- Haskell-Cafe - Haskell.org

lexing nested comments in GHC/Parser/Lexer.x
by Benjamin Redelings 11 Feb '21

11 Feb '21

Hi, I notice that in Lexer.x for GHC nested comments are parsed using a special function, with the comment "nested comments require traversing by hand, they can't be parsed using regular expressions." While I see that nested comments can't be parsed using regular expressions, the lexer has a state stack, and so it seems like nested comments could be parsed by pushing a new "nested comment" state onto the lexer state every time a "{-" is encountered. But perhaps this is not done because its not clear how to make the entire comment into a single token that way? This might be a naive question -- I don't have that much experience with lexers. Thanks! -BenRI

2 1

International Conference on Recent Theories and Applications in Transportation and Mobility - (RTATM 2021) Prague
by matteo＠confscience.com 10 Feb '21

10 Feb '21

Call for papers ************************************************* International Conference on Recent Theories and Applications in Transportation and Mobility - (RTATM 2021) Prague - Czech Republic, October 14-15, 2021 https://confscience.com/rtatm/ Submission deadline: April 1, 2021 All papers accepted in RTATM 2021 will be published in Springer CCIS (Communications in Computer and Information Science). CCIS is abstracted/indexed in Scopus, SCImago, EI-Compendex, Mathematical Reviews, DBLP, Google Scholar, and Thomson Reuters Conference Proceedings Citation (Former ISI Proceedings) *************************************************************************** IMPORTANT DATES: - Paper Submission: April 1, 2021 - Acceptance Notification: July 1, 2021 - Final Manuscript Due: September 1, 2021 *************************************************************************** The RTATM 2021 conference will be held in Conjunction with: International Conference on Applied Data Science and Intelligence (ADSI 2021) International Conference on Informatics Revolution for Smarter Healthcare (IRSH 2021) *************************************************************************** TOPICS: Authors are invited to submit their original papers to address the topics of the conference, including but not limited to: FUNDAMENTALS AND THEORIES - Modelling and Simulation Algorithms - Vehicular Wireless Medium Access Control - V2X communications - Routings and Protocols for Connected Vehicles - Mobility Models and Architectures - Distribution Strategies - Traffic Incident Management Systems - Bio-Inspired Approaches - Optimization and Collaboration - Automatic Control in Vehicular Networks - Energy-aware Connected Mobility - Programming Languages - Sustainable Transportation - Multimodal Transportation Networks and Systems - Systemsb Integration - Driver Behavior Models and Simulation - Human Factors and Travel Behaviour - Green Mobility - Regulations and Bylaws for Intelligent - Transportation and Mobility SMART TRANSPORTATION AND LOGISTICS - Mobility Management - Connected Vehicles - VANETs - Predictive Logistics - Spatio-Temporal Event Tracking - Decision Support Systems - Emergency Management - Logistics and E-Commerce - Supply Chain Design and Execution - Supply Chain Management - Advanced Planning Systems - Fleet Management - Multi-Agent Systems - Machine Learning for Smart Logistics - Intelligent Infrastructures - Real-time Analysis of Comprehensive Supply Chain Data - Smart Synchronization of Logistics Processes - New Approaches for Cost Transparency - Big Data for Smart Logistics - Logistics 4.0 - Mobile Networks - Next-Generation Smart Logistics - Performance Management Approaches - Tests and Deployment - Software Defined Networks - Smart Freight Management - Smart Shipment Management - Smart Warehousing - Smart Inventory management DATA AND SERVICES - Real-Time transportation Data Acquisition - Event Detection and Monitoring - Data Warehouses for connected mobility - Data mining and Data analytics - Data Worthiness in Connected Vehicles - Data Trustworthiness for effective transportation and mobility - Road Traffic Data Analytics - Structured and Unstructured Data for Connected Mobility - Volunteered Geographic Information (VGI) - Data Representation for Connected Mobility - Transportation Data Mining - Transportation and mobility Data Visualization - Cognitive and Context-aware Intelligence - Transportation Decision Support Systems - Mobility as a Service (MaaS) - Intelligent Transportation Services - Smart Mobility Services - Big Data and Vehicle Analytics - Massive Data Management - Collective and connected Intelligence - Next Generation Services - Driver Behaviour Analysis - Geo-Spatial Services - Service-Oriented Architecture (SOA) - Web and Mobile Services SAFETY, SECURITY, AND HAZARD MANAGEMENT - Security Issues in Vehicular Communications - Safety Applications of Connected Vehicles - Weather-related Safety solutions - V2V, V2I and I2V Road Safety Applications - Connected Mobility for Hazard Management - Risk Management - Road Traffic Crashes Analytics - Traffic Jam Prediction - Resource Allocation for Hazard Management - Trust and Privacy Issues in Logistics - Management of Exceptional Events - New approaches to Networking Security for Transportation Applications - Failure modes, human factors, software safety - Automated Failure Analysis - Performance and Human Error Analysis - Design and Reliability of Control Systems - Dispersion Modelling Software - Quantification of Risk *************************************************************************** OUTSTANDING PAPERS: Based on the peer review scores as well as the presentations at the conference, the authors of outstanding papers will be invited to extend their works for a potential publication in journals special issues with high impact factors. *************************************************************************** PAPER SUBMISSION: Papers must be submitted electronically as PDF files via easychair (https://easychair.org/conferences/?conf=rtatm2021) All papers will be peer reviewed. Length of Full papers: 12-15 pages long (written in the LNCS/CCIS one-column page format, 400 words per page) Length of Short papers: less than 12 pages For more information, please refer to the conference website: https://confscience.com/rtatm/ *************************************************************************** CONTACT For more information, please send an email to info-rtatm(a)confscience.com

1 0

21st Midlands Graduate School in the Foundations of Computing Science: Call for Participation
by Andrei Popescu 09 Feb '21

09 Feb '21

CALL FOR PARTICIPATION 21st Midlands Graduate School in the Foundations of Computing Science MGS 21 12-16 April 2021, virtually https://staffwww.dcs.shef.ac.uk/people/G.Struth/mgs21.html OVERVIEW The annual Midlands Graduate School in the Foundations of Computing Science (MGS) offers an intensive programme of lectures on the mathematical foundations of computing. It addresses first of all PhD students in their first or second year, but is open to anyone interested in its topics, from academia to industry and around the world. The MGS has been run since 1999 and is hosted alternately by the Universities of Birmingham, Leicester, Nottingham and Sheffield. MGS 21 is its 21st incarnation. Information about previous events can be found at the MGS web site http://www.cs.nott.ac.uk/MGS PROGRAMME MGS 21 consists of eight courses, each with four or five hours of lectures and a similar number of exercise sessions. Three courses are introductory; one is given by an invited lecturer. These should be attended by all participants. The remaining more advanced courses should be selected based on interest. MGS 21 aims at a mix of livestreamed and prerecorded lectures and livestreamed exercise sessions, with additional social online events. Invited lectures: Monads and Interactions Tarmo Uustalu, Reykjavik Introductory courses: Category Theory Jacopo Emmenegger, Birmingham Type Theory Thorsten Altenkirch, Nottingham Proof Theory Anupam Das, Birmingham Advanced courses: Homotopy Type Theory Nicolai Kraus, Nottingham Inductive and Coinductive Reasoning with Isabelle/HOL Andrei Popescu, Sheffield Effects and Call-by-Push-Value Paul Levy, Birmingham Formal Modelling and Analysis of Concurrent Systems Mohammad Mousavi, Leicester In addition we are organising a session where participants can briefly present and discuss their own research. A call will be made in March. REGISTRATION Participation at MGS 21 is free of charge, but selective. Requests must be submitted online via https://staffwww.dcs.shef.ac.uk/people/G.Struth/mgs21.html Registration deadline is April 1. ORGANISATION Please direct all queries about MGS 21 to Georg Struth. The Sheffield organisers are Harsh Beohar (H.Beohar(a)sheffield.ac.uk) Andrei Popescu (A.Popescu(a)sheffield.ac.uk) Georg Struth (G.Struth(a)sheffield.ac.uk)

1 0

Postdoc Position (up to 3 years) at St Andrews
by Christopher Brown 09 Feb '21

09 Feb '21

Dear All I have an opening for a postdoc to work on a new 3-year EPSRC project in the Programming Languages group at St Andrews. The deadline has been extended to the 26th February. Send me an email (cmb21(a)st-andrews.ac.uk<mailto:cmb21@st-andrews.ac.uk>) if you’d like to informally chat about the post. I’m very happy to chat to you. Thanks Chris Lecturer in Computer Science University of St Andrews Scotland -------------------- The Programming Languages Group seeks a Research Fellow to work on the newly funded 3-year EPSRC project, Energise: Refactorings and Skeletons for Energy-Aware Applications on High-Performance Embedded Systems. Embedded devices, such as mobile phones, drones, medical devices and even satellite imaging are now common place in society. These types of devices rely very heavily on battery power, contributing to climate change and global warming. Optimizing the software that runs on such devices for energy is a very challenging problem for software developers. The Energise project aims to address this issue by providing the developer with a refactoring tool to repurpose their software to make it consume less energy, and to do it in such a way that the code is guaranteed to still meet its specification. The Energise project aims to develop new, formally-motivated, refactorings and transformations that reduce energy consumption for embedded multi-core devices. This includes implementing refactorings for target languages such as C; proving general soundness of the refactorings using e.g. dependent types; developing new programming abstractions (skeletons) for common energy-reducing programming patterns; running experiments; writing proofs of correctness, etc. The post will require skills in formal semantics of programming languages, compilers, program transformation, lightweight formal methods (including, e.g. dependent types) and knowledge of parallelism and non-functional properties, including energy. Informal enquiries can be directed to Dr Chris Brown (cmb21(a)st-andrews.ac.uk<mailto:cmb21@st-andrews.ac.uk>). Applications are particularly welcome from women, people from the Black, Asian, Minority or Ethnic (BAME) community and other protected characteristics who are under-represented in research posts at the University. The University is committed to equality for all, demonstrated through our working on diversity awards (ECU Athena SWAN/Race Charters; Carer Positive; LGBT Charter; and Stonewall). More details can be found at http://www.st-andrews.ac.uk/hr/edi/diversityawards/. Interviews will be held on TBC. Please quote ref: AR2474MR Closing Date: 26 February 2021 School of Computer Science Salary: £33,797 - £36,914 per annum Fixed Term: 3 years Start: As soon as possible More details at: https://www.vacancies.st-andrews.ac.uk/Vacancies/W/6918/0/284952/889/resear…

1 0

tls 1.5.5
by Kazu Yamamoto 08 Feb '21

08 Feb '21

Hi all, I would like to announce that tls 1.5.5 has been released. The main purpose of this version is provide the Network.TLS.QUIC module. This is the first step to bring QUIC to the Haksell community. Changelog says: - QUIC support [#419](https://github.com/vincenthz/hs-tls/pull/419) [#427](https://github.com/vincenthz/hs-tls/pull/427) [#428](https://github.com/vincenthz/hs-tls/pull/428) [#430](https://github.com/vincenthz/hs-tls/pull/430) [#433](https://github.com/vincenthz/hs-tls/pull/433) [#441](https://github.com/vincenthz/hs-tls/pull/441) - Server ECDSA for P-256 [#436](https://github.com/vincenthz/hs-tls/pull/436) - Sort ciphersuites based on hardware-acceleration support [#439](https://github.com/vincenthz/hs-tls/pull/439) - Sending no_application_protocol [#440](https://github.com/vincenthz/hs-tls/pull/440) - Internal improvements [#426](https://github.com/vincenthz/hs-tls/pull/426) [#431](https://github.com/vincenthz/hs-tls/pull/431) Technical information can be found from the following blog posts: - Implementation status of QUIC in Haskell https://kazu-yamamoto.hatenablog.jp/entry/2020/02/18/145038 - Improving QUIC APIs of the TLS library in Haskell https://kazu-yamamoto.hatenablog.jp/entry/2020/09/16/150801 - The Current Plan for Haskell QUIC https://kazu-yamamoto.hatenablog.jp/entry/2020/10/23/141648 IMPORTANT NOTE: If you want to make "tls" faster, please install "cryptonite" with the "support_pclmuldq" flag: % cabal install cryptonite -f support_pclmuldq This enables hardware acceleration for the GCM part of AES-GCM. If you use old GCC, you need to disable the "use_target_attributes" flag: % cabal install cryptonite -f support_pclmuldq -f-use_target_attributes --Kazu

1 0

Haskell exercises for beginners
by Olaf Klinke 06 Feb '21

06 Feb '21

> Hello Haskell Café, > > I have been working on a website aimed at teaching programming and Computer > Science through quick examples. It is called "Computer Science by Example > <https://cscx.org/>;": https://cscx.org/ > > The exercises start very simple (e.g. read two numbers and print their sum > <https://cscx.org/add>;) then increase in difficulty and complexity > gradually (e.g. solving the change-making problem <https://cscx.org/cash>;). > The website has an "online judge" functionality where students can submit > their solutions which are tested and graded automatically without human > intervention. It currently supports solutions in *Haskell* and > additionally: Python, C, C++, C#, Java, JavaScript, Lua and Ruby. > > The exercises are useful not only to first time programmers, but also to > experienced programmers trying to learn a new language such as Haskell. > > Check it out at cscx.org. The exercises are freely available for anyone to > try. > > Best Regards, > Rudy Dear Rudy, thanks for sharing all these excercises. Automated grading has many advantages. The kind of automated grading cscx uses lets the program use stdin and stdout. However, for Haskell (and all other programming languages too) this means that students are, from the very beginning, forced to write parsers for the data the grading system gives on stdin. This means that either * You limit input data to stuff with built-in parsers (which you don't) * You teach proper parsing early, which is non-trivial, or * You permit the students develop an ad-hoc and potentially messy style of coping with unstructured input. In all the excercises I looked at, the grading specification does not say what the program should do with invalid input. Therefore messy ad- hoc parsing is what you should expect to see in, and in some cases comprise the largest part of, submitted solutions. Others may disagree whether this is to be prevented or not. I have limited experience in teaching. In some other CS courses the excercises give a program fragment which is to be completed by the student. In Haskell you could use property- based testing [1] like QuickCheck or doctests to do the heavy lifting for you, while at the same time presenting the students with an infinity of test cases. Another way might be to provide a random generator of structured test data, and the student's task is to write a program that echoes the random data together with the computed result. That way, you could still use the stdout-based automated grading. Example of QuickCheck-based grading: module Triple1 where -- Your task: Complete this function -- so that for example -- -- >>> triple 2 -- 6 -- >>> triple 123 -- 369 triple :: Integer -> Integer triple = undefined -- Automated grading appends the following and runs -- quickCheck prop_triple prop_triple :: Integer -> Bool prop_triple = triple n == 3*n Example of Random-based grading: module Triple1 where -- Your task: complete this function -- so that for example -- -- >>> pure 2 >>= triple -- 2 -- 6 triple :: Integer -> IO () triple n = do print n undefined -- Automated grading compiles -- main = (yourIntegerGenerator :: IO Integer) >>= triple -- and executes repeatedly. Kind regards Olaf [1] https://www.cs.tufts.edu/~nr/cs257/archive/john-hughes/automatic-grading.pdf

1 0

International Conference on Applied Data Science and Intelligence - (ADSI 2021) Prague
by matteo＠confscience.com 06 Feb '21

06 Feb '21

Call for papers ************************************************* International Conference on Applied Data Science and Intelligence - (ADSI 2021) Prague- Czech Republic, October 14-15, 2021 https://confscience.com/adsi/ Submission deadline: April 1, 2021 All papers accepted in ADSI 2021 will be published in Springer CCIS (Communications in Computer and Information Science). CCIS is abstracted/indexed in Scopus, SCImago, EI-Compendex, Mathematical Reviews, DBLP, Google Scholar, and Thomson Reuters Conference Proceedings Citation (Former ISI Proceedings) *************************************************************************** IMPORTANT DATES: - Paper Submission: April 1, 2021 - Acceptance Notification: July 1, 2021 - Final Manuscript Due: September 1, 2021 *************************************************************************** The ADSI 2021 conference will be held in Conjunction with: International Conference on Recent Theories and Applications in Transportation and Mobility (RTATM 2021) International Conference on Informatics Revolution for Smarter Healthcare (IRSH 2021) *************************************************************************** TOPICS: Authors are invited to submit their original papers to address the topics of the conference, including but not limited to: FUNDAMENTALS AND THEORIES - Theoretical Models - Spatial and temporal multi-models - Multi-dimensional data - Data acquisition and pre-processing - Data inference - Data Classification and Taxonomy - Data Metrics - New approaches for collaboration and competition - Self-organization, self-healing, fault-tolerance approaches - Spatial reasoning - Context awareness - Intelligent mobility - New approaches to supervised and unsupervised learning - New approaches for security, privacy, trust, and ethics in data science - Real-time data analytics - Multi-Agent Systems for data science - Distributed data analytics - Data authenticity - New theories and approaches for Deep learning - New approaches for Business Intelligence - Fuzzy logic - Decision trees - Support vector machines - Evolutionary computation - Statistical methods - Collaborative filtering - Data engineering - Content mining - Indexing schemes - Information retrieval - Metadata use and management INTELLIGENT DATA PROCESSING AND ANALYTICS - Multi-level data processing - Data analytics optimization - Smart data mining - Machine Learning - Deep Learning - Bio-Inspired Computing - Secure data analytics - Privacy in data analytics - Trust in Big Data - Business intelligence - Visualization Analytics - Intelligence as a Service (IaaS) - Data Science as a Service (DSaaS) - Natural Language Processing - Signal Processing - Simulation and Modeling - Data-Intensive Computing SYSTEMS AND INFRASTRUCTURES - Data storage infrastructure - Data warehouses - Data Query and Indexing Technologies - Software Defined Infrastructures - Software Defined Networks (SDN) - Distributed data systems - Smart grid computing - Intelligent data management - Big Data computing - Smart data networking - Internet of Things - Cyber Physical Systems - Blockchain - Fog and Edge intelligence - Parallel Computing systems - Open Source systems for data science - Embedded intelligence - Embedded data science - In-Memory computing - Intelligent drones - Internet of Drones - Real-time data acquisition systems APPLICATIONS - Intelligent Hazard management - Intelligent data science in healthcare - Intelligent data science in farming - Intelligent data science in Oil and Gas - Smart logistics - Intelligent data science in transportation - Intelligent data science in surveillance - Xtech (Fintech, Agritech, etc.) - Intelligent drones - Digital transformation - Bioinformatics - Marketing - Social Science - E-learning and E-services *************************************************************************** OUTSTANDING PAPERS: Based on the peer review scores as well as the presentations at the conference, the authors of outstanding papers will be invited to extend their works for a potential publication in journals special issues with high impact factors. *************************************************************************** PAPER SUBMISSION: Papers must be submitted electronically as PDF files via easychair (https://easychair.org/conferences/?conf=adsi2021) All papers will be peer reviewed. Length of Full papers: 12-15 pages long (written in the LNCS/CCIS one-column page format, 400 words per page) Length of Short papers: less than 12 pages For more information, please refer to the conference website: https://confscience.com/adsi/ *************************************************************************** CONTACT For more information, please send an email to info-adsi(a)confscience.com

1 0

Haskell exercises for beginners
by Rudy Matela 05 Feb '21

05 Feb '21

Hello Haskell Café, I have been working on a website aimed at teaching programming and Computer Science through quick examples. It is called "Computer Science by Example <https://cscx.org/>": https://cscx.org/ The exercises start very simple (e.g. read two numbers and print their sum <https://cscx.org/add>) then increase in difficulty and complexity gradually (e.g. solving the change-making problem <https://cscx.org/cash>). The website has an "online judge" functionality where students can submit their solutions which are tested and graded automatically without human intervention. It currently supports solutions in *Haskell* and additionally: Python, C, C++, C#, Java, JavaScript, Lua and Ruby. The exercises are useful not only to first time programmers, but also to experienced programmers trying to learn a new language such as Haskell. Check it out at cscx.org. The exercises are freely available for anyone to try. Best Regards, Rudy

1 0

International Conference on Recent Theories and Applications in Transportation and Mobility - (RTATM 2021) Prague
by matteo＠confscience.com 04 Feb '21

04 Feb '21

Call for papers ************************************************* International Conference on Recent Theories and Applications in Transportation and Mobility - (RTATM 2021) Prague - Czech Republic, October 14-15, 2021 https://confscience.com/rtatm/ Submission deadline: April 1, 2021 All papers accepted in RTATM 2021 will be published in Springer CCIS (Communications in Computer and Information Science). CCIS is abstracted/indexed in Scopus, SCImago, EI-Compendex, Mathematical Reviews, DBLP, Google Scholar, and Thomson Reuters Conference Proceedings Citation (Former ISI Proceedings) *************************************************************************** IMPORTANT DATES: - Paper Submission: April 1, 2021 - Acceptance Notification: July 1, 2021 - Final Manuscript Due: September 1, 2021 *************************************************************************** The RTATM 2021 conference will be held in Conjunction with: International Conference on Applied Data Science and Intelligence (ADSI 2021) International Conference on Informatics Revolution for Smarter Healthcare (IRSH 2021) *************************************************************************** TOPICS: Authors are invited to submit their original papers to address the topics of the conference, including but not limited to: FUNDAMENTALS AND THEORIES - Modelling and Simulation Algorithms - Vehicular Wireless Medium Access Control - V2X communications - Routings and Protocols for Connected Vehicles - Mobility Models and Architectures - Distribution Strategies - Traffic Incident Management Systems - Bio-Inspired Approaches - Optimization and Collaboration - Automatic Control in Vehicular Networks - Energy-aware Connected Mobility - Programming Languages - Sustainable Transportation - Multimodal Transportation Networks and Systems - Systemsb Integration - Driver Behavior Models and Simulation - Human Factors and Travel Behaviour - Green Mobility - Regulations and Bylaws for Intelligent - Transportation and Mobility SMART TRANSPORTATION AND LOGISTICS - Mobility Management - Connected Vehicles - VANETs - Predictive Logistics - Spatio-Temporal Event Tracking - Decision Support Systems - Emergency Management - Logistics and E-Commerce - Supply Chain Design and Execution - Supply Chain Management - Advanced Planning Systems - Fleet Management - Multi-Agent Systems - Machine Learning for Smart Logistics - Intelligent Infrastructures - Real-time Analysis of Comprehensive Supply Chain Data - Smart Synchronization of Logistics Processes - New Approaches for Cost Transparency - Big Data for Smart Logistics - Logistics 4.0 - Mobile Networks - Next-Generation Smart Logistics - Performance Management Approaches - Tests and Deployment - Software Defined Networks - Smart Freight Management - Smart Shipment Management - Smart Warehousing - Smart Inventory management DATA AND SERVICES - Real-Time transportation Data Acquisition - Event Detection and Monitoring - Data Warehouses for connected mobility - Data mining and Data analytics - Data Worthiness in Connected Vehicles - Data Trustworthiness for effective transportation and mobility - Road Traffic Data Analytics - Structured and Unstructured Data for Connected Mobility - Volunteered Geographic Information (VGI) - Data Representation for Connected Mobility - Transportation Data Mining - Transportation and mobility Data Visualization - Cognitive and Context-aware Intelligence - Transportation Decision Support Systems - Mobility as a Service (MaaS) - Intelligent Transportation Services - Smart Mobility Services - Big Data and Vehicle Analytics - Massive Data Management - Collective and connected Intelligence - Next Generation Services - Driver Behaviour Analysis - Geo-Spatial Services - Service-Oriented Architecture (SOA) - Web and Mobile Services SAFETY, SECURITY, AND HAZARD MANAGEMENT - Security Issues in Vehicular Communications - Safety Applications of Connected Vehicles - Weather-related Safety solutions - V2V, V2I and I2V Road Safety Applications - Connected Mobility for Hazard Management - Risk Management - Road Traffic Crashes Analytics - Traffic Jam Prediction - Resource Allocation for Hazard Management - Trust and Privacy Issues in Logistics - Management of Exceptional Events - New approaches to Networking Security for Transportation Applications - Failure modes, human factors, software safety - Automated Failure Analysis - Performance and Human Error Analysis - Design and Reliability of Control Systems - Dispersion Modelling Software - Quantification of Risk *************************************************************************** OUTSTANDING PAPERS: Based on the peer review scores as well as the presentations at the conference, the authors of outstanding papers will be invited to extend their works for a potential publication in journals special issues with high impact factors. *************************************************************************** PAPER SUBMISSION: Papers must be submitted electronically as PDF files via easychair (https://easychair.org/conferences/?conf=rtatm2021) All papers will be peer reviewed. Length of Full papers: 12-15 pages long (written in the LNCS/CCIS one-column page format, 400 words per page) Length of Short papers: less than 12 pages For more information, please refer to the conference website: https://confscience.com/rtatm/ *************************************************************************** CONTACT For more information, please send an email to info-rtatm(a)confscience.com

2 1

TH: quoting name and value
by Sylvain Henry 02 Feb '21

02 Feb '21

Hi, I have the following kind of template haskell code: module Foo where foo :: String -> Name -> Q [Dec] foo str name = return [] module Bar where bar :: String bar = "whatever" module FooBar where import Foo import Bar foo bar 'bar It works great as in `foo` I can use both bar's Name and bar's value computed at compile time. But it's unsafe for my purpose because a user could call: `foo "fakeBarValue" 'bar` So the question is: is there a way to write `foo` so that it can only be used safely? If not, I guess it could be possible to add a new kind of quote to TH, something like: data Named a = Named Name a -- constructor not exported so that Named values can't be forged by users. [namedValue||bar||] :: Named String -- new quote What do you think? Thanks, Sylvain

2 2