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Conference

International Symposium on Temporal Representation and Reasoning 

About: International Symposium on Temporal Representation and Reasoning is an academic conference. The conference publishes majorly in the area(s): Temporal logic & Temporal database. Over the lifetime, 547 publications have been published by the conference receiving 8307 citations.


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Book ChapterDOI
08 Jul 2003
TL;DR: Counterexample-guided abstraction refinement is an automatic abstraction method where the key step is to extract information from false negatives ("spurious counterexamples") due to over-approximation.
Abstract: The main practical problem in model checking is the combinatorial explosion of system states commonly known as the state explosion problem. Abstraction methods attempt to reduce the size of the state space by employing knowledge about the system and the specification in order to model only relevant features in the Kripke structure. Counterexample-guided abstraction refinement is an automatic abstraction method where, starting with a relatively small skeletal representation of the system to be verified, increasingly precise abstract representations of the system are computed. The key step is to extract information from false negatives ("spurious counterexamples") due to over-approximation.

1,520 citations

Proceedings ArticleDOI
16 Jun 2008
TL;DR: This work surveys temporal description logics that are based on standard temporal logics such as LTL and CTL and focuses on the computational complexity of the satisfiability problem and algorithms for deciding it.
Abstract: We survey temporal description logics that are based on standard temporal logics such as LTL and CTL. In particular, we concentrate on the computational complexity of the satisfiability problem and algorithms for deciding it.

236 citations

Proceedings ArticleDOI
23 Jun 2005
TL;DR: A specification language and algorithms for the online and offline monitoring of synchronous systems including circuits and embedded systems, and a class of specifications, characterized syntactically, for which the algorithm's memory requirement is independent of the length of the input streams.
Abstract: We present a specification language and algorithms for the online and offline monitoring of synchronous systems including circuits and embedded systems. Such monitoring is useful not only for testing, but also under actual deployment. The specification language is simple and expressive; it can describe both correctness/failure assertions along with interesting statistical measures that are useful for system profiling and coverage analysis. The algorithm for online monitoring of queries in this language follows a partial evaluation strategy: it incrementally constructs output streams from input streams, while maintaining a store of partially evaluated expressions for forward references. We identify a class of specifications, characterized syntactically, for which the algorithm's memory requirement is independent of the length of the input streams. Being able to bound memory requirements is especially important in online monitoring of large input streams. We extend the concepts used in the online algorithm to construct an efficient offline monitoring algorithm for large traces. We have implemented our algorithm and applied it to two industrial systems, the PCI bus protocol and a memory controller. The results demonstrate that our algorithms are practical and that our specification language is sufficiently expressive to handle specifications of interest to industry.

233 citations

Proceedings ArticleDOI
28 Jun 2007
TL;DR: This paper introduces a framework consisting of a set of distance operators based on primitive as well as derived parameters of trajectories (speed and direction) to support trajectory clustering and classification mining tasks, which definitely imply a way to quantify the distance between two trajectories.
Abstract: Trajectory database (TD) management is a relatively new topic of database research, which has emerged due to the explosion of mobile devices and positioning technologies. Trajectory similarity search forms an important class of queries in TD with applications in trajectory data analysis and spatiotemporal knowledge discovery. In contrast to related works which make use of generic similarity metrics that virtually ignore the temporal dimension, in this paper we introduce a framework consisting of a set of distance operators based on primitive (space and time) as well as derived parameters of trajectories (speed and direction). The novelty of the approach is not only to provide qualitatively different means to query for similar trajectories, but also to support trajectory clustering and classification mining tasks, which definitely imply a way to quantify the distance between two trajectories. For each of the proposed distance operators we devise highly parametric algorithms, the efficiency of which is evaluated through an extensive experimental study using synthetic and real trajectory datasets.

149 citations

Proceedings ArticleDOI
14 Jun 2001
TL;DR: The paper extends the well-known a priori algorithm, and also develops two optimization techniques to take advantage of the special properties of the calendar-based patterns.
Abstract: A temporal association rule is an association rule that holds during specific time intervals. An example is that eggs and coffee are frequently sold together in morning hours. The paper studies temporal association rules during the time intervals specified by user-given calendar schemas. Generally, the use of calendar schemas makes the discovered temporal association rules easier to understand. An example of calendar schema is (year, month, day), which yields a set of calendar-based patterns of the form (d/sub 3/, d/sub 2/, d/sub 1/), where each d/sub i/ is either an integer or the symbol *. For example, (2000, *, 16) is such a pattern, which corresponds to the time intervals, each consisting of the 16th day of a month in year 2000. This paper defines two types of temporal association rules: precise-match association rules require that the association rule holds during every interval, and fuzzy-match ones require that the association rule holds during most of these intervals. The paper extends the well-known a priori algorithm, and also develops two optimization techniques to take advantage of the special properties of the calendar-based patterns. The experiments show that the algorithms and optimization techniques are effective.

137 citations

Performance
Metrics
No. of papers from the Conference in previous years
YearPapers
20212
202012
201913
201815
201714
201623