~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 16th European Lisp Symposium In-Cooperation-With: ACM SIGLAN

Call for Participation

April 24-25, 2023 Startup Village, Amsterdam, Nederlands

https://www.european-lisp-symposium.org/2023

Sponsored by EPITA, DIRO, MLPrograms, Franz Inc., and SISCOG ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

Recent News ~~~~~~~~~~~ Registrer now. Early bird discount closing soon! Keynote details now available.

Important Dates ~~~~~~~~~~~~~~~ - Final papers due: April 9, 2023 - Early registration deadline: April 9, 2023 - Symposium: April 24-25, 2023

Scope ~~~~~

The European Lisp Symposium is a premier forum for the discussion and dissemination of all aspects of design, implementation, and application of any of the Lisp dialects, including Common Lisp, Scheme, Emacs Lisp, Clojure, Racket, ACL2, AutoLisp, ISLISP, Dylan, SKILL, Hy, Shen, Carp, Janet, uLisp, Picolisp, Gamelisp, TXR, and so on. We encourage everyone interested in Lisp to participate.

The European Lisp Symposium invites high quality papers about novel research results, insights and lessons learned from practical applications, and educational perspectives. We also encourage submissions about known ideas as long as they are presented in a new setting and/or in a highly elegant way.

Topics include but are not limited to:

- context-, aspect-, domain-oriented and generative programming - macro-, reflective-, meta- and/or rule-based development approaches - language design and implementation - language integration, inter-operation, and deployment - development methodologies, support, and environments - educational approaches and perspectives - experience reports and case studies

Keynotes ~~~~~~~~ ##### Artificial Intelligence: a Problem of Plumbing? -- Gerald J. Sussman, MIT CSAIL, USA

We have made amazing progress in the construction and deployment of systems that do work originally thought to require human-like intelligence. On the symbolic side we have world-champion Chess-playing and Go-playing systems. We have deductive systems and algebraic manipulation systems that exceed the capabilities of human mathematicians. We are now observing the rise of connectionist mechanisms that appear to see and hear pretty well, and chatbots that appear to have some impressive linguistic ability. But there is a serious problem. The mechanisms that can distinguish pictures of cats from pictures of dogs have no idea what a cat or a dog is. The chatbots have no idea what they are talking about. The algebraic systems do not understand anything about the real physical world. And no deontic logic system has any idea about feelings and morality.

So what is the problem? We generally do not know how to combine systems so that a system that knows how to solve problems of class A and another system that knows how to solve problems of class B can be combined to solve not just problems of class A or class B but can solve problems that require both skills that are needed for problems of class A and skills that are needed for problems of class B.

Perhaps this is partly a problem of plumbing. We do not have linguistic structures that facilitate discovering and building combinations. This is a fundamental challenge for the programming-language community. We need appropriate ideas for abstract plumbing fittings that enable this kind of cooperation among disparate mechanisms. For example, why is the amazingly powerful tree exploration mechanism that is used for games not also available, in the same system, to a deductive engine that is being applied to a social interaction problem?

I will attempt to elucidate this problem and perhaps point at avenues of attack that we may work on together.

##### Hedy: Gradual, Multi-Lingual, and Teacher-Centric Programming Education -- Felienne Hermans, Vrije Universiteit Amsterdam, Nederlands

When kids learn to program they often use either a visual language like Scratch, or a textual language like Python. While visual languages are great for the first steps, children and educators often want to move on to textual languages. However, early on, a textual language and its error messages can be scary. Hedy aims to bridge this gap with a programming language that is gradual, using different language levels.

In level 1, there is hardly any syntax at all; printing is done with: print hello!

At every level, new syntax and concepts are added, so learners do not have to master everything at once. Hedy builds up to a subset of Python including conditions, loops, variables, and lists.

To make learning as accessible as possible, Hedy also allows for the use of localized keywords, f.e in Spanish: imprimir Hello! Hedy (www.hedy.org) was launched in early 2020 and over 5 million Hedy progams have been created to date, and has been translated into 46 languages.

##### A Language-Based Approach to Programming with Serialized Data -- Michael Vollmer, School of Computing, University of Kent, UK

It is common for software running today to use object representations fixed by the language runtime system; both the Java and Haskell runtimes dictate an object layout, and the compiler must stick to it for all programs. And yet when humans optimize a program, one of their primary levers on performance is changing data representation. For example, an HPC programmer knows how to pack a regular tree into a byte array for more efficient access. Unfortunately, this is error-prone, making it an undesirable way to achieve performance optimization at the expense of safety and readability.

Furthermore, whenever a program receives data from the network or disk, rigid insistence on a particular heap layout causes an impedance mismatch we know as deserialization. Data represented in memory has pointers and arbitrary, sparse layout, while data on disk is packed contiguously, so data must be transformed from one form to another and back.

Programming with serialized data is a technique for unifying the in-memory and on-disk representations of data, where the serialized form is used both on-disk and in-memory. This technique allows data processing programs to skip the deserialization/reserialization steps by operating directly on the data in its serialized form. It also represents a principled approach to optimizing programs by compacting data representations, which increases locality and minimizes indirection.

In this talk, I will present a programming language, LoCal, for programming with serialized data. I will also describe Gibbon, an experimental compiler that automatically transforms functional programs to operate on serialized data.

##### Run-Time Verification of Communication Protocols in Clojure -- Sung-Shik Jongmans, Open Universiteit, Nederlands

To simplify shared-memory concurrent programming, languages have started to offer core support for high-level communications primitives, in the form of message passing though channels, in addition to lower-level synchronization primitives. Yet, a growing body of evidence suggests that channel-based programming abstractions also have their issues.

The Discourje project aims to help programmers cope with channels and concurrency bugs in Clojure programs, based on dynamic analysis. The idea is that programmers write not only implementations of communication protocols in their Clojure programs, but also specifications. Discourje then offers a run-time verification library to ensure that channel actions in implementations are safe relative to specifications.

Programme Chair ~~~~~~~~~~~~~~~ Stefan Monnier, DIRO, Université de Montréal, Canada

Programme Committee ~~~~~~~~~~~~~~~~~~~ Mark Evenson, not.org, Austria Marco Heisig, Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany Ioanna Dimitriou, Igalia S.L., Germany Robert Smith, HRL Laboratories Mattias Engdegård Marc Feeley, Université de Montréal, Canada Marc Battyani, FractalConcept Alan Ruttenberg, National Center for Ontological Research, USA Nick Levine, RavenPack, Spain Ludovic Courtès, Inria, France Matthew Flatt, University of Utah, USA Irène Durand, Université Bordeaux 1, France Jay McCarthy, Brigham Young University, USA Ambrose Bonnaire-Sergeant, Cisco Christopher League, Long Island University, NY, USA Pascal Costanza, Intel, Belgium Christian Queinnec

Local Chair ~~~~~~~~~~~ Breanndán Ó Nualláin, Machine Learning Programs, Nederlands