MODELFY: A Model-driven Solution for Decision Making based on Fuzzy Information

There exist areas, such as the disease prevention or inclement weather protocols, in which the analysis of the information based on strict protocols require a high level of rigor and security. In this situation, it would be desirable to apply formal methodologies that provide these features. In this scope, recently, it has been proposed a formalism, fuzzy automaton, that captures two relevant aspects for fuzzy information analysis: imprecision and uncertainty. However, the models should be designed by domain experts, who have the required knowledge for the design of the processes, but do not have the necessary technical knowledge. To address this limitation, this paper proposes MODELFY, a novel model-driven solution for designing a decision-making process based on fuzzy automata that allows users to abstract from technical complexities. With this goal in mind, we have developed a framework for fuzzy automaton model design based on a Domain- Specific Modeling Language (DSML) and a graphical editor. To improve the interoperability and functionality of this framework, it also includes a model-to-text transformation that translates the models designed by using the graphical editor into a format that can be used by a tool for data analysis. The practical value of this proposal is also evaluated through a non-trivial medical protocol for detecting potential heart problems. The results confirm that MODELFY is useful for defining such a protocol in a user-friendly and rigorous manner, bringing fuzzy automata closer to domain expert

Systematic engineering of mutation operators

In the context of software engineering, mutation consists in injecting small changes in artefacts – like models, programs, or data – for purposes like (mutation) testing, test data generation, and all sorts of search-based methods. These tasks typically require defining sets of mutation operators, which are often built ad-hoc because there is currently poor support for their development and testing. To improve this situation, we propose a methodology and corresponding tool support for the proper engineering of mutation operators. Our proposal is model-based, representing the artefacts to be mutated as models. It includes a domain-specific language to describe the mutation operators, facilities to synthesize models that can be used to test the operators, different metrics to analyse operator coverage, and services to generate operators when the coverage is insufficient. We show automated support atop the WODEL tool, and illustrate its use by defining mutation operators for UML Class Diagrams.This work has been partially funded by the Spanish Ministry of Science (RTI2018-095255-B-I00), by the R&D programme of the Madrid Region (S2018/TCS-4314) and by the Spanish MINECO-FEDER (grant number FAME RTI2018-093608-BC31

A tool for domain-independent model mutation

Mutation is a systematic technique to create variants of a seed artefact by means of mutation operators. It has many applications in computer science, like software testing, automatic exercise generation and design space exploration. Typically, mutation frameworks are developed ad-hoc by implementing mutation operators and their application strategies from scratch, using general-purpose programming languages. However, this is costly and error-prone. To improve this situation, we propose WODEL: a domain-specific language and tool for model-based mutation that is independent of the domain meta-model. WODELenables the rapid development and application of model mutations. It provides built-in advanced functionalities like automatic generation of seed models, and static and dynamic metrics of operator coverage and applicability. It offers extension points, e.g., to post-process mutants and describe domain-specific equivalence criteria. As an example, we illustrate the usage of WODEL for the mutation of security policies, and present an empirical evaluation of its expressiveness.Work partially funded by project FLEXOR (Spanish MINECO, TIN2014- 52129-R), project DArDOS (Spanish MINECO/FEDER TIN2015-65845-C3-1- R) and the R&D programme of the Madrid Region (S2013/ICE-3006

Using genetic algorithms to generate test sequences for complex timed systems

The generation of test data for state based specifications is a computationally expensive process. This problem is magnified if we consider that time con- straints have to be taken into account to govern the transitions of the studied system. The main goal of this paper is to introduce a complete methodology, sup- ported by tools, that addresses this issue by represent- ing the test data generation problem as an optimisa- tion problem. We use heuristics to generate test cases. In order to assess the suitability of our approach we consider two different case studies: a communication protocol and the scientific application BIPS3D. We give details concerning how the test case generation problem can be presented as a search problem and automated. Genetic algorithms (GAs) and random search are used to generate test data and evaluate the approach. GAs outperform random search and seem to scale well as the problem size increases. It is worth to mention that we use a very simple fitness function that can be eas- ily adapted to be used with other evolutionary search techniques

Testing timed systems modeled by stream X-machines

Stream X-machines have been used to specify real systems where complex data structures. They are a variety of extended finite state machine where a shared memory is used to represent communications between the components of systems. In this paper we introduce an extension of the Stream X-machines formalism in order to specify systems that present temporal requirements. We add time in two different ways. First, we consider that (output) actions take time to be performed. Second, our formalism allows to specify timeouts. Timeouts represent the time a system can wait for the environment to react without changing its internal state. Since timeous affect the set of available actions of the system, a relation focusing on the functional behavior of systems, that is, the actions that they can perform, must explicitly take into account the possible timeouts. In this paper we also propose a formal testing methodology allowing to systematically test a system with respect to a specification. Finally, we introduce a test derivation algorithm. Given a specification, the derived test suite is sound and complete, that is, a system under test successfully passes the test suite if and only if this system conforms to the specification

Timed Implementation Relations for the Distributed Test Architecture

In order to test systems that have physically distributed interfaces, called ports, we might use a distributed approach in which there is a separate tester at each port. If the testers do not synchronise during testing then we cannot always determine the relative order of events observed at different ports and this leads to new notions of correctness that have been described using corresponding implementation relations. We study the situation in which each tester has a local clock and timestamps its observations. If we know nothing about how the local clocks relate then this does not affect the implementation relation while if the local clocks agree exactly then we can reconstruct the sequence of observations made. In practice, however, we are likely to be between these extremes: the local clocks will not agree exactly but we have some information regarding how they can differ. We start by assuming that a local tester interacts synchronously with the corresponding port of the system under test and then extend this to the case where communications can be asynchronous, considering both the first-in-first-out (FIFO) case and the non-FIFO case. The new implementation relations are stronger than implementation relations for distributed testing that do not use timestamps but still reflect the distributed nature of observations. This paper explores these alternatives and derives corresponding implementation relations

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries