Baptiste Esteban, Edwin Carlinet, G. Tochon, D. Verna
Generic programming is a powerful paradigm abstracting data structures and algorithms to improve their reusability, as long as they respect a given interface. Coupled with a performance-driven language, it is a paradigm of choice for scientific libraries where the implementation of manipulated objects may change depending on their use case, or for performance purposes. In those performance-driven languages, genericity is often implemented statically to perform some optimization. This does not fit well with the dynamism needed to handle objects which may only be known at runtime. Thus, in this article, we evaluate a model that couples static genericity with a dynamic model based on type erasure in the context of image processing. Its cost is assessed by comparing the performance of the implementation of some common image processing algorithms in C++ and Rust, two performance-driven languages supporting some form of genericity. Finally, we demonstrate that compile-time knowledge of some specific information is critical for performance, and also that the runtime overhead depends on the algorithmic scheme in use.
{"title":"The Cost of Dynamism in Static Languages for Image Processing","authors":"Baptiste Esteban, Edwin Carlinet, G. Tochon, D. Verna","doi":"10.1145/3564719.3568693","DOIUrl":"https://doi.org/10.1145/3564719.3568693","url":null,"abstract":"Generic programming is a powerful paradigm abstracting data structures and algorithms to improve their reusability, as long as they respect a given interface. Coupled with a performance-driven language, it is a paradigm of choice for scientific libraries where the implementation of manipulated objects may change depending on their use case, or for performance purposes. In those performance-driven languages, genericity is often implemented statically to perform some optimization. This does not fit well with the dynamism needed to handle objects which may only be known at runtime. Thus, in this article, we evaluate a model that couples static genericity with a dynamic model based on type erasure in the context of image processing. Its cost is assessed by comparing the performance of the implementation of some common image processing algorithms in C++ and Rust, two performance-driven languages supporting some form of genericity. Finally, we demonstrate that compile-time knowledge of some specific information is critical for performance, and also that the runtime overhead depends on the algorithmic scheme in use.","PeriodicalId":423660,"journal":{"name":"Proceedings of the 21st ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122218511","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}
Evgeny Kusmenko, Maximilian Münker, Matthias Nadenau, Bernhard Rumpe
Turn-based games such as chess are very popular, but tool-chains tailored for their development process are still rare. In this paper we present a model-driven and generative toolchain aiming to cover the whole development process of rule-based games. In particular, we present a game description language enabling the developer to model the game in a logics-based syntax. An executable game interpreter is generated from the game model and can then act as an environment for reinforcement learning-based self-play training of players. Before the training, the deep neural network can be modeled manually by a deep learning developer or generated using a heuristics estimating the complexity of mapping the state space to the action space. Finally, we present a case study modeling three games and evaluate the language features as well as the player training capabilities of the toolchain.
{"title":"A Model-Driven Generative Self Play-Based Toolchain for Developing Games and Players","authors":"Evgeny Kusmenko, Maximilian Münker, Matthias Nadenau, Bernhard Rumpe","doi":"10.1145/3564719.3568687","DOIUrl":"https://doi.org/10.1145/3564719.3568687","url":null,"abstract":"Turn-based games such as chess are very popular, but tool-chains tailored for their development process are still rare. In this paper we present a model-driven and generative toolchain aiming to cover the whole development process of rule-based games. In particular, we present a game description language enabling the developer to model the game in a logics-based syntax. An executable game interpreter is generated from the game model and can then act as an environment for reinforcement learning-based self-play training of players. Before the training, the deep neural network can be modeled manually by a deep learning developer or generated using a heuristics estimating the complexity of mapping the state space to the action space. Finally, we present a case study modeling three games and evaluate the language features as well as the player training capabilities of the toolchain.","PeriodicalId":423660,"journal":{"name":"Proceedings of the 21st ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences","volume":"123 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127059224","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}
Incremental computations react to input changes by updating their outputs. Compared to a non-incremental rerun, incremental computations can provide order-of-magnitude speedups, since often small input changes trigger small output changes. One popular means for implementing incremental computations is to encode the computation in Datalog, for which efficient incremental solvers exist. However, Datalog is very restrictive in terms of the data types it can process: Atomic data organized in relations. While structured tree and graph-shaped data can be encoded in relations, a naive encoding inhibits incrementality. In this paper, we present an encoding of structured data in Datalog that supports efficient incrementality such that small input changes are expressible. We explain how to efficiently implement and integrate this encoding into an existing incremental Datalog engine, and we show how tree diffing algorithms can be used to change the encoded data.
{"title":"Incremental Processing of Structured Data in Datalog","authors":"André Pacak, Tamás Szabó, Sebastian Erdweg","doi":"10.1145/3564719.3568686","DOIUrl":"https://doi.org/10.1145/3564719.3568686","url":null,"abstract":"Incremental computations react to input changes by updating their outputs. Compared to a non-incremental rerun, incremental computations can provide order-of-magnitude speedups, since often small input changes trigger small output changes. One popular means for implementing incremental computations is to encode the computation in Datalog, for which efficient incremental solvers exist. However, Datalog is very restrictive in terms of the data types it can process: Atomic data organized in relations. While structured tree and graph-shaped data can be encoded in relations, a naive encoding inhibits incrementality. In this paper, we present an encoding of structured data in Datalog that supports efficient incrementality such that small input changes are expressible. We explain how to efficiently implement and integrate this encoding into an existing incremental Datalog engine, and we show how tree diffing algorithms can be used to change the encoded data.","PeriodicalId":423660,"journal":{"name":"Proceedings of the 21st ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129285960","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}
The operational behavior of control operators has been studied comprehensively in the past few decades, but type systems of control operators have not. There are distinct type systems for shift, control, and shift0 without any relationship between them, and there has not been a type system that directly corresponds to control0. This paper remedies this situation by giving a uniform type system for all the four control operators. Following Danvy and Filinski’s approach, we derive a monomorphic type system from the CPS interpreter that defines the operational semantics of the four control operators. By implementing the typed CPS interpreter in Agda, we show that the CPS translation preserves types and that the calculus with all the four control operators is terminating. Furthermore, we show the relationship between our type system and the previous type systems for shift, control, and shift0.
{"title":"Type System for Four Delimited Control Operators","authors":"Chiaki Ishio, K. Asai","doi":"10.1145/3564719.3568691","DOIUrl":"https://doi.org/10.1145/3564719.3568691","url":null,"abstract":"The operational behavior of control operators has been studied comprehensively in the past few decades, but type systems of control operators have not. There are distinct type systems for shift, control, and shift0 without any relationship between them, and there has not been a type system that directly corresponds to control0. This paper remedies this situation by giving a uniform type system for all the four control operators. Following Danvy and Filinski’s approach, we derive a monomorphic type system from the CPS interpreter that defines the operational semantics of the four control operators. By implementing the typed CPS interpreter in Agda, we show that the CPS translation preserves types and that the calculus with all the four control operators is terminating. Furthermore, we show the relationship between our type system and the previous type systems for shift, control, and shift0.","PeriodicalId":423660,"journal":{"name":"Proceedings of the 21st ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122246945","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}
Pub Date : 2022-10-21DOI: 10.48550/arXiv.2210.12077
S. Fowler, Vashti Galpin, J. Cheney
Modern applications often manage time-varying data. Despite decades of research on temporal databases, which culminated in the addition of temporal data operations into the SQL:2011 standard, temporal data query and manipulation operations are unavailable in most mainstream database management systems, leaving developers with the unenviable task of implementing such functionality from scratch. In this paper, we extend language-integrated query to support writing temporal queries and updates in a uniform host language, with the language performing the required rewriting to emulate temporal capabilities automatically on any standard relational database. We introduce two core languages, λTLINQ and λVLINQ, for manipulating transaction time and valid time data respectively, and formalise existing implementation strategies by giving provably correct semantics-preserving translations into a non-temporal core language, λLINQ. We show how existing work on query normalisation supports a surprisingly simple implementation strategy for sequenced joins. We implement our approach in the Links programming language, and describe a non-trivial case study based on curating COVID-19 statistics.
{"title":"Language-Integrated Query for Temporal Data","authors":"S. Fowler, Vashti Galpin, J. Cheney","doi":"10.48550/arXiv.2210.12077","DOIUrl":"https://doi.org/10.48550/arXiv.2210.12077","url":null,"abstract":"Modern applications often manage time-varying data. Despite decades of research on temporal databases, which culminated in the addition of temporal data operations into the SQL:2011 standard, temporal data query and manipulation operations are unavailable in most mainstream database management systems, leaving developers with the unenviable task of implementing such functionality from scratch. In this paper, we extend language-integrated query to support writing temporal queries and updates in a uniform host language, with the language performing the required rewriting to emulate temporal capabilities automatically on any standard relational database. We introduce two core languages, λTLINQ and λVLINQ, for manipulating transaction time and valid time data respectively, and formalise existing implementation strategies by giving provably correct semantics-preserving translations into a non-temporal core language, λLINQ. We show how existing work on query normalisation supports a surprisingly simple implementation strategy for sequenced joins. We implement our approach in the Links programming language, and describe a non-trivial case study based on curating COVID-19 statistics.","PeriodicalId":423660,"journal":{"name":"Proceedings of the 21st ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences","volume":"5 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116823445","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}
Pub Date : 2022-10-10DOI: 10.48550/arXiv.2210.04826
G. Espada, L. Ingelse, Paulo Canelas, Pedro Barbosa, Alcides Fonseca
Genetic Programming (GP) is an heuristic method that can be applied to many Machine Learning, Optimization and Engineering problems. In particular, it has been widely used in Software Engineering for Test-case generation, Program Synthesis and Improvement of Software (GI). Grammar-Guided Genetic Programming (GGGP) approaches allow the user to refine the domain of valid program solutions. Backus Normal Form is the most popular interface for describing Context-Free Grammars (CFG) for GGGP. BNF and its derivatives have the disadvantage of interleaving the grammar language and the target language of the program. We propose to embed the grammar as an internal Domain-Specific Language in the host language of the framework. This approach has the same expressive power as BNF and EBNF while using the host language type-system to take advantage of all the existing tooling: linters, formatters, type-checkers, autocomplete, and legacy code support. These tools have a practical utility in designing software in general, and GP systems in particular. We also present Meta-Handlers, user-defined overrides of the tree-generation system. This technique extends our object-oriented encoding with more practicability and expressive power than existing CFG approaches, achieving the same expressive power of Attribute Grammars, but without the grammar vs target language duality. Furthermore, we evidence that this approach is feasible, showing an example Python implementation as proof. We also compare our approach against textual BNF-representations w.r.t. expressive power and ergonomics. These advantages do not come at the cost of performance, as shown by our empirical evaluation on 5 benchmarks of our example implementation against PonyGE2. We conclude that our approach has better ergonomics with the same expressive power and performance of textual BNF-based grammar encodings.
{"title":"Data Types as a More Ergonomic Frontend for Grammar-Guided Genetic Programming","authors":"G. Espada, L. Ingelse, Paulo Canelas, Pedro Barbosa, Alcides Fonseca","doi":"10.48550/arXiv.2210.04826","DOIUrl":"https://doi.org/10.48550/arXiv.2210.04826","url":null,"abstract":"Genetic Programming (GP) is an heuristic method that can be applied to many Machine Learning, Optimization and Engineering problems. In particular, it has been widely used in Software Engineering for Test-case generation, Program Synthesis and Improvement of Software (GI). Grammar-Guided Genetic Programming (GGGP) approaches allow the user to refine the domain of valid program solutions. Backus Normal Form is the most popular interface for describing Context-Free Grammars (CFG) for GGGP. BNF and its derivatives have the disadvantage of interleaving the grammar language and the target language of the program. We propose to embed the grammar as an internal Domain-Specific Language in the host language of the framework. This approach has the same expressive power as BNF and EBNF while using the host language type-system to take advantage of all the existing tooling: linters, formatters, type-checkers, autocomplete, and legacy code support. These tools have a practical utility in designing software in general, and GP systems in particular. We also present Meta-Handlers, user-defined overrides of the tree-generation system. This technique extends our object-oriented encoding with more practicability and expressive power than existing CFG approaches, achieving the same expressive power of Attribute Grammars, but without the grammar vs target language duality. Furthermore, we evidence that this approach is feasible, showing an example Python implementation as proof. We also compare our approach against textual BNF-representations w.r.t. expressive power and ergonomics. These advantages do not come at the cost of performance, as shown by our empirical evaluation on 5 benchmarks of our example implementation against PonyGE2. We conclude that our approach has better ergonomics with the same expressive power and performance of textual BNF-based grammar encodings.","PeriodicalId":423660,"journal":{"name":"Proceedings of the 21st ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130900028","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}
{"title":"Proceedings of the 21st ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences","authors":"","doi":"10.1145/3564719","DOIUrl":"https://doi.org/10.1145/3564719","url":null,"abstract":"","PeriodicalId":423660,"journal":{"name":"Proceedings of the 21st ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116661830","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}
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