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Proceedings of the ACM on Programming Languages
A C M (ASSN FOR COMPUTING MAC)
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Cubical Agda: a dependently typed programming language with univalence and higher inductive types
Vezzosi A., Mörtberg A., Abel A. Proceedings of the ACM on Programming Languages 3(ICFP): 1-29, 2019. Type: Article
Russell proposed type theory in the first decades of the 20th century in response to the foundational crisis faced by set theory. Over the last century, there have been a number of developments in type theory, in particular the mechani...
Jul 23 2021
Efficient differentiable programming in a functional array-processing language
Shaikhha A., Fitzgibbon A., Vytiniotis D., Peyton Jones S. Proceedings of the ACM on Programming Languages 3(ICFP): 1-30, 2019. Type: Article
Differentiable programming, or automatic differentiation, is a powerful technique in many fields, including dynamic systems, machine learning, and computer vision, mainly for solving nonlinear problems. Forward (versus reverse) differe...
Jul 20 2021
Constructing quotient inductive-inductive types
Kaposi A., Kovács A., Altenkirch T. Proceedings of the ACM on Programming Languages 3(POPL): 1-24, 2019. Type: Article
At the core of Martin-Löf type theory (also known as “intuitionistic type theory”) are dependent types, that is, types whose definitions depend on values; these may be used to encode logical quantification....
Jul 9 2021
Implementing a modal dependent type theory
Gratzer D., Sterling J., Birkedal L. Proceedings of the ACM on Programming Languages 3(ICFP): 1-29, 2019. Type: Article
Modalities are widely used in mathematics and computer science as an abstraction tool, but it turns out to be difficult to incorporate them in rich type theories. The authors address this problem, proposing a new dependent type theory ...
Apr 27 2021
Quantum relational Hoare logic
Unruh D. Proceedings of the ACM on Programming Languages 3(POPL): 1-31, 2019. Type: Article
All programs need to be verified--even post-quantum cryptography software. To prove properties of such protocols requires proofs that involve not only quantum programming, but also pairs of programs, an encryptor and an attack...
Jan 22 2021
A predicate transformer semantics for effects (functional pearl)
Swierstra W., Baanen T. Proceedings of the ACM on Programming Languages 3(ICFP): 1-26, 2019. Type: Article
Proving properties of imperative programs with side effects is quite arduous. Purely functional code, on the other hand, has a relatively pleasant equational theory that enables reasonable proofs. Is it possible to use modern machinery...
Jan 20 2021
Compiling with continuations, or without? Whatever.
Cong Y., Osvald L., Essertel G., Rompf T. Proceedings of the ACM on Programming Languages 3(ICFP): 1-28, 2019. Type: Article
The front end of a compiler analyzes a computer program’s source code and parses it into an intermediate representation (IR). The back end then takes this IR and translates it into machine code for execution. The techniques u...
Dec 16 2020
A calculus for Esterel: If can, can. If no can, no can.
Florence S., You S., Tov J., Findler R. Proceedings of the ACM on Programming Languages 3(POPL): 1-29, 2019. Type: Article
Esterel is a synchronous language for reactive programming. Developed in the mid 1980s, it has been used in several safety-critical applications for aviation and nuclear power plant control....
Oct 27 2020
A domain theory for statistical probabilistic programming
Vákár M., Kammar O., Staton S. Proceedings of the ACM on Programming Languages 3(POPL): 1-29, 2019. Type: Article
On the one hand, a statistical programming language is similar to a traditional programming language, but with libraries providing statistical functions. Examples are Mathematica, MATLAB, and the omnipresent R. On the other hand, proba...
Aug 6 2020
Bayesian synthesis of probabilistic programs for automatic data modeling
Saad F., Cusumano-Towner M., Schaechtle U., Rinard M., Mansinghka V. Proceedings of the ACM on Programming Languages 3(POPL): 1-32, 2019. Type: Article
Somewhat overshadowed by neural networks (NN) is another thread in machine learning: the Bayesian-based approach. Less data hungry, it also has the promise of being closer to explainable artificial intelligence (XAI), although it hasn&...
Jun 3 2020
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