15,359 research outputs found
On-Line Monitoring for Temporal Logic Robustness
In this paper, we provide a Dynamic Programming algorithm for on-line
monitoring of the state robustness of Metric Temporal Logic specifications with
past time operators. We compute the robustness of MTL with unbounded past and
bounded future temporal operators MTL over sampled traces of Cyber-Physical
Systems. We implemented our tool in Matlab as a Simulink block that can be used
in any Simulink model. We experimentally demonstrate that the overhead of the
MTL robustness monitoring is acceptable for certain classes of practical
specifications
Temporal Data Modeling and Reasoning for Information Systems
Temporal knowledge representation and reasoning is a major research field in Artificial
Intelligence, in Database Systems, and in Web and Semantic Web research. The ability to
model and process time and calendar data is essential for many applications like appointment
scheduling, planning, Web services, temporal and active database systems, adaptive
Web applications, and mobile computing applications. This article aims at three complementary
goals. First, to provide with a general background in temporal data modeling
and reasoning approaches. Second, to serve as an orientation guide for further specific
reading. Third, to point to new application fields and research perspectives on temporal
knowledge representation and reasoning in the Web and Semantic Web
Monitoring-Oriented Programming: A Tool-Supported Methodology for Higher Quality Object-Oriented Software
This paper presents a tool-supported methodological paradigm for object-oriented software development, called monitoring-oriented programming and abbreviated MOP, in which runtime monitoring is a basic software design principle. The general idea underlying MOP is that software developers insert specifications in their code via annotations. Actual monitoring code is automatically synthesized from these annotations before compilation and integrated at appropriate places in the program, according to user-defined configuration attributes. This way, the specification is checked at runtime against the implementation. Moreover, violations and/or validations of specifications can trigger user-defined code at any points in the program, in particular recovery code, outputting or sending messages, or raising exceptions.
The MOP paradigm does not promote or enforce any specific formalism to specify requirements: it allows the users to plug-in their favorite or domain-specific specification formalisms via logic plug-in modules. There are two major technical challenges that MOP supporting tools unavoidably face: monitor synthesis and monitor integration. The former is heavily dependent on the specification formalism and comes as part of the corresponding logic plug-in, while the latter is uniform for all specification formalisms and depends only on the target programming language. An experimental prototype tool, called Java-MOP, is also discussed, which currently supports most but not all of the desired MOP features. MOP aims at reducing the gap between formal specification and implementation, by integrating the two and allowing them together to form a system
Interpretable Categorization of Heterogeneous Time Series Data
Understanding heterogeneous multivariate time series data is important in
many applications ranging from smart homes to aviation. Learning models of
heterogeneous multivariate time series that are also human-interpretable is
challenging and not adequately addressed by the existing literature. We propose
grammar-based decision trees (GBDTs) and an algorithm for learning them. GBDTs
extend decision trees with a grammar framework. Logical expressions derived
from a context-free grammar are used for branching in place of simple
thresholds on attributes. The added expressivity enables support for a wide
range of data types while retaining the interpretability of decision trees. In
particular, when a grammar based on temporal logic is used, we show that GBDTs
can be used for the interpretable classi cation of high-dimensional and
heterogeneous time series data. Furthermore, we show how GBDTs can also be used
for categorization, which is a combination of clustering and generating
interpretable explanations for each cluster. We apply GBDTs to analyze the
classic Australian Sign Language dataset as well as data on near mid-air
collisions (NMACs). The NMAC data comes from aircraft simulations used in the
development of the next-generation Airborne Collision Avoidance System (ACAS
X).Comment: 9 pages, 5 figures, 2 tables, SIAM International Conference on Data
Mining (SDM) 201
On the Complexity of Temporal-Logic Path Checking
Given a formula in a temporal logic such as LTL or MTL, a fundamental problem
is the complexity of evaluating the formula on a given finite word. For LTL,
the complexity of this task was recently shown to be in NC. In this paper, we
present an NC algorithm for MTL, a quantitative (or metric) extension of LTL,
and give an NCC algorithm for UTL, the unary fragment of LTL. At the time of
writing, MTL is the most expressive logic with an NC path-checking algorithm,
and UTL is the most expressive fragment of LTL with a more efficient
path-checking algorithm than for full LTL (subject to standard
complexity-theoretic assumptions). We then establish a connection between LTL
path checking and planar circuits, which we exploit to show that any further
progress in determining the precise complexity of LTL path checking would
immediately entail more efficient evaluation algorithms than are known for a
certain class of planar circuits. The connection further implies that the
complexity of LTL path checking depends on the Boolean connectives allowed:
adding Boolean exclusive or yields a temporal logic with P-complete
path-checking problem
Real-time and Probabilistic Temporal Logics: An Overview
Over the last two decades, there has been an extensive study on logical
formalisms for specifying and verifying real-time systems. Temporal logics have
been an important research subject within this direction. Although numerous
logics have been introduced for the formal specification of real-time and
complex systems, an up to date comprehensive analysis of these logics does not
exist in the literature. In this paper we analyse real-time and probabilistic
temporal logics which have been widely used in this field. We extrapolate the
notions of decidability, axiomatizability, expressiveness, model checking, etc.
for each logic analysed. We also provide a comparison of features of the
temporal logics discussed
Timed Automata Approach for Motion Planning Using Metric Interval Temporal Logic
In this paper, we consider the robot motion (or task) planning problem under
some given time bounded high level specifications. We use metric interval
temporal logic (MITL), a member of the temporal logic family, to represent the
task specification and then we provide a constructive way to generate a timed
automaton and methods to look for accepting runs on the automaton to find a
feasible motion (or path) sequence for the robot to complete the task.Comment: Full Version for ECC 201
Trace checking of Metric Temporal Logic with Aggregating Modalities using MapReduce
Modern complex software systems produce a large amount of execution data,
often stored in logs. These logs can be analyzed using trace checking
techniques to check whether the system complies with its requirements
specifications. Often these specifications express quantitative properties of
the system, which include timing constraints as well as higher-level
constraints on the occurrences of significant events, expressed using aggregate
operators. In this paper we present an algorithm that exploits the MapReduce
programming model to check specifications expressed in a metric temporal logic
with aggregating modalities, over large execution traces. The algorithm
exploits the structure of the formula to parallelize the evaluation, with a
significant gain in time. We report on the assessment of the implementation -
based on the Hadoop framework - of the proposed algorithm and comment on its
scalability.Comment: 16 pages, 6 figures, Extended version of the SEFM 2014 pape
Requirement verification in simulation-based automation testing
The emergence of the Industrial Internet results in an increasing number of
complicated temporal interdependencies between automation systems and the
processes to be controlled. There is a need for verification methods that scale
better than formal verification methods and which are more exact than testing.
Simulation-based runtime verification is proposed as such a method, and an
application of Metric temporal logic is presented as a contribution. The
practical scalability of the proposed approach is validated against a
production process designed by an industrial partner, resulting in the
discovery of requirement violations.Comment: 4 pages, 2 figures. Added IEEE copyright notic
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