Search arXivSearch

arXiv · 0705.1452

Typer la dé-sérialisation sans sérialiser les types

Abstract

In this paper, we propose a way of assigning static type information to unmarshalling functions and we describe a verification technique for unmarshalled data that preserves the execution safety provided by static type checking. This technique, whose correctness is proven, relies on singleton types whose values are transmitted to unmarshalling routines at runtime, and on an efficient checking algorithm able to deal with sharing and cycles.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Grégoire Henry, Michel Mauny, Emmanuel Chailloux. 2007-05-10. Typer la dé-sérialisation sans sérialiser les types. https://arxiv.org/abs/0705.1452

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

On the computational complexity of JavaScript regex matching

Despite widespread use, the complexity of the matching problem for modern regular expressions languages remains unclear. Previous work proved that an idealized regular expression language with backreferences and lookarounds had PSPACE-complete matching. We extend this work to a real-world regex language by proving that JavaScript regex matching with expanded lower-bounded quantifiers is PSPACE-complete. We then generalize the result: we show that PSPACE-hardness survives the removal of negative lookarounds, and that removing all lookarounds leads to an OptP-complete parsing problem. Our core arguments are formalized in Rocq.

cs.PL

Opportunistic ZGC: Leveraging Idle Cores for More Effective Concurrent Garbage Collection

Managed language runtimes often provide concurrent garbage collectors so that latency-critical applications with large working sets can keep running while most collection work proceeds in the background. ZGC is a production-quality, generational, concurrent collector in OpenJDK with sub-millisecond pause times. While ZGC is designed to run concurrently, frequent and excessive collections with ZGC can still slow the mutators due to synchronization costs and interference with shared computing resources. Hence, the ZGC scheduler is conservative by default, and in most cases, will grow the heap toward the maximum allowed before scheduling a collection. While this approach minimizes collection effort, it can be wasteful, or even harmful, if the maximum heap size is not well tuned to the actual working set. We propose Opportunistic ZGC (OppZGC), a feedback-directed ZGC scheduling policy that constrains the heap dynamically and automatically, without per-application tuning. OppZGC identifies periods when CPU cores are underutilized and leverages them for concurrent collection with ZGC. We describe the design and implementation of OppZGC in OpenJDK's HotSpot Java VM and evaluate it with standard and latency-sensitive benchmarks from DaCapo Chopin and SPECjbb. OppZGC limits heap usage when there is CPU capacity sufficient for additional collections, and avoids scheduling extra collections when they would substantially degrade performance. Overall, it reduces maximum heap usage for our DaCapo benchmarks by between 61% and 90%, on average, depending on configuration, with minimal impact on throughput and request latency compared to default ZGC.

cs.PL

From Rocq to Metal: A Pipeline for Formally Verified Microcontroller Firmware

Enforcing invariants in safety-critical firmware is increasingly urgent as generated code becomes widespread, but standard extraction targets for proof assistants require runtimes too large for many embedded devices. We present a pipeline for running formally verified Rocq firmware logic on Cortex-M microcontrollers. The pipeline extracts Gallina to Scheme, compiles it with Encore!, a bare-metal Continuation Passing Style (CPS) bytecode virtual machine, and embeds the result in no_std Rust firmware. We structure applications as pure state-transition functions, so the business logic is proved in Rocq while the event/effect boundary, host callbacks, compiler, and VM remain explicit trusted components. On ST33-class targets with a 50 KB RAM lower bound, Encore! executes Rocq-extracted code end-to-end, stays within the target memory budget on our benchmarks, and validates a transaction-signing application on physical Ledger Flex hardware.

cs.PL