A logical approach for behavioural composition of scenario-based models

As modern systems become more complex, design approaches model different aspects of the system separately. When considering (intra and inter) system interactions, it is usual to model individual scenarios using UML’s sequence diagrams. Given a set of scenarios we then need to check whether these are consistent and can be combined for a better understanding of the overall behaviour. This paper addresses this by presenting a novel formal technique for composing behavioural models at the metamodel level through exact metamodel restriction (EMR). In our approach a sequence diagram can be completely described by a set of logical constraints at the metamodel level. When composing sequence diagrams we take the union of the sets of logical constraints for each diagram and additional behavioural constraints that describe the matching composition glue. A formal semantics for composition in accordance with the glue guides our model transformation to Alloy. Alloy’s fully automated constraint solver gives us the solution. Our technique has been implemented as an Eclipse plugin SD2Alloy.Postprin

Regular symmetry patterns

Symmetry reduction is a well-known approach for alleviating the state explosion problem in model checking. Automatically identifying symmetries in concurrent systems, however, is computationally expensive. We propose a symbolic framework for capturing symmetry patterns in parameterised systems (i.e. an infinite family of finite-state systems): two regular word transducers to represent, respectively, parameterised systems and symmetry patterns. The framework subsumes various types of "symmetry relations" ranging from weaker notions (e.g. simulation preorders) to the strongest notion (i.e. isomorphisms). Our framework enjoys two algorithmic properties: (1) symmetry verification: given a transducer, we can automatically check whether it is a symmetry pattern of a given system, and (2) symmetry synthesis: we can automatically generate a symmetry pattern for a given system in the form of a transducer. Furthermore, our symbolic language allows additional constraints that the symmetry patterns need to satisfy to be easily incorporated in the verification/synthesis. We show how these properties can help identify symmetry patterns in examples like dining philosopher protocols, self-stabilising protocols, and prioritised resource-allocator protocol. In some cases (e.g. Gries's coffee can problem), our technique automatically synthesises a safety-preserving finite approximant, which can then be verified for safety solely using a finite-state model checker.UPMAR

On Tackling the Limits of Resolution in SAT Solving

The practical success of Boolean Satisfiability (SAT) solvers stems from the CDCL (Conflict-Driven Clause Learning) approach to SAT solving. However, from a propositional proof complexity perspective, CDCL is no more powerful than the resolution proof system, for which many hard examples exist. This paper proposes a new problem transformation, which enables reducing the decision problem for formulas in conjunctive normal form (CNF) to the problem of solving maximum satisfiability over Horn formulas. Given the new transformation, the paper proves a polynomial bound on the number of MaxSAT resolution steps for pigeonhole formulas. This result is in clear contrast with earlier results on the length of proofs of MaxSAT resolution for pigeonhole formulas. The paper also establishes the same polynomial bound in the case of modern core-guided MaxSAT solvers. Experimental results, obtained on CNF formulas known to be hard for CDCL SAT solvers, show that these can be efficiently solved with modern MaxSAT solvers

Improving patient experience and safety at transitions of care through the Your Care Needs You (YCNY) intervention: a study protocol for a cluster randomised controlled feasibility trial

Background Patients, particularly older people, often experience safety issues when transitioning from hospital to home. Although the evidence is currently equivocal as to how we can improve this transition of care, interventions that support patient involvement may be more effective. The ‘Your Care Needs You’ (YCNY) intervention supports patients to ‘know more’ and ‘do more’ whilst in hospital in order that they better understand their health condition and medications, maintain their daily activities, and can seek help at home if required. The intervention aims to reduce emergency hospital readmissions and improve safety and experience during the transition to home. Methods As part of the Partners At Care Transitions (PACT) programme of research, a multi-centred cluster randomised controlled trial (cRCT) will be conducted to explore the feasibility of the YCNY intervention and trial methodology. Data will be used to refine the intervention and develop a protocol for a definitive cRCT. Ten acute hospital wards (the clusters) from varying medical specialties including older peoples’ medicine, trauma and orthopaedics, cardiology, intermediate care, and stroke will be randomised to deliver YCNY or usual care on a 3:2 basis. Up to 200 patients aged 75 years and over and discharged to their own homes will be recruited to the study. Patients will complete follow-up questionnaires at 5-, 30-, and 90-days post-discharge and readmission data up to 90-days post-discharge will be extracted from their medical records. Study outcomes will include measures of feasibility (e.g. screening, recruitment, and retention data) and processes required to collect routine data at a patient and ward level. In addition, interviews and observations involving up to 24 patients/carers and 28 staff will be conducted to qualitatively assess the acceptability, usefulness, and feasibility of the intervention and implementation package to patients and staff. A separate sub-study will be conducted to explore how accurately primary outcome data (30-day emergency hospital readmissions) can be gathered for the definitive cRCT. Discussion This study will establish the feasibility of the YCNY intervention which aims to improve safety and experience during transitions of care. It will identify key methodological and implementation issues that need to be addressed prior to assessing the effectiveness of the YCNY intervention in a definitive cluster randomised controlled trial. Trial registration UK Clinical Research Network Portfolio: 42191; ISTCRN: ISRCTN51154948. Registered 16/07/2019

From Cleanroom to Desktop: Emerging Micro-Nanofabrication Technology for Biomedical Applications

This review is motivated by the growing demand for low-cost, easy-to-use, compact-size yet powerful micro-nanofabrication technology to address emerging challenges of fundamental biology and translational medicine in regular laboratory settings. Recent advancements in the field benefit considerably from rapidly expanding material selections, ranging from inorganics to organics and from nanoparticles to self-assembled molecules. Meanwhile a great number of novel methodologies, employing off-the-shelf consumer electronics, intriguing interfacial phenomena, bottom-up self-assembly principles, etc., have been implemented to transit micro-nanofabrication from a cleanroom environment to a desktop setup. Furthermore, the latest application of micro-nanofabrication to emerging biomedical research will be presented in detail, which includes point-of-care diagnostics, on-chip cell culture as well as bio-manipulation. While significant progresses have been made in the rapidly growing field, both apparent and unrevealed roadblocks will need to be addressed in the future. We conclude this review by offering our perspectives on the current technical challenges and future research opportunities

Abstract Cores in Implicit Hitting Set MaxSat Solving

Peer reviewe

Matching and merging scenarios automatically with Alloy

The design of large systems often involves the creation of models that describe partial specifications. Model composition is the process of combining partial models to create a single coherent model. This paper presents an automatic composition technique for creating a sequence diagram from partial specifications captured in multiple sequence diagrams with the help of Alloy. Our contribution is twofold: a novel true-concurrent semantics for sequence diagram composition, and a model-driven transformation of sequence diagrams to Alloy that preserves the semantics of composition defined. We have created a tool SD2Alloy that implements the technique as follows: two given sequence diagrams are transformed into two Alloy models, and merged according to a set of syntactic logical constraints describing how their elements should be matched. These constraints are in accordance to our compositional semantics. The technique can also be used to detect problems and inconsistencies in the composition of diagrams.Postprin