Lune

OOPSLA2025Top-tier venue

Faster Explicit-Trace Monitoring-Oriented Programming for Runtime Verification of Software Tests

Kevin Guan, Marcelo d'Amorim, Owolabi Legunsen

2025Year
7Citations
3Top-tier citations

Abstract

Runtime verification (RV) monitors program executions for conformance with formal specifications (specs). This paper concerns Monitoring-Oriented Programming (MOP), the only RV approach shown to scale to thousands of open-source GitHub projects when simultaneously monitoring passing unit tests against dozens of specs. Explicitly storing traces-sequences of spec-related program events-can make it easier to debug spec violations or to monitor tests against hyperproperties, which requires reasoning about sets of traces. But, most online MOP algorithms are implicit trace, i.e. they work event by event to avoid the time and space costs of storing traces. Yet, TraceMOP, the only explicit-trace online MOP algorithm, is often too slow and often fails.

We propose LazyMOP, a faster explicit-trace online MOP algorithm for RV of tests that is enabled by three simple optimizations. First, whereas all existing online MOP algorithms eagerly monitor all events as they occur, LazyMOP lazily stores only unique traces at runtime and monitors them just before the test run ends. Lazy monitoring is inspired by a recent finding: 99.87% of traces during RV of tests are duplicates. Second, to speed up trace storage, LazyMOP encodes events and their locations as integers, and amortizes the cost of looking up locations across events. Lastly, LazyMOP only synchronizes accesses to its trace store after detecting multi-threading, unlike TraceMOP's eager and wasteful synchronization of all accesses.

On 179 Java open-source projects, LazyMOP is up to 4.9x faster and uses 4.8x less memory than TraceMOP, finding the same traces (modulo test non-determinism) and violations. We show LazyMOP's usefulness in the context of software evolution, where tests are re-run after each code change. LazyMOP ๐‘’ optimizes LazyMOP in this context by generating fewer duplicate traces. Using unique traces from one code version, LazyMOP ๐‘’ finds all pairs of method ๐‘š and spec ๐‘ , where all traces for ๐‘  in ๐‘š are identical. Then, in a future version, LazyMOP ๐‘’ generates and monitors only one trace of ๐‘  in ๐‘š. LazyMOP ๐‘’ is up to 3.9x faster than LazyMOP and it speeds up two recent techniques that speed up RV during evolution by up to 4.6x with no loss in violations.

CCS Concepts: โ€ข Software and its engineering โ†’ Software testing and debugging.

Ask about this paper

Your agent reads all of it.

Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.

Questions to start from

Your agent calls

Luneget_paper_fulltext

Ask in Lune

Free to start. No credit card required.

lune papers fulltext 99906ebe-4a24-4740-b65c-a1b818f8ad6f

Cited by top-tier papers3

Ask how each one uses it

Builds on5

Related papers

Dusk over the sea between two cliffs drawn in fine vertical lines