@inproceedings{70b845f5a8ae47cd83a28d15e20407a1,
title = "Efficient runtime verification of first-order temporal properties",
abstract = "Runtime verification allows monitoring the execution of a system against a temporal property, raising an alarm if the property is violated. In this paper we present a theory and system for runtime verification of a first-order past time linear temporal logic. The first-order nature of the logic allows a monitor to reason about events with data elements. While runtime verification of propositional temporal logic requires only a fixed amount of memory, the first-order variant has to deal with a number of data values potentially growing unbounded in the length of the execution trace. This requires special compactness considerations in order to allow checking very long executions. In previous work we presented an efficient use of BDDs for such first-order runtime verification, implemented in the tool DejaVu. We first summarize this previous work. Subsequently, we look at the new problem of dynamically identifying when data observed in the past are no longer needed, allowing to reclaim the data elements used to represent them. We also study the problem of adding relations over data values. Finally, we present parts of the implementation, including a new concept of user defined property macros.",
author = "Klaus Havelund and Doron Peled",
note = "Publisher Copyright: {\textcopyright} 2018, Springer International Publishing AG, part of Springer Nature.; 25th International Symposium on Model Checking Software, SPIN 2018 ; Conference date: 20-06-2018 Through 22-06-2018",
year = "2018",
doi = "https://doi.org/10.1007/978-3-319-94111-0_2",
language = "الإنجليزيّة",
isbn = "9783319941103",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "26--47",
editor = "Gallardo, {Mar{\'i}a del} and Pedro Merino",
booktitle = "Model Checking Software - 25th International Symposium, SPIN 2018, Proceedings",
address = "ألمانيا",
}