Skip to content

Trace-Based Execution-Level Observability of VDM-SL Specifications

Aug 2026 · 0 citations · 13 references
Computer Science

TL;DR

The recording and utilization of execution traces of assignments, operation calls, and return statements are proposed to make the internal behavior of operations persistent and analyzable as state-based models.

Abstract

VDM has been pursuing rigorous verification through mathematical theorem proving and software testing via simulated execution. Animation through an interpreter enables validation of the specification to ensure it meets the required functionality. Step-by-step execution in a debugger also allows the user to follow the internal behavior of operations. In this paper, we propose the recording and utilization of execution traces of assignments, operation calls, and return statements to make the internal behavior of operations persistent and analyzable as state-based models. The data model of events in execution traces, its implementation in ViennaTalk, and its application to visualization will be introduced.

View source

Similar papers

Book Open access Aug 2026

VeriLucid: A Verification-aware Data-plane Programming Language

This paper introduces the first verification-aware data-plane language: VeriLucid, which aims to unify programming and specification in one high-level language, with built-in proof automation.

John Sonchack, P. Zave, Jennifer Rexford · 0 citations
Book Open access Jul 2026

Engineering Verified Model Transformations through a Proof-Based Language Workbench

BCerT is developed, an extension of the Meeduse language workbench originally dedicated to the formal modeling of domain-specific languages, allowing animation and model checking with ProB, as well as theorem proving with Atelier B.

Akram Idani, Germán Vega · 0 citations
Preprint Aug 2026

Can Formal Specifications Be Synthesized from Tests Alone?

This approach uses LLMs to infer candidate specifications solely from test code and dynamic execution traces: the LLM observes only the program interface, selected inputs, and corresponding outputs or state changes, while the implementation internals remain hidden.

Tianhai Liu, Maximilian Müller, Tobias Hey et al. · 0 citations
Book Open access Jul 2026

Towards Extensible, Auditable, and Modular Measurement Specification and Execution in Computer Networking

We present the Measurement Template Library (Mtl), a Go library and runtime for specifying and executing measurements. Mtl provides a framework for specifying and executing extensible, modular, and auditable measurements using generic programming techniques. By leveraging the notion of polymorphic measurement programs, we show how to lift measurement tools/probes into a typed computational context and model. This lifting supports the structured definition and refinement of common data structures, algorithms, and concurrency and interleaving semantics which appear in measurement work. In short, we show that measurement points (i.e., the Linux ping utility, scamper, or RIPE Atlas) are types, and measurements are type expressions.

I. Ndubuisi-Obi, Siya Kulkarni · 0 citations
Preprint Aug 2026

Forbench: Symbolic Simulation Helps Make Your Testbench More Formal

Forbench is introduced, a word-level symbolic simulation framework that retains the familiar execution semantics of simulation but augments it with solver-backed symbolic signals and state transitions, enabling systematic exploration of RTL behaviors under symbolic inputs and conditions.

Ziyi Yang, Wenbin Che, Ziyue Zheng et al. · 0 citations
2026

Remote Concolic Multiverse Debugging (Artifact)

A novel multiverse debugger capable of effectively pruning redundant paths from the state space to reduce the effect of state explosion is presented, which uses a trace-based approach which significantly reduces the overhead of multiverse de-bugging.

Maarten Steevens, Tom Lauwaerts, Christophe Scholliers · 0 citations

Related blog posts

MIT News · Artificial Intelligence Aug 17, 2026

Q&A: Rethinking how innovation happens

In his latest book, Professor Eugene Fitzgerald examines the forces that turn breakthroughs into value — and why innovation resists simple formulas.