42,069 research outputs found
Semantics of trace relations in requirements models for consistency checking and inferencing
Requirements traceability is the ability to relate requirements back to stakeholders and forward to corresponding design artifacts, code, and test cases. Although considerable research has been devoted to relating requirements in both forward and backward directions, less attention has been paid to relating requirements with other requirements. Relations between requirements influence a number of activities during software development such as consistency checking and change management. In most approaches and tools, there is a lack of precise definition of requirements relations. In this respect, deficient results may be produced. In this paper, we aim at formal definitions of the relation types in order to enable reasoning about requirements relations. We give a requirements metamodel with commonly used relation types. The semantics of the relations is provided with a formalization in first-order logic. We use the formalization for consistency checking of relations and for inferring new relations. A tool has been built to support both reasoning activities. We illustrate our approach in an example which shows that the formal semantics of relation types enables new relations to be inferred and contradicting relations in requirements documents to be determined. The application of requirements reasoning based on formal semantics resolves many of the deficiencies observed in other approaches. Our tool supports better understanding of dependencies between requirements
Dynamic Interference Mitigation for Generalized Partially Connected Quasi-static MIMO Interference Channel
Recent works on MIMO interference channels have shown that interference
alignment can significantly increase the achievable degrees of freedom (DoF) of
the network. However, most of these works have assumed a fully connected
interference graph. In this paper, we investigate how the partial connectivity
can be exploited to enhance system performance in MIMO interference networks.
We propose a novel interference mitigation scheme which introduces constraints
for the signal subspaces of the precoders and decorrelators to mitigate "many"
interference nulling constraints at a cost of "little" freedoms in precoder and
decorrelator design so as to extend the feasibility region of the interference
alignment scheme. Our analysis shows that the proposed algorithm can
significantly increase system DoF in symmetric partially connected MIMO
interference networks. We also compare the performance of the proposed scheme
with various baselines and show via simulations that the proposed algorithms
could achieve significant gain in the system performance of randomly connected
interference networks.Comment: 30 pages, 10 figures, accepted by IEEE Transaction on Signal
Processin
Incompleteness of States w.r.t. Traces in Model Checking
Cousot and Cousot introduced and studied a general past/future-time
specification language, called mu*-calculus, featuring a natural time-symmetric
trace-based semantics. The standard state-based semantics of the mu*-calculus
is an abstract interpretation of its trace-based semantics, which turns out to
be incomplete (i.e., trace-incomplete), even for finite systems. As a
consequence, standard state-based model checking of the mu*-calculus is
incomplete w.r.t. trace-based model checking. This paper shows that any
refinement or abstraction of the domain of sets of states induces a
corresponding semantics which is still trace-incomplete for any propositional
fragment of the mu*-calculus. This derives from a number of results, one for
each incomplete logical/temporal connective of the mu*-calculus, that
characterize the structure of models, i.e. transition systems, whose
corresponding state-based semantics of the mu*-calculus is trace-complete
Effective Marking Equivalence Checking in Systems with Dynamic Process Creation
The starting point of this work is a framework allowing to model systems with
dynamic process creation, equipped with a procedure to detect symmetric
executions (ie., which differ only by the identities of processes). This allows
to reduce the state space, potentially to an exponentially smaller size, and,
because process identifiers are never reused, this also allows to reduce to
finite size some infinite state spaces. However, in this approach, the
procedure to detect symmetries does not allow for computationally efficient
algorithms, mainly because each newly computed state has to be compared with
every already reached state.
In this paper, we propose a new approach to detect symmetries in this
framework that will solve this problem, thus enabling for efficient algorithms.
We formalise a canonical representation of states and identify a sufficient
condition on the analysed model that guarantees that every symmetry can be
detected. For the models that do not fall into this category, our approach is
still correct but does not guarantee a maximal reduction of state space.Comment: In Proceedings Infinity 2012, arXiv:1302.310
Learning and Designing Stochastic Processes from Logical Constraints
Stochastic processes offer a flexible mathematical formalism to model and
reason about systems. Most analysis tools, however, start from the premises
that models are fully specified, so that any parameters controlling the
system's dynamics must be known exactly. As this is seldom the case, many
methods have been devised over the last decade to infer (learn) such parameters
from observations of the state of the system. In this paper, we depart from
this approach by assuming that our observations are {\it qualitative}
properties encoded as satisfaction of linear temporal logic formulae, as
opposed to quantitative observations of the state of the system. An important
feature of this approach is that it unifies naturally the system identification
and the system design problems, where the properties, instead of observations,
represent requirements to be satisfied. We develop a principled statistical
estimation procedure based on maximising the likelihood of the system's
parameters, using recent ideas from statistical machine learning. We
demonstrate the efficacy and broad applicability of our method on a range of
simple but non-trivial examples, including rumour spreading in social networks
and hybrid models of gene regulation
Symmetry Reduction Enables Model Checking of More Complex Emergent Behaviours of Swarm Navigation Algorithms
The emergent global behaviours of robotic swarms are important to achieve
their navigation task goals. These emergent behaviours can be verified to
assess their correctness, through techniques like model checking. Model
checking exhaustively explores all possible behaviours, based on a discrete
model of the system, such as a swarm in a grid. A common problem in model
checking is the state-space explosion that arises when the states of the model
are numerous. We propose a novel implementation of symmetry reduction, in the
form of encoding navigation algorithms relatively with respect to a reference,
based on the symmetrical properties of swarms in grids. We applied the relative
encoding to a swarm navigation algorithm, Alpha, modelled for the NuSMV model
checker. A comparison of the state-space and verification results with an
absolute (or global) and a relative encoding of the Alpha algorithm highlights
the advantages of our approach, allowing model checking larger grid sizes and
number of robots, and consequently, verifying more complex emergent behaviours.
For example, a property was verified for a grid with 3 robots and a maximum
allowed size of 8x8 cells in a global encoding, whereas this size was increased
to 16x16 using a relative encoding. Also, the time to verify a property for a
swarm of 3 robots in a 6x6 grid was reduced from almost 10 hours to only 7
minutes. Our approach is transferable to other swarm navigation algorithms.Comment: Accepted for presentation in Towards Autonomous Robotic Systems
(TAROS) 2015, Liverpool, U
Conditional Transition Systems with Upgrades
We introduce a variant of transition systems, where activation of transitions
depends on conditions of the environment and upgrades during runtime
potentially create additional transitions. Using a cornerstone result in
lattice theory, we show that such transition systems can be modelled in two
ways: as conditional transition systems (CTS) with a partial order on
conditions, or as lattice transition systems (LaTS), where transitions are
labelled with the elements from a distributive lattice. We define equivalent
notions of bisimilarity for both variants and characterise them via a
bisimulation game.
We explain how conditional transition systems are related to featured
transition systems for the modelling of software product lines. Furthermore, we
show how to compute bisimilarity symbolically via BDDs by defining an operation
on BDDs that approximates an element of a Boolean algebra into a lattice. We
have implemented our procedure and provide runtime results
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