GPCE '25: "Imperative Program Synthesis ..."
Imperative Program Synthesis by Abstract Static Analysis and SMT Mutations
Aleksandar S. Dimovski
(Mother Teresa University, Skopje, North Macedonia)
This paper introduces a novel technique for synthesizing imperative programs that meet behavioral specifications given in the form of assumptions and assertions (logic formulas). In particular, we combine basic statement-directed enumerative search, static analysis via abstract interpretation, and expression-directed enumerative search via (incremental) SMT-based mutations to efficiently explore all candidate complete programs generated from an input program template (with statement and expression holes) until a solution is found. Firstly, the algorithm uses a basic enumerative search through the space of all possible statements, thus filling in all statement holes. In effect, we obtain partial programs with only missing (arithmetic and boolean) expressions, which are subsequently classified by a static analysis either as potential solutions or as definite failures. Finally, we repeatedly mutate the missing expressions in potential solutions and check if the resulting complete programs become bounded correct with respect to the given assertions.
We have implemented our technique in a prototype tool and evaluated it on a set of introductory C programs. The experimental results confirm the effectiveness of our technique for synthesizing various interesting C programs.
@InProceedings{GPCE25p27,
author = {Aleksandar S. Dimovski},
title = {Imperative Program Synthesis by Abstract Static Analysis and SMT Mutations},
booktitle = {Proc.\ GPCE},
publisher = {ACM},
pages = {27-40},
doi = {10.1145/3742876.3742884},
year = {2025},
}
Publisher's Version
Published Artifact
Artifacts Available
Artifacts Functional
Results Reproduced
Article: gpce25main-p23-p doi:10.1145/3742876.3742884
GPCE '25: "Retrofitting a Virtual Instrument ..."
Retrofitting a Virtual Instrument DSL with Programming Abstractions
Mathias Vatter and Sebastian Erdweg
(JGU Mainz, Germany)
KSP is an imperative DSL in music production that enables realistic modelling of musical instruments in real-time using Kontakt as a runtime environment. Once a niche topic for hobbyists, the field has since professionalized, with Kontakt becoming an industry standard. Its scripting language, however, has not evolved much, lacking modern functional and data abstractions while remaining closed-source. This paper proposes transformations that introduce modularity and basic abstraction principles to KSP. This entails functions with parameters and return values, recursive data types, and the implementation of lexical scope to replace the current global variable management. The transformations have been implemented in a preprocessing compiler framework--preceding the actual KSP interpreter--to an extend, that allows for the new syntax elements to be used in real-world KSP scripts.
@InProceedings{GPCE25p67,
author = {Mathias Vatter and Sebastian Erdweg},
title = {Retrofitting a Virtual Instrument DSL with Programming Abstractions},
booktitle = {Proc.\ GPCE},
publisher = {ACM},
pages = {67-79},
doi = {10.1145/3742876.3742878},
year = {2025},
}
Publisher's Version
Article: gpce25main-p3-p doi:10.1145/3742876.3742878
GPCE '25: "A Stable Model Semantics for ..."
A Stable Model Semantics for eFLINT Norm Specifications and Model Checking Scenarios
Christopher A. Esterhuyse, Tim Müller, and L. Thomas van Binsbergen
(University of Amsterdam, Netherlands)
Since its introduction at GPCE2020, the eFLINT norm specification language has been used in academic and industrial applications to specify and automate compliance for various norms, such as privacy regulations and data processing agreements. The eFLINT interpreter has been used to automate the analysis of real-time or historical cases by computing logical consequences and reporting normative violations.
To support future language and tooling developments, we contribute a formal definition of the language as a translation to first-order logic programming with stable model semantics. The described semantics aligns with the previous semi-formal descriptions of the language, but resolves issues relating to logical inference with negative antecedent and aggregation operators. Specifically, we formalise the connection between eFLINT's derivation rules and Horn clauses under the stable model semantics. Secondly, by repurposing the Clingo answer-set solver as a highly-optimised eFLINT interpreter, we extend the toolset for eFLINT with model-checking abstract properties in addition to case analysis.
We evaluate the new semantics and interpreter via an empirical comparison of the existing implementation to our prototype implementation. We observe that the expected subset of our tests have the equivalent behaviours.
@InProceedings{GPCE25p80,
author = {Christopher A. Esterhuyse and Tim Müller and L. Thomas van Binsbergen},
title = {A Stable Model Semantics for eFLINT Norm Specifications and Model Checking Scenarios},
booktitle = {Proc.\ GPCE},
publisher = {ACM},
pages = {80-93},
doi = {10.1145/3742876.3742882},
year = {2025},
}
Publisher's Version
Published Artifact
Artifacts Available
Artifacts Functional
Results Reproduced
Article: gpce25main-p16-p doi:10.1145/3742876.3742882
GPCE '25: "P4DDG: Data-Dependent Grammars ..."
P4DDG: Data-Dependent Grammars for Packet Specification and Parsing in P4
Tommaso Pacciani, Damian Frolich, L. Thomas van Binsbergen, and Chrysa Papagianni
(University of Amsterdam, Netherlands)
In software-defined networking, the domain-specific language P4 allows developers to program the behavior of networking devices at a comparatively high level of abstraction. A P4 program defines a state machine to parse incoming packets. The parsers are flexible and efficient but may be sensitive to bugs and difficult to maintain. As a possible alternative, data-dependent grammars (DDGs) can describe both packet structure and parser at a higher level of abstraction.
In this work, we investigate the use of DDGs in P4 programs. In particular, we demonstrate how DDGs can be used to simultaneously define packets and parsers. We describe a DDG to P4 compiler and evaluate our approach empirically. Input to our evaluation is a collection of P4 programs with for each: the original (handwritten) parser, the (handwritten) DDG alternative, and the compiler-generated parser. The handwritten and generated parsers are compared for equivalence and performance.
Our results show that the generated parsers are three times slower for grammars that do not utilize features distinguishing DDGs from context-free grammars. When parameterized nonterminals are used, a key feature of DDGs, the generated parsers are around six times slower.
@InProceedings{GPCE25p54,
author = {Tommaso Pacciani and Damian Frolich and L. Thomas van Binsbergen and Chrysa Papagianni},
title = {P4DDG: Data-Dependent Grammars for Packet Specification and Parsing in P4},
booktitle = {Proc.\ GPCE},
publisher = {ACM},
pages = {54-66},
doi = {10.1145/3742876.3742879},
year = {2025},
}
Publisher's Version
Article: gpce25main-p8-p doi:10.1145/3742876.3742879
GPCE '25: "Comparative Analysis of Pre-trained ..."
Comparative Analysis of Pre-trained Code Language Models for Automated Program Repair via Code Infill Generation
Iman Hemati Moghadam, Oebele Lijzenga, and Vadim Zaytsev
(Eindhoven University of Technology, Netherlands; University of Twente, Netherlands)
Automated Program Repair (APR) has advanced significantly with the emergence of pre-trained Code Language Models (CLMs), enabling the generation of high-quality patches. However, selecting the most suitable CLM for APR remains challenging due to a range of factors, including accuracy, efficiency, and scalability, among others. These factors are interdependent and interact in complex ways, making the selection of a CLM for APR a multifaceted problem.
This study systematically evaluates 20 pre-trained CLMs, ranging from 60M to 16B parameters, on the HumanEval-Java benchmark (163 buggy Java methods). The evaluation examines bug-fixing accuracy, resource consumption, compilability, patch diversity, and sampling strategies (beam search vs. nucleus sampling).
Results indicate that larger models such as CodeLLaMA-13B and StarCoder generally perform better in bug fixing and compiler error handling, but scale alone does not guarantee effectiveness, as some (e.g., CodeGen2) perform poorly despite their size. Notably, memory usage increases with model size, but time consumption does not exhibit a clear correlation, suggesting that efficiency is influenced by architecture rather than scale alone. Additionally, nucleus sampling slightly outperforms beam search, though the difference is not statistically significant. Since no single CLM fixes all bugs, these findings highlight the potential of hybrid or ensemble-based CLM-driven APR approaches for more robust bug-fixing.
@InProceedings{GPCE25p13,
author = {Iman Hemati Moghadam and Oebele Lijzenga and Vadim Zaytsev},
title = {Comparative Analysis of Pre-trained Code Language Models for Automated Program Repair via Code Infill Generation},
booktitle = {Proc.\ GPCE},
publisher = {ACM},
pages = {13-26},
doi = {10.1145/3742876.3742881},
year = {2025},
}
Publisher's Version
Info
Article: gpce25main-p15-p doi:10.1145/3742876.3742881
GPCE '25: "Integrating Static Optimization ..."
Integrating Static Optimization and Dynamic Nature in JavaScript
Tadashi Saito and Hideya Iwasaki
(University of Electro-Communications, Japan; Meiji University, Japan)
The class definitions and class field declarations in the ECMAScript standard suggest that the JavaScript engines could be optimized like class-based static languages. This paper focuses on two well-known optimizations. One is method specialization, using fixed offsets to access properties. The other is prior hidden class construction, which involves creating runtime class-like structures called hidden classes before creating instances of the classes. However, implementing such optimizations into JavaScript faces difficulties because of its dynamic features. We point out three difficulties that must be overcome and propose reasonable solutions. We implemented these optimizations and solutions in QuickJS, a small, practical JavaScript engine, and obtained promising results.
@InProceedings{GPCE25p41,
author = {Tadashi Saito and Hideya Iwasaki},
title = {Integrating Static Optimization and Dynamic Nature in JavaScript},
booktitle = {Proc.\ GPCE},
publisher = {ACM},
pages = {41-53},
doi = {10.1145/3742876.3742877},
year = {2025},
}
Publisher's Version
Article: gpce25main-p2-p doi:10.1145/3742876.3742877
GPCE '25: "Staged Gradual Typing ..."
Staged Gradual Typing
Hiroto Yaguchi and Yukiyoshi Kameyama
(University of Tsukuba, Japan)
Staging dynamically typed programming languages safely is a challenge, as the programming-language support for staged computation typically relies on static type systems. To solve this problem, we propose a staged gradual type system that seamlessly integrates static and dynamic typing with staged computation. Our system combines the basic gradual type system and the let-polymorphic staged type system for run-time code generation safely. We discuss the design and issues in developing the calculus, and present a type system and operational semantics via a translation to a cast calculus where dynamic type checking is made explicit. We also show several applications, such as lightweight stage polymorphism.
@InProceedings{GPCE25p94,
author = {Hiroto Yaguchi and Yukiyoshi Kameyama},
title = {Staged Gradual Typing},
booktitle = {Proc.\ GPCE},
publisher = {ACM},
pages = {94-104},
doi = {10.1145/3742876.3742880},
year = {2025},
}
Publisher's Version
Article: gpce25main-p10-p doi:10.1145/3742876.3742880
GPCE '25: "Comparative Analysis of Pre-trained ..."
Comparative Analysis of Pre-trained Code Language Models for Automated Program Repair via Code Infill Generation
Iman Hemati Moghadam, Oebele Lijzenga, and Vadim Zaytsev
(Eindhoven University of Technology, Netherlands; University of Twente, Netherlands)
Automated Program Repair (APR) has advanced significantly with the emergence of pre-trained Code Language Models (CLMs), enabling the generation of high-quality patches. However, selecting the most suitable CLM for APR remains challenging due to a range of factors, including accuracy, efficiency, and scalability, among others. These factors are interdependent and interact in complex ways, making the selection of a CLM for APR a multifaceted problem.
This study systematically evaluates 20 pre-trained CLMs, ranging from 60M to 16B parameters, on the HumanEval-Java benchmark (163 buggy Java methods). The evaluation examines bug-fixing accuracy, resource consumption, compilability, patch diversity, and sampling strategies (beam search vs. nucleus sampling).
Results indicate that larger models such as CodeLLaMA-13B and StarCoder generally perform better in bug fixing and compiler error handling, but scale alone does not guarantee effectiveness, as some (e.g., CodeGen2) perform poorly despite their size. Notably, memory usage increases with model size, but time consumption does not exhibit a clear correlation, suggesting that efficiency is influenced by architecture rather than scale alone. Additionally, nucleus sampling slightly outperforms beam search, though the difference is not statistically significant. Since no single CLM fixes all bugs, these findings highlight the potential of hybrid or ensemble-based CLM-driven APR approaches for more robust bug-fixing.
@InProceedings{GPCE25p13,
author = {Iman Hemati Moghadam and Oebele Lijzenga and Vadim Zaytsev},
title = {Comparative Analysis of Pre-trained Code Language Models for Automated Program Repair via Code Infill Generation},
booktitle = {Proc.\ GPCE},
publisher = {ACM},
pages = {13-26},
doi = {10.1145/3742876.3742881},
year = {2025},
}
Publisher's Version
Info
Article: gpce25main-p15-p doi:10.1145/3742876.3742881
GPCE '25: "A Stable Model Semantics for ..."
A Stable Model Semantics for eFLINT Norm Specifications and Model Checking Scenarios
Christopher A. Esterhuyse, Tim Müller, and L. Thomas van Binsbergen
(University of Amsterdam, Netherlands)
Since its introduction at GPCE2020, the eFLINT norm specification language has been used in academic and industrial applications to specify and automate compliance for various norms, such as privacy regulations and data processing agreements. The eFLINT interpreter has been used to automate the analysis of real-time or historical cases by computing logical consequences and reporting normative violations.
To support future language and tooling developments, we contribute a formal definition of the language as a translation to first-order logic programming with stable model semantics. The described semantics aligns with the previous semi-formal descriptions of the language, but resolves issues relating to logical inference with negative antecedent and aggregation operators. Specifically, we formalise the connection between eFLINT's derivation rules and Horn clauses under the stable model semantics. Secondly, by repurposing the Clingo answer-set solver as a highly-optimised eFLINT interpreter, we extend the toolset for eFLINT with model-checking abstract properties in addition to case analysis.
We evaluate the new semantics and interpreter via an empirical comparison of the existing implementation to our prototype implementation. We observe that the expected subset of our tests have the equivalent behaviours.
@InProceedings{GPCE25p80,
author = {Christopher A. Esterhuyse and Tim Müller and L. Thomas van Binsbergen},
title = {A Stable Model Semantics for eFLINT Norm Specifications and Model Checking Scenarios},
booktitle = {Proc.\ GPCE},
publisher = {ACM},
pages = {80-93},
doi = {10.1145/3742876.3742882},
year = {2025},
}
Publisher's Version
Published Artifact
Artifacts Available
Artifacts Functional
Results Reproduced
Article: gpce25main-p16-p doi:10.1145/3742876.3742882
GPCE '25: "CoCoCoLa: Code Completion ..."
CoCoCoLa: Code Completion Control Language
Nhat and Vadim Zaytsev
(University of Twente, Netherlands)
In software development, the efficiency and accuracy of code completion systems are crucial for productivity and codebase discovery. From simple spell checkers to advanced AI-powered tools, there are more ways to complete your code than ever. This results in an explosion in the number of possible valid proposals, especially when working with today’s increasingly large codebases. Over the years, a lot of effort has been put into developing effective ranking systems to prioritise proposals with more potential. Yet developers still often struggle with an overwhelming number of suggestions, leading to reduced productivity and increased cognitive load.
In this paper, instead of just performing completion by name, we propose CoCoCoLa — an alternative approach to give back the control over the presented proposals to the developer. By investigating the recorded code completion events, frequencies of desirable code elements’ properties were calculated to identify useful control factors. To avoid adding further complexity to the completion process, we propose a simple language, defined within the boundary of a valid identifier of the 50+ most popular software languages in 2024. This language allows developers to specify and filter for desired properties of the proposals.
@InProceedings{GPCE25p1,
author = { Nhat and Vadim Zaytsev},
title = {CoCoCoLa: Code Completion Control Language},
booktitle = {Proc.\ GPCE},
publisher = {ACM},
pages = {1-12},
doi = {10.1145/3742876.3742883},
year = {2025},
}
Publisher's Version
Published Artifact
Info
Artifacts Available
Article: gpce25main-p17-p doi:10.1145/3742876.3742883
GPCE '25: "P4DDG: Data-Dependent Grammars ..."
P4DDG: Data-Dependent Grammars for Packet Specification and Parsing in P4
Tommaso Pacciani, Damian Frolich, L. Thomas van Binsbergen, and Chrysa Papagianni
(University of Amsterdam, Netherlands)
In software-defined networking, the domain-specific language P4 allows developers to program the behavior of networking devices at a comparatively high level of abstraction. A P4 program defines a state machine to parse incoming packets. The parsers are flexible and efficient but may be sensitive to bugs and difficult to maintain. As a possible alternative, data-dependent grammars (DDGs) can describe both packet structure and parser at a higher level of abstraction.
In this work, we investigate the use of DDGs in P4 programs. In particular, we demonstrate how DDGs can be used to simultaneously define packets and parsers. We describe a DDG to P4 compiler and evaluate our approach empirically. Input to our evaluation is a collection of P4 programs with for each: the original (handwritten) parser, the (handwritten) DDG alternative, and the compiler-generated parser. The handwritten and generated parsers are compared for equivalence and performance.
Our results show that the generated parsers are three times slower for grammars that do not utilize features distinguishing DDGs from context-free grammars. When parameterized nonterminals are used, a key feature of DDGs, the generated parsers are around six times slower.
@InProceedings{GPCE25p54,
author = {Tommaso Pacciani and Damian Frolich and L. Thomas van Binsbergen and Chrysa Papagianni},
title = {P4DDG: Data-Dependent Grammars for Packet Specification and Parsing in P4},
booktitle = {Proc.\ GPCE},
publisher = {ACM},
pages = {54-66},
doi = {10.1145/3742876.3742879},
year = {2025},
}
Publisher's Version
Article: gpce25main-p8-p doi:10.1145/3742876.3742879
GPCE '25: "P4DDG: Data-Dependent Grammars ..."
P4DDG: Data-Dependent Grammars for Packet Specification and Parsing in P4
Tommaso Pacciani, Damian Frolich, L. Thomas van Binsbergen, and Chrysa Papagianni
(University of Amsterdam, Netherlands)
In software-defined networking, the domain-specific language P4 allows developers to program the behavior of networking devices at a comparatively high level of abstraction. A P4 program defines a state machine to parse incoming packets. The parsers are flexible and efficient but may be sensitive to bugs and difficult to maintain. As a possible alternative, data-dependent grammars (DDGs) can describe both packet structure and parser at a higher level of abstraction.
In this work, we investigate the use of DDGs in P4 programs. In particular, we demonstrate how DDGs can be used to simultaneously define packets and parsers. We describe a DDG to P4 compiler and evaluate our approach empirically. Input to our evaluation is a collection of P4 programs with for each: the original (handwritten) parser, the (handwritten) DDG alternative, and the compiler-generated parser. The handwritten and generated parsers are compared for equivalence and performance.
Our results show that the generated parsers are three times slower for grammars that do not utilize features distinguishing DDGs from context-free grammars. When parameterized nonterminals are used, a key feature of DDGs, the generated parsers are around six times slower.
@InProceedings{GPCE25p54,
author = {Tommaso Pacciani and Damian Frolich and L. Thomas van Binsbergen and Chrysa Papagianni},
title = {P4DDG: Data-Dependent Grammars for Packet Specification and Parsing in P4},
booktitle = {Proc.\ GPCE},
publisher = {ACM},
pages = {54-66},
doi = {10.1145/3742876.3742879},
year = {2025},
}
Publisher's Version
Article: gpce25main-p8-p doi:10.1145/3742876.3742879
GPCE '25: "Integrating Static Optimization ..."
Integrating Static Optimization and Dynamic Nature in JavaScript
Tadashi Saito and Hideya Iwasaki
(University of Electro-Communications, Japan; Meiji University, Japan)
The class definitions and class field declarations in the ECMAScript standard suggest that the JavaScript engines could be optimized like class-based static languages. This paper focuses on two well-known optimizations. One is method specialization, using fixed offsets to access properties. The other is prior hidden class construction, which involves creating runtime class-like structures called hidden classes before creating instances of the classes. However, implementing such optimizations into JavaScript faces difficulties because of its dynamic features. We point out three difficulties that must be overcome and propose reasonable solutions. We implemented these optimizations and solutions in QuickJS, a small, practical JavaScript engine, and obtained promising results.
@InProceedings{GPCE25p41,
author = {Tadashi Saito and Hideya Iwasaki},
title = {Integrating Static Optimization and Dynamic Nature in JavaScript},
booktitle = {Proc.\ GPCE},
publisher = {ACM},
pages = {41-53},
doi = {10.1145/3742876.3742877},
year = {2025},
}
Publisher's Version
Article: gpce25main-p2-p doi:10.1145/3742876.3742877
GPCE '25: "P4DDG: Data-Dependent Grammars ..."
P4DDG: Data-Dependent Grammars for Packet Specification and Parsing in P4
Tommaso Pacciani, Damian Frolich, L. Thomas van Binsbergen, and Chrysa Papagianni
(University of Amsterdam, Netherlands)
In software-defined networking, the domain-specific language P4 allows developers to program the behavior of networking devices at a comparatively high level of abstraction. A P4 program defines a state machine to parse incoming packets. The parsers are flexible and efficient but may be sensitive to bugs and difficult to maintain. As a possible alternative, data-dependent grammars (DDGs) can describe both packet structure and parser at a higher level of abstraction.
In this work, we investigate the use of DDGs in P4 programs. In particular, we demonstrate how DDGs can be used to simultaneously define packets and parsers. We describe a DDG to P4 compiler and evaluate our approach empirically. Input to our evaluation is a collection of P4 programs with for each: the original (handwritten) parser, the (handwritten) DDG alternative, and the compiler-generated parser. The handwritten and generated parsers are compared for equivalence and performance.
Our results show that the generated parsers are three times slower for grammars that do not utilize features distinguishing DDGs from context-free grammars. When parameterized nonterminals are used, a key feature of DDGs, the generated parsers are around six times slower.
@InProceedings{GPCE25p54,
author = {Tommaso Pacciani and Damian Frolich and L. Thomas van Binsbergen and Chrysa Papagianni},
title = {P4DDG: Data-Dependent Grammars for Packet Specification and Parsing in P4},
booktitle = {Proc.\ GPCE},
publisher = {ACM},
pages = {54-66},
doi = {10.1145/3742876.3742879},
year = {2025},
}
Publisher's Version
Article: gpce25main-p8-p doi:10.1145/3742876.3742879
GPCE '25: "A Stable Model Semantics for ..."
A Stable Model Semantics for eFLINT Norm Specifications and Model Checking Scenarios
Christopher A. Esterhuyse, Tim Müller, and L. Thomas van Binsbergen
(University of Amsterdam, Netherlands)
Since its introduction at GPCE2020, the eFLINT norm specification language has been used in academic and industrial applications to specify and automate compliance for various norms, such as privacy regulations and data processing agreements. The eFLINT interpreter has been used to automate the analysis of real-time or historical cases by computing logical consequences and reporting normative violations.
To support future language and tooling developments, we contribute a formal definition of the language as a translation to first-order logic programming with stable model semantics. The described semantics aligns with the previous semi-formal descriptions of the language, but resolves issues relating to logical inference with negative antecedent and aggregation operators. Specifically, we formalise the connection between eFLINT's derivation rules and Horn clauses under the stable model semantics. Secondly, by repurposing the Clingo answer-set solver as a highly-optimised eFLINT interpreter, we extend the toolset for eFLINT with model-checking abstract properties in addition to case analysis.
We evaluate the new semantics and interpreter via an empirical comparison of the existing implementation to our prototype implementation. We observe that the expected subset of our tests have the equivalent behaviours.
@InProceedings{GPCE25p80,
author = {Christopher A. Esterhuyse and Tim Müller and L. Thomas van Binsbergen},
title = {A Stable Model Semantics for eFLINT Norm Specifications and Model Checking Scenarios},
booktitle = {Proc.\ GPCE},
publisher = {ACM},
pages = {80-93},
doi = {10.1145/3742876.3742882},
year = {2025},
}
Publisher's Version
Published Artifact
Artifacts Available
Artifacts Functional
Results Reproduced
Article: gpce25main-p16-p doi:10.1145/3742876.3742882
GPCE '25: "Retrofitting a Virtual Instrument ..."
Retrofitting a Virtual Instrument DSL with Programming Abstractions
Mathias Vatter and Sebastian Erdweg
(JGU Mainz, Germany)
KSP is an imperative DSL in music production that enables realistic modelling of musical instruments in real-time using Kontakt as a runtime environment. Once a niche topic for hobbyists, the field has since professionalized, with Kontakt becoming an industry standard. Its scripting language, however, has not evolved much, lacking modern functional and data abstractions while remaining closed-source. This paper proposes transformations that introduce modularity and basic abstraction principles to KSP. This entails functions with parameters and return values, recursive data types, and the implementation of lexical scope to replace the current global variable management. The transformations have been implemented in a preprocessing compiler framework--preceding the actual KSP interpreter--to an extend, that allows for the new syntax elements to be used in real-world KSP scripts.
@InProceedings{GPCE25p67,
author = {Mathias Vatter and Sebastian Erdweg},
title = {Retrofitting a Virtual Instrument DSL with Programming Abstractions},
booktitle = {Proc.\ GPCE},
publisher = {ACM},
pages = {67-79},
doi = {10.1145/3742876.3742878},
year = {2025},
}
Publisher's Version
Article: gpce25main-p3-p doi:10.1145/3742876.3742878
GPCE '25: "Staged Gradual Typing ..."
Staged Gradual Typing
Hiroto Yaguchi and Yukiyoshi Kameyama
(University of Tsukuba, Japan)
Staging dynamically typed programming languages safely is a challenge, as the programming-language support for staged computation typically relies on static type systems. To solve this problem, we propose a staged gradual type system that seamlessly integrates static and dynamic typing with staged computation. Our system combines the basic gradual type system and the let-polymorphic staged type system for run-time code generation safely. We discuss the design and issues in developing the calculus, and present a type system and operational semantics via a translation to a cast calculus where dynamic type checking is made explicit. We also show several applications, such as lightweight stage polymorphism.
@InProceedings{GPCE25p94,
author = {Hiroto Yaguchi and Yukiyoshi Kameyama},
title = {Staged Gradual Typing},
booktitle = {Proc.\ GPCE},
publisher = {ACM},
pages = {94-104},
doi = {10.1145/3742876.3742880},
year = {2025},
}
Publisher's Version
Article: gpce25main-p10-p doi:10.1145/3742876.3742880
GPCE '25: "Comparative Analysis of Pre-trained ..."
Comparative Analysis of Pre-trained Code Language Models for Automated Program Repair via Code Infill Generation
Iman Hemati Moghadam, Oebele Lijzenga, and Vadim Zaytsev
(Eindhoven University of Technology, Netherlands; University of Twente, Netherlands)
Automated Program Repair (APR) has advanced significantly with the emergence of pre-trained Code Language Models (CLMs), enabling the generation of high-quality patches. However, selecting the most suitable CLM for APR remains challenging due to a range of factors, including accuracy, efficiency, and scalability, among others. These factors are interdependent and interact in complex ways, making the selection of a CLM for APR a multifaceted problem.
This study systematically evaluates 20 pre-trained CLMs, ranging from 60M to 16B parameters, on the HumanEval-Java benchmark (163 buggy Java methods). The evaluation examines bug-fixing accuracy, resource consumption, compilability, patch diversity, and sampling strategies (beam search vs. nucleus sampling).
Results indicate that larger models such as CodeLLaMA-13B and StarCoder generally perform better in bug fixing and compiler error handling, but scale alone does not guarantee effectiveness, as some (e.g., CodeGen2) perform poorly despite their size. Notably, memory usage increases with model size, but time consumption does not exhibit a clear correlation, suggesting that efficiency is influenced by architecture rather than scale alone. Additionally, nucleus sampling slightly outperforms beam search, though the difference is not statistically significant. Since no single CLM fixes all bugs, these findings highlight the potential of hybrid or ensemble-based CLM-driven APR approaches for more robust bug-fixing.
@InProceedings{GPCE25p13,
author = {Iman Hemati Moghadam and Oebele Lijzenga and Vadim Zaytsev},
title = {Comparative Analysis of Pre-trained Code Language Models for Automated Program Repair via Code Infill Generation},
booktitle = {Proc.\ GPCE},
publisher = {ACM},
pages = {13-26},
doi = {10.1145/3742876.3742881},
year = {2025},
}
Publisher's Version
Info
Article: gpce25main-p15-p doi:10.1145/3742876.3742881
GPCE '25: "CoCoCoLa: Code Completion ..."
CoCoCoLa: Code Completion Control Language
Nhat and Vadim Zaytsev
(University of Twente, Netherlands)
In software development, the efficiency and accuracy of code completion systems are crucial for productivity and codebase discovery. From simple spell checkers to advanced AI-powered tools, there are more ways to complete your code than ever. This results in an explosion in the number of possible valid proposals, especially when working with today’s increasingly large codebases. Over the years, a lot of effort has been put into developing effective ranking systems to prioritise proposals with more potential. Yet developers still often struggle with an overwhelming number of suggestions, leading to reduced productivity and increased cognitive load.
In this paper, instead of just performing completion by name, we propose CoCoCoLa — an alternative approach to give back the control over the presented proposals to the developer. By investigating the recorded code completion events, frequencies of desirable code elements’ properties were calculated to identify useful control factors. To avoid adding further complexity to the completion process, we propose a simple language, defined within the boundary of a valid identifier of the 50+ most popular software languages in 2024. This language allows developers to specify and filter for desired properties of the proposals.
@InProceedings{GPCE25p1,
author = { Nhat and Vadim Zaytsev},
title = {CoCoCoLa: Code Completion Control Language},
booktitle = {Proc.\ GPCE},
publisher = {ACM},
pages = {1-12},
doi = {10.1145/3742876.3742883},
year = {2025},
}
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Article: gpce25main-p17-p doi:10.1145/3742876.3742883