our extensive…

Neural and Evolutionary Computing · Computer Science 2017-10-12 Yinyan Zhang , Shuai Li , Hongliang Guo

Simultaneous perturbation stochastic approximation (SPSA) is widely used in stochastic optimization due to its high efficiency, asymptotic stability, and reduced number of required loss function measurements. However, the standard SPSA…

Optimization and Control · Mathematics 2023-02-07 Zhichao Jia , Ziyi Wei , James C. Spall
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