Daniel Thoma

This paper proposes a unified framework that combines compositional assume-guarantee (A-G) reasoning with runtime monitoring and model-based diagnosis tailored to stream-based architectures. We extend classical A-G contracts to capture temporal relationships between assumptions and guarantees and reinterpret system composition in terms of event-driven data streams. Building on Reiter’s theory of diagnosis, we adapt the notion of minimal diagnoses to continuous observation traces, enabling the identification of root causes of contract violations in interconnected systems. Our approach is realized within an extension of the Lola stream-processing framework, supporting not only runtime monitoring but also formal system modeling and automated diagnosis. Furthermore, we demonstrate the applicability of our methodology in the domain of Digital Twin-enabled Systems (DTES) by extending the TwinLang modeling language with executable contracts.

Runtime verification deals with checking correctness properties on the runs of a system under scrutiny. To achieve this, it addresses a variety of sub-problems related to monitoring of systems: These range from the appropriate design of a specification language over efficient monitor generation as hardware and software monitors to solutions for instrumenting the monitored system, preferably in a non-intrusive way. Further aspects play a role for the usability of a runtime verification toolchain, e.g. availability, sufficient documentation and the existence of a developer community. In this paper we present the TeSSLa ecosystem, a runtime verification framework built around the stream runtime verification language TeSSLa: It provides a rich toolchain of mostly freely available compilers for monitor generation on different hardware and software backends, as well as instrumentation mechanisms for various runtime verification requirements. Additionally, we highlight how the online resources and supporting tools of the community-driven project enable the productive usage of stream runtime verification.

Runtime Verification (RV) studies how to analyze execution traces of a system under observation. Stream Runtime Verification (SRV) applies stream transformations to obtain information from observed traces. Incomplete traces with information missing in gaps pose a common challenge when applying RV and SRV techniques to real-world systems as RV approaches typically require the complete trace without missing parts. This paper presents a solution to perform SRV on incomplete traces based on abstraction. We use TeSSLa as specification language for non-synchronized timed event streams and define abstract event streams representing the set of all possible traces that could have occurred during gaps in the input trace. We show how to translate a TeSSLa specification to its abstract counterpart that can propagate gaps through the transformation of the input streams and thus generate sound outputs even if the input streams contain gaps and events with imprecise values. The solution has been implemented as a set of macros for the original TeSSLa and an empirical evaluation shows the feasibility of the approach.

We study temporal logics and automata on multi-attributed data words. Recently, BD-LTL was introduced as a temporal logic on data words extending LTL by navigation along positions of single data values. As allowing for navigation wrt. tuples of data values renders the logic undecidable, we introduce ND-LTL, an extension of BD-LTL by a restricted form of tuple-navigation. While complete ND-LTL is still undecidable, the two natural fragments allowing for either future or past navigation along data values are shown to be Ackermann-hard, yet decidability is obtained by reduction to nested multi-counter systems. To this end, we introduce and study nested variants of data automata as an intermediate model simplifying the constructions. To complement these results we show that imposing the same restrictions on BD-LTL yields two 2ExpSpace-complete fragments while satisfiability for the full logic is known to be as hard as reachability in Petri nets.