Caruca: Effective and Efficient Specification Mining for Opaque Software Components
October 16, 2025 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Evangelos Lamprou, Seong-Heon Jung, Mayank Keoliya, Lukas Lazarek, Konstantinos Kallas, Michael Greenberg, Nikos Vasilakis
arXiv ID
2510.14279
Category
cs.SE: Software Engineering
Cross-listed
cs.PL
Citations
0
Venue
arXiv.org
Last Checked
5 months ago
Abstract
A wealth of state-of-the-art systems demonstrate impressive improvements in performance, security, and reliability on programs composed of opaque components, such as Unix shell commands. To reason about commands, these systems require partial specifications. However, creating such specifications is a manual, laborious, and error-prone process, limiting the practicality of these systems. This paper presents Caruca, a system for automatic specification mining for opaque commands. To overcome the challenge of language diversity across commands, Caruca first instruments a large language model to translate a command's user-facing documentation into a structured invocation syntax. Using this representation, Caruca explores the space of syntactically valid command invocations and execution environments. Caruca concretely executes each command-environment pair, interposing at the system-call and filesystem level to extract key command properties such as parallelizability and filesystem pre- and post-conditions. These properties can be exported in multiple specification formats and are immediately usable by existing systems. Applying Caruca across 60 GNU Coreutils, POSIX, and third-party commands across several specification-dependent systems shows that Caruca generates correct specifications for all but one case, completely eliminating manual effort from the process and currently powering the full specifications for a state-of-the-art static analysis tool.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Software Engineering
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Microservices: yesterday, today, and tomorrow
π
π
The Cartographer
A Survey of Machine Learning for Big Code and Naturalness
R.I.P.
π»
Ghosted
An Overview on Smart Contracts: Challenges, Advances and Platforms
R.I.P.
π»
Ghosted
Slither: A Static Analysis Framework For Smart Contracts
R.I.P.
π»
Ghosted
ContractFuzzer: Fuzzing Smart Contracts for Vulnerability Detection
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted