2,587 research outputs found
Learning Linear Temporal Properties
We present two novel algorithms for learning formulas in Linear Temporal
Logic (LTL) from examples. The first learning algorithm reduces the learning
task to a series of satisfiability problems in propositional Boolean logic and
produces a smallest LTL formula (in terms of the number of subformulas) that is
consistent with the given data. Our second learning algorithm, on the other
hand, combines the SAT-based learning algorithm with classical algorithms for
learning decision trees. The result is a learning algorithm that scales to
real-world scenarios with hundreds of examples, but can no longer guarantee to
produce minimal consistent LTL formulas. We compare both learning algorithms
and demonstrate their performance on a wide range of synthetic benchmarks.
Additionally, we illustrate their usefulness on the task of understanding
executions of a leader election protocol
Low-Effort Specification Debugging and Analysis
Reactive synthesis deals with the automated construction of implementations
of reactive systems from their specifications. To make the approach feasible in
practice, systems engineers need effective and efficient means of debugging
these specifications.
In this paper, we provide techniques for report-based specification
debugging, wherein salient properties of a specification are analyzed, and the
result presented to the user in the form of a report. This provides a
low-effort way to debug specifications, complementing high-effort techniques
including the simulation of synthesized implementations.
We demonstrate the usefulness of our report-based specification debugging
toolkit by providing examples in the context of generalized reactivity(1)
synthesis.Comment: In Proceedings SYNT 2014, arXiv:1407.493
LTLf and LDLf Monitoring: A Technical Report
Runtime monitoring is one of the central tasks to provide operational
decision support to running business processes, and check on-the-fly whether
they comply with constraints and rules. We study runtime monitoring of
properties expressed in LTL on finite traces (LTLf) and in its extension LDLf.
LDLf is a powerful logic that captures all monadic second order logic on finite
traces, which is obtained by combining regular expressions and LTLf, adopting
the syntax of propositional dynamic logic (PDL). Interestingly, in spite of its
greater expressivity, LDLf has exactly the same computational complexity of
LTLf. We show that LDLf is able to capture, in the logic itself, not only the
constraints to be monitored, but also the de-facto standard RV-LTL monitors.
This makes it possible to declaratively capture monitoring metaconstraints, and
check them by relying on usual logical services instead of ad-hoc algorithms.
This, in turn, enables to flexibly monitor constraints depending on the
monitoring state of other constraints, e.g., "compensation" constraints that
are only checked when others are detected to be violated. In addition, we
devise a direct translation of LDLf formulas into nondeterministic automata,
avoiding to detour to Buechi automata or alternating automata, and we use it to
implement a monitoring plug-in for the PROM suite
Predictive Monitoring of Business Processes
Modern information systems that support complex business processes generally
maintain significant amounts of process execution data, particularly records of
events corresponding to the execution of activities (event logs). In this
paper, we present an approach to analyze such event logs in order to
predictively monitor business goals during business process execution. At any
point during an execution of a process, the user can define business goals in
the form of linear temporal logic rules. When an activity is being executed,
the framework identifies input data values that are more (or less) likely to
lead to the achievement of each business goal. Unlike reactive compliance
monitoring approaches that detect violations only after they have occurred, our
predictive monitoring approach provides early advice so that users can steer
ongoing process executions towards the achievement of business goals. In other
words, violations are predicted (and potentially prevented) rather than merely
detected. The approach has been implemented in the ProM process mining toolset
and validated on a real-life log pertaining to the treatment of cancer patients
in a large hospital
Structural Synthesis for GXW Specifications
We define the GXW fragment of linear temporal logic (LTL) as the basis for
synthesizing embedded control software for safety-critical applications. Since
GXW includes the use of a weak-until operator we are able to specify a number
of diverse programmable logic control (PLC) problems, which we have compiled
from industrial training sets. For GXW controller specifications, we develop a
novel approach for synthesizing a set of synchronously communicating
actor-based controllers. This synthesis algorithm proceeds by means of
recursing over the structure of GXW specifications, and generates a set of
dedicated and synchronously communicating sub-controllers according to the
formula structure. In a subsequent step, 2QBF constraint solving identifies and
tries to resolve potential conflicts between individual GXW specifications.
This structural approach to GXW synthesis supports traceability between
requirements and the generated control code as mandated by certification
regimes for safety-critical software. Synthesis for GXW specifications is in
PSPACE compared to 2EXPTIME-completeness of full-fledged LTL synthesis. Indeed
our experimental results suggest that GXW synthesis scales well to
industrial-sized control synthesis problems with 20 input and output ports and
beyond.Comment: The long (including appendix) version being reviewed by CAV'16
program committee. Compared to the submitted version, one author (out of her
wish) is moved to the Acknowledgement. (v2) Corrected typos. (v3) Add an
additional remark over environment assumption and easy corner case
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