Proceedings of the 16th ACM SIGPLAN International Haskell Symposium最新文献

The Essence of Reactivity 反应性的本质

Proceedings of the 16th ACM SIGPLAN International Haskell Symposium Pub Date : 2023-08-30 DOI: 10.1145/3609026.3609727

Ivan Perez, F. Dedden

引用次数: 0

falsify: Internal Shrinking Reimagined for Haskell 伪造:内部萎缩为哈斯克尔重新想象

Proceedings of the 16th ACM SIGPLAN International Haskell Symposium Pub Date : 2023-08-30 DOI: 10.1145/3609026.3609733

Edsko de Vries

引用次数: 0

This Is Driving Me Loopy: Efficient Loops in Arrowized Functional Reactive Programs 这让我发疯:箭头化函数式反应程序中的高效循环

Proceedings of the 16th ACM SIGPLAN International Haskell Symposium Pub Date : 2023-08-30 DOI: 10.1145/3609026.3609726

Finnbar Keating, Michael B. Gale

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Haskell for Choice-Based Learning (Keynote) 基于选择学习的Haskell(主题演讲)

Proceedings of the 16th ACM SIGPLAN International Haskell Symposium Pub Date : 2023-08-30 DOI: 10.1145/3609026.3615580

Ningning Xie

{"title":"Haskell for Choice-Based Learning (Keynote)","authors":"Ningning Xie","doi":"10.1145/3609026.3615580","DOIUrl":"https://doi.org/10.1145/3609026.3615580","url":null,"abstract":"Machine learning has achieved many successes during the past decades, spanning domains of game-playing, protein folding, competitive programming, and many others. However, while there have been major efforts in building programming techniques and frameworks for machine learning programming, there has been very little study of general language design for machine learning programming. We pursue such a study in this talk, focusing on choice-based learning, particularly where choices are driven by optimizations. This includes widely-used decision-making models and techniques (e.g., Markov decision processes or gradient descent) which provide frameworks for describing systems in terms of choices (e.g., actions or parameters) and their resulting feedback as losses (dually, rewards). We propose and give evidence for the following thesis: languages for choice-based learning can be obtained by combining two paradigms, algebraic effects and handlers, and the selection monad. We provide a prototype implementation as a Haskell library and present a variety of programming examples for choice-based learning: stochastic gradient descent, hyperparameter tuning, generative adversarial networks, and reinforcement learning.","PeriodicalId":184785,"journal":{"name":"Proceedings of the 16th ACM SIGPLAN International Haskell Symposium","volume":"513 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123249362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Don’t Go Down the Rabbit Hole: Reprioritizing Enumeration for Property-Based Testing 不要掉进兔子洞:为基于属性的测试重新确定枚举的优先级

Proceedings of the 16th ACM SIGPLAN International Haskell Symposium Pub Date : 2023-08-30 DOI: 10.1145/3609026.3609730

Segev Elazar Mittelman, Aviel Resnick, Ivan Perez, Alwyn E. Goodloe, Leonidas Lampropoulos

引用次数: 0

Haskell Library for Safer Virtual Machine Introspection (Experience Report) Haskell库用于更安全的虚拟机自省(体验报告)

Proceedings of the 16th ACM SIGPLAN International Haskell Symposium Pub Date : 2023-08-30 DOI: 10.1145/3609026.3609732

Takato Otsuka, H. Iwasaki

引用次数: 0

The Evolution of Effects (Keynote) 效应的演变(主题演讲)

Proceedings of the 16th ACM SIGPLAN International Haskell Symposium Pub Date : 2023-08-30 DOI: 10.1145/3609026.3615581

Nicolas Wu

{"title":"The Evolution of Effects (Keynote)","authors":"Nicolas Wu","doi":"10.1145/3609026.3615581","DOIUrl":"https://doi.org/10.1145/3609026.3615581","url":null,"abstract":"Functional programming has been celebrated for its promise of pure functions, delivering referential transparency and elegant reasoning about programs. However, real-world applications are not pure, and necessitate interaction with the outside world, introducing computational effects such as IO, state, and exceptions. The journey to harmonize these seemingly contradictory paradigms has led to a fascinating evolution of effectful programming in Haskell. The introduction of monads as a practical programming tool was a pivotal discovery, enabling controlled sequencing of effectful computations and addressing the challenge of handling side effects in a pure language. However, it soon became evident that the lack of modularity in composing effects using monads posed a limitation to effectful programming. To overcome this obstacle, monad transformers emerged as a solution, providing a composable manner of building effects on top of one another. More recent advancements have led to algebraic effects as an alternative framework that is easy to extend, particularly as domain-specific languages crafted to work in specific contexts. Nevertheless, these effects are not without quirks and limitations, leading to the development of higher-order effects. These higher-order effects extend the capabilities of algebraic effects, providing greater flexibility for expressing effectful computations, while also shedding light on the connection between the monad approach and the algebraic approach to effects. This talk will survey the historical milestones that have shaped the landscape of effectful programming in Haskell, exploring the transition from monads to monad transformers and the emergence of algebraic and higher-order effects.","PeriodicalId":184785,"journal":{"name":"Proceedings of the 16th ACM SIGPLAN International Haskell Symposium","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123264340","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

HasTEE: Programming Trusted Execution Environments with Haskell HasTEE:用Haskell编程可信执行环境

Proceedings of the 16th ACM SIGPLAN International Haskell Symposium Pub Date : 2023-07-24 DOI: 10.1145/3609026.3609731

Abhiroop Sarkar, Robert Krook, Alejandro Russo, Koen Claessen

{"title":"HasTEE: Programming Trusted Execution Environments with Haskell","authors":"Abhiroop Sarkar, Robert Krook, Alejandro Russo, Koen Claessen","doi":"10.1145/3609026.3609731","DOIUrl":"https://doi.org/10.1145/3609026.3609731","url":null,"abstract":"Trusted Execution Environments (TEEs) are hardware enforced memory isolation units, emerging as a pivotal security solution for security-critical applications. TEEs, like Intel SGX and ARM TrustZone, allow the isolation of confidential code and data within an untrusted host environment, such as the cloud and IoT. Despite strong security guarantees, TEE adoption has been hindered by an awkward programming model. This model requires manual application partitioning and the use of error-prone, memory-unsafe, and potentially information-leaking low-level C/C++ libraries. We address the above with HasTEE, a domain-specific language (DSL) embedded in Haskell for programming TEE applications. HasTEE includes a port of the GHC runtime for the Intel-SGX TEE.HasTEE uses Haskell’s type system to automatically partition an application and to enforce Information Flow Control on confidential data. The DSL, being embedded in Haskell, allows for the usage of higher-order functions, monads, and a restricted set of I/O operations to write any standard Haskell application. Contrary to previous work, HasTEE is lightweight, simple, and is provided as a simple security library; thus avoiding any GHC modifications. We show the applicability of HasTEE by implementing case studies on federated learning, an encrypted password wallet, and a differentially-private data clean room.","PeriodicalId":184785,"journal":{"name":"Proceedings of the 16th ACM SIGPLAN International Haskell Symposium","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123112936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Exceptional Actor System (Functional Pearl) 一个特殊角色系统(功能珍珠)

Proceedings of the 16th ACM SIGPLAN International Haskell Symposium Pub Date : 2023-07-20 DOI: 10.1145/3609026.3609728

Patrick Redmond, L. Kuper

引用次数: 0

Effect Handlers for Programmable Inference 可编程推理的效果处理程序

Proceedings of the 16th ACM SIGPLAN International Haskell Symposium Pub Date : 2023-03-02 DOI: 10.1145/3609026.3609729

Minh Nguyen, R. Perera, M. Wang, S. Ramsay

{"title":"Effect Handlers for Programmable Inference","authors":"Minh Nguyen, R. Perera, M. Wang, S. Ramsay","doi":"10.1145/3609026.3609729","DOIUrl":"https://doi.org/10.1145/3609026.3609729","url":null,"abstract":"Inference algorithms for probabilistic programming are complex imperative programs with many moving parts. Efficient inference often requires customising an algorithm to a particular probabilistic model or problem, sometimes called inference programming. Most inference frameworks are implemented in languages that lack a disciplined approach to side effects, which can result in monolithic implementations where the structure of the algorithms is obscured and inference programming is hard. Functional programming with typed effects offers a more structured and modular foundation for programmable inference, with monad transformers being the primary structuring mechanism explored to date. This paper presents an alternative approach to inference programming based on algebraic effects. Using effect signatures to specify the key operations of the algorithms, and effect handlers to modularly interpret those operations for specific variants, we develop two abstract algorithms, or inference patterns, representing two important classes of inference: Metropolis-Hastings and particle filtering. We show how our approach reveals the algorithms’ high-level structure, and makes it easy to tailor and recombine their parts into new variants. We implement the two inference patterns as a Haskell library, and discuss the pros and cons of algebraic effects vis-à-vis monad transformers as a structuring mechanism for modular imperative algorithm design.","PeriodicalId":184785,"journal":{"name":"Proceedings of the 16th ACM SIGPLAN International Haskell Symposium","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132473630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1