Effect Systems Revisited—Control-Flow Algebra and Semantics

Mycroft, Alan; Orchard, Dominic; Petříček, Tomáš

doi:10.1007/978-3-319-27810-0_1

Cited by 25 publications

(35 citation statements)

References 39 publications

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“…CMTT defines rules for composing context-dependent propositions that would allow us to express the splicing operation used in (mem-expr). In categorical terms, the context-dependent proposition can be modelled as a graded comonad [18,38]. The evaluation of a preview with no context dependencies (built implicitly into our evaluation rules) corresponds to the counit operation of a comonad and would be explicitly written as A → A.…”

Section: B Theories Of Delayed Previewsmentioning

confidence: 99%

Foundations of a live data exploration environment

Petříček

2020

Programming

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A growing amount of code is written to explore and analyze data, often by data analysts who do not have a traditional background in programming, for example by journalists. The way such data anlysts write code is different from the way software engineers do so. They use few abstractions, work interactively and rely heavily on external libraries. We aim to capture this way of working and build a programming environment that makes data exploration easier by providing instant live feedback.We combine theoretical and applied approach. We present the data exploration calculus, a formal language that captures the structure of code written by data analysts. We then implement a data exploration environment that evaluates code instantly during editing and shows previews of the results. We formally describe an algorithm for providing instant previews for the data exploration calculus that allows the user to modify code in an unrestricted way in a text editor. Supporting interactive editing is tricky as any edit can change the structure of code and fully recomputing the output would be too expensive. We prove that our algorithm is correct and that it reuses previous results when updating previews after a number of common code edit operations. We also illustrate the practicality of our approach with an empirical evaluation and a case study.As data analysis becomes an ever more important use of programming, research on programming languages and tools needs to consider new kinds of programming workflows appropriate for those domains and conceive new kinds of tools that can support them. The present paper is one step in this important direction. ACM CCS 2012Human-centered computing → Interactive systems and tools; Information systems → Data mining;Software and its engineering → Compilers;Foundations of a live data exploration environment development and execution. Data analysts write small snippets of code, run them to see results immediately and then revise them.Notebooks are used by users ranging from scientists who implement complex models of physical systems to journalists who perform simple data aggregations and create visualizations. Our focus is on the simplest use cases. Making programmatic data exploration more spreadsheet-like should encourage users to choose programming tools over spreadsheets, resulting in more reproducible and transparent data analyses.Consider the Financial Times analysis of plastic waste [7,25]. It joins datasets from Eurostat, UN Comtrade and more, aggregates the data and builds a visualization comparing waste flows in 2017 and 2018. Figure 1 shows an excerpt from one notebook of the data analysis. The code has a number of important properties:There is no abstraction. The analysis uses lambda functions as arguments to library calls, but it does not define any custom functions. Code is parameterized by having a global variable material set to "plastics" and keeping other possible values in a comment. This lets the analyst run and check results of intermediate steps.The code relies on external lib...

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Section: B Theories Of Delayed Previewsmentioning

confidence: 99%

Foundations of a live data exploration environment

Petříček

2020

Programming

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“…Even though they do not originate from intuition about programs, monad laws are unanimously accepted by the programming community. In contrast, various extensions of monads [41,45] usually motivate the laws by programming intuition, but there is often little agreement on the laws. The best example is the MonadPlus extension that adds an operation of type M a → M a → M a.…”

Section: Reasoning About Programs Using Monadsmentioning

confidence: 99%

What we talk about when we talk about monads

Petříček

2018

Programming

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Computer science provides an in-depth understanding of technical aspects of programming concepts, but if we want to understand how programming concepts evolve, how programmers think and talk about them and how they are used in practice, we need to consider a broader perspective that includes historical, philosophical and cognitive aspects. In this paper, we develop such broader understanding of monads, a programming concept that has an infamous formal definition, syntactic support in several programming languages and a reputation for being elegant and powerful, but also intimidating and difficult to grasp. This paper is not a monad tutorial. It will not tell you what a monad is. Instead, it helps you understand how computer scientists and programmers talk about monads and why they do so. To answer these questions, we review the history of monads in the context of programming and study the development through the perspectives of philosophy of science, philosophy of mathematics and cognitive sciences.More generally, we present a framework for understanding programming concepts that considers them at three levels: formal, metaphorical and implementation. We base such observations on established results about the scientific method and mathematical entities -cognitive sciences suggest that the metaphors used when thinking about monads are more important than widely accepted, while philosophy of science explains how the research paradigm from which monads originate influences and restricts their use.Finally, we provide evidence for why a broader philosophical, sociological look at programming concepts should be of interest for programmers. It lets us understand programming concepts better and, fundamentally, choose more appropriate abstractions as illustrated in a number of case studies that conclude the paper. ACM CCS 2012General and reference → Surveys and overviews; Social and professional topics → History of computing;

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“…This provides a general characterisation of the control-flow, allowing various kinds of data flow analysis including may and must analyses. The encoding of ⊕ is thus dependent on the notion of effect and so we cannot give a general encoding (work on effect control-flow algebras elucidates this [36]). We can however encode a restricted version of case.…”

Section: Control Flow: Conditionals and Fixed-pointsmentioning

confidence: 99%

“…They are the type system representation of effect systems, a general class of static program analysis for collecting information on effects such as state, exceptions, or resource use [12,20,50]. Classes of effect analyses are often defined abstractly via a system parameterised by an algebra of effects such as semi-lattices in early work [20] or semiring and Kleene algebra-like structures later [36,38]. On the other hand, session types describe and restrict 1 At the University of Cambridge, Computer Laboratory from January 2016.…”

Section: Introductionmentioning

confidence: 99%

Effects as sessions, sessions as effects

OrchardDominic¹,

Yoshida²

2016

SIGPLAN Not.

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Effect and session type systems are two expressive behavioural type systems. The former is usually developed in the context of the lambda-calculus and its variants, the latter for the pi-calculus. In this paper we explore their relative expressive power. Firstly, we give an embedding from PCF, augmented with a parameterised effect system, into a session-typed pi-calculus (session calculus), showing that session types are powerful enough to express effects. Secondly, we give a reverse embedding, from the session calculus back into PCF, by instantiating PCF with concurrency primitives and its effect system with a session-like effect algebra; effect systems are powerful enough to express sessions. The embedding of session types into an effect system is leveraged to give a new implementation of session types in Haskell, via an effect system encoding. The correctness of this implementation follows from the second embedding result. We also discuss various extensions to our embeddings.

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Effect Systems Revisited—Control-Flow Algebra and Semantics

Cited by 25 publications

References 39 publications

Foundations of a live data exploration environment

Foundations of a live data exploration environment

What we talk about when we talk about monads

Effects as sessions, sessions as effects

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