ISSTA 2023 Workshops
32nd ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA 2023)
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18th ACM International Workshop on Implementation, Compilation, Optimization of OO Languages, Programs and Systems (ICOOOLPS 2023), July 17, 2023, Seattle, WA, USA

ICOOOLPS 2023 – Proceedings

Contents - Abstracts - Authors

18th ACM International Workshop on Implementation, Compilation, Optimization of OO Languages, Programs and Systems (ICOOOLPS 2023)

Frontmatter

Title Page


Welcome from the Chairs
Welcome to the 2023 edition of International Workshop on Implementation, Compilation, Optimization of Object-Oriented Languages, Programs and Systems (ICOOOLPS 2023), held on July 17th at the University of Washington, Seattle, WA, co-located with ECOOP and ISSTA 2023.
ICOOOLPS brings together researchers and practitioners working in the field of programming language implementation and optimization. Although its origins are attached to object-oriented approaches, it has since broadened its scope and now encompasses all programming language paradigms.

Info
ICOOOLPS 2023 Organization
Committee listings

Invited Talks

Deegen: A Meta-compiler Approach for High Performance VMs at Low Engineering Cost (Invited Talk)
Haoran Xu ORCID logo
(Stanford University, USA)
Building a high-performance VM for a dynamic language has traditionally required a huge amount of time, money, and expertise. To reduce the high engineering cost, we present Deegen, a meta-compiler that generates a high-performance VM automatically from a semantical description of the bytecodes. Currently, Deegen is capable of automatically generating an optimized interpreter and baseline JIT compiler. This allows the user get a high-performance VM for their own language at an engineering cost similar to writing an interpreter. To demonstrate Deegen's capability in the real world, we implemented LuaJIT Remake (LJR), a standard-compliant VM for Lua 5.1. Across a variety of benchmarks, we demonstrated that LJR's interpreter significantly outperforms LuaJIT's interpreter, and LJR's baseline JIT generates high-quality code with a negligible compilation cost.

Publisher's Version
A Retrospective on Julia (Invited Talk)
Benjamin Chung ORCID logo
(University of Washington, USA; Northeastern University, USA)
The Julia programming language was designed around a lofty objective: to let scientists and researchers write both dynamic scripts and fast libraries in the same language while also facilitating decoupling and abstraction. Moreover, Julia wanted to do this with a scrappy academic development team of three people and in the span of about two years. I'll talk about the decisions that Julia made early on to meet this goal, reflect on how those decisions have aged as the language (and ecosystem around it) matured, and about some key lessons that other languages might be able to learn from Julia's experience.

Publisher's Version

Papers

Lazy Code Transformations in a Formally Verified Compiler
Léo Gourdin ORCID logo
(Université Grenoble Alpes, France; CNRS, France; Grenoble INP, France; VERIMAG, France)
Translation validation verifies the results of an untrusted translator—called an oracle—at the compiler’s runtime using a validator. This approach enables validating intricate optimizations without having to prove them directly. Parametrizing such a validator with hints provided by oracles greatly simplifies its integration within a formally verified compiler—such as CompCert. However, generating those hints requires adapting state-of-the-art optimizations.
The co-design of a validation framework supporting a class of optimizations led us to improve the Lazy Code Motion (LCM) and Lazy Strength Reduction (LSR) data-flow algorithms of Knoop, Rüthing, and Steffen. We propose an efficient implementation in OCaml combining both LCM and LSR, operating over basic-blocks, and whose result is checked by a Coq-verified validator. We show how to generate invariant annotations from the data-flow equations as hints for the defensive validation, and we introduce several algorithmic refinements w.r.t. the original papers.
Our solution is fully integrated within CompCert, and to the best of our knowledge, it is the first formally verified strength-reduction of loop-induction variables.

Publisher's Version Info
Towards Reliable Memory Management for Python Native Extensions
Joannah Nanjekye ORCID logo, David Bremner ORCID logo, and Aleksandar Micic ORCID logo
(University of New Brunswick, Canada; IBM, Canada)
Many programming languages provide a C interface as a foreign function interface (FFI) for C developers to access the language, the Python language being one of these languages. Over the years, the Python C API has grown to be a challenge for the evolution of the Python ecosystem. In this paper, we implement a new Python FFI, we call CyStck, by combining a stack and light-weight handles, to support efficient garbage collection (GC) in Python native extensions. CyStck introduces execution time overhead while copying the fewest bytes for all benchmarks across the CPython boundary compared to the CPython API and HPy respectively. We also implemented a tool to automate the migration of extensions from the CPython C API to CyStck using advanced pattern matching and static analysis, with a success rate as high as 90% in some workloads.

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