A Model-Derivation Framework for Software Analysis

Model-based verification allows to express behavioral correctness conditions like the validity of execution states, boundaries of variables or timing at a high level of abstraction and affirm that they are satisfied by a software system. However, this requires expressive models which are difficult and cumbersome to create and maintain by hand. This paper presents a framework that automatically derives behavioral models from real-sized Java programs. Our framework builds on the EMF/ECore technology and provides a tool that creates an initial model from Java bytecode, as well as a series of transformations that simplify the model and eventually output a timed-automata model that can be processed by a model checker such as UPPAAL. The framework has the following properties: (1) consistency of models with software, (2) extensibility of the model derivation process, (3) scalability and (4) expressiveness of models. We report several case studies to validate how our framework satisfies these properties.Comment: In Proceedings MARS 2017, arXiv:1703.0581

A Model-Derivation Framework for Software Analysis

Model-based verification allows to express behavioral correctness conditions like the validity of execution states, boundaries of variables or timing at a high level of abstraction and affirm that they are satisfied by a software system. However, this requires expressive models which are difficult and cumbersome to create and maintain by hand. This paper presents a framework that automatically derives behavioral models from real-sized Java programs. Our framework builds on the EMF/ECore technology and provides a tool that creates an initial model from Java bytecode, as well as a series of transformations that simplify the model and eventually output a timed-automata model that can be processed by a model checker such as UPPAAL. The framework has the following properties: (1) consistency of models with software, (2) extensibility of the model derivation process, (3) scalability and (4) expressiveness of models. We report several case studies to validate how our framework satisfies these properties.Comment: In Proceedings MARS 2017, arXiv:1703.0581

A timed-automata approach for critical path detection in a soft real-time application

In this paper, we report preliminary ideas from our project called “Time Performance Improvement With Parallel Processing Systems” (TIPS). In the TIPS project, we plan to take advantage of multi-core platforms for performance improvement by parallelizing a complex soft real-time application. In order to increase the timing performance, one needs to adapt the optimizations on the critical execution paths of an application which are both significantly time consuming and important from user requirements' perspective. In this work, we present an approach how to detect critical paths in a target application

A model-derivation framework for timing analysis of Java software Systems

One of the main challenges in developing a software system is to assure that its properties fulfill the specifications. In the context of this paper, we are especially interested in timing properties. Model-based software verification is one of the approaches to achieve this. However, model-based verification requires expressive models of software systems and deriving such models is not a trivial task. Although there are a few model derivation tool proposals for the purpose of model-checking timing properties, these are dedicated tools supporting a selected set of verification techniques and as such they are not explicitly designed for coping with new demands. This paper presents a framework that derives models from Java programs in an automated way for analyzing timing properties. The framework has the following properties that are not provided by the previous proposals: (1) Efficiency in model development, (2) consistency of models with software, (3) expressiveness of models, (4) scalability and (5) extensibility of the model derivation process

Elective cancer surgery in COVID-19-free surgical pathways during the SARS-CoV-2 pandemic: An international, multicenter, comparative cohort study

PURPOSE As cancer surgery restarts after the first COVID-19 wave, health care providers urgently require data to determine where elective surgery is best performed. This study aimed to determine whether COVID-19–free surgical pathways were associated with lower postoperative pulmonary complication rates compared with hospitals with no defined pathway. PATIENTS AND METHODS This international, multicenter cohort study included patients who underwent elective surgery for 10 solid cancer types without preoperative suspicion of SARS-CoV-2. Participating hospitals included patients from local emergence of SARS-CoV-2 until April 19, 2020. At the time of surgery, hospitals were defined as having a COVID-19–free surgical pathway (complete segregation of the operating theater, critical care, and inpatient ward areas) or no defined pathway (incomplete or no segregation, areas shared with patients with COVID-19). The primary outcome was 30-day postoperative pulmonary complications (pneumonia, acute respiratory distress syndrome, unexpected ventilation). RESULTS Of 9,171 patients from 447 hospitals in 55 countries, 2,481 were operated on in COVID-19–free surgical pathways. Patients who underwent surgery within COVID-19–free surgical pathways were younger with fewer comorbidities than those in hospitals with no defined pathway but with similar proportions of major surgery. After adjustment, pulmonary complication rates were lower with COVID-19–free surgical pathways (2.2% v 4.9%; adjusted odds ratio [aOR], 0.62; 95% CI, 0.44 to 0.86). This was consistent in sensitivity analyses for low-risk patients (American Society of Anesthesiologists grade 1/2), propensity score–matched models, and patients with negative SARS-CoV-2 preoperative tests. The postoperative SARS-CoV-2 infection rate was also lower in COVID-19–free surgical pathways (2.1% v 3.6%; aOR, 0.53; 95% CI, 0.36 to 0.76). CONCLUSION Within available resources, dedicated COVID-19–free surgical pathways should be established to provide safe elective cancer surgery during current and before future SARS-CoV-2 outbreaks

Elective Cancer Surgery in COVID-19-Free Surgical Pathways During the SARS-CoV-2 Pandemic: An International, Multicenter, Comparative Cohort Study.

PURPOSE: As cancer surgery restarts after the first COVID-19 wave, health care providers urgently require data to determine where elective surgery is best performed. This study aimed to determine whether COVID-19-free surgical pathways were associated with lower postoperative pulmonary complication rates compared with hospitals with no defined pathway. PATIENTS AND METHODS: This international, multicenter cohort study included patients who underwent elective surgery for 10 solid cancer types without preoperative suspicion of SARS-CoV-2. Participating hospitals included patients from local emergence of SARS-CoV-2 until April 19, 2020. At the time of surgery, hospitals were defined as having a COVID-19-free surgical pathway (complete segregation of the operating theater, critical care, and inpatient ward areas) or no defined pathway (incomplete or no segregation, areas shared with patients with COVID-19). The primary outcome was 30-day postoperative pulmonary complications (pneumonia, acute respiratory distress syndrome, unexpected ventilation). RESULTS: Of 9,171 patients from 447 hospitals in 55 countries, 2,481 were operated on in COVID-19-free surgical pathways. Patients who underwent surgery within COVID-19-free surgical pathways were younger with fewer comorbidities than those in hospitals with no defined pathway but with similar proportions of major surgery. After adjustment, pulmonary complication rates were lower with COVID-19-free surgical pathways (2.2% v 4.9%; adjusted odds ratio [aOR], 0.62; 95% CI, 0.44 to 0.86). This was consistent in sensitivity analyses for low-risk patients (American Society of Anesthesiologists grade 1/2), propensity score-matched models, and patients with negative SARS-CoV-2 preoperative tests. The postoperative SARS-CoV-2 infection rate was also lower in COVID-19-free surgical pathways (2.1% v 3.6%; aOR, 0.53; 95% CI, 0.36 to 0.76). CONCLUSION: Within available resources, dedicated COVID-19-free surgical pathways should be established to provide safe elective cancer surgery during current and before future SARS-CoV-2 outbreaks

Numerical Simulation of a Two-Crack Rotor System Supported by Radial Active Magnetic Bearings

In this work a computational simulation is utilized to investigate the steady-state response of a two-crack rotor system supported by radial active magnetic bearings on an excitation by centrifugal forces of discs unbalances. The static deflection of a shaft is considered larger than vibration amplitude of a shaft and therefore a so-called breathing behaviour of cracks is introduced. Parametric study has been carried out in order to investigate influence of different values of the angle between cracks on the steady-state response of a rotor system. The results presented in this work can therefore help with detection of cracks in the shaft

A tool framework for deriving the application architecture for global software development projects

In order to meet the communication, coordination and control requirements of distributed Global Software Development (GSD) teams, it is necessary to define a proper software architecture. Designing a GSD architecture, however, involves a multitude of design decisions that are related in different ways. As such, it is not trivial for the architect to design a system that meets the different GSD concerns. To assist the architect in designing a suitable GSD architecture we propose the tool framework Global Architect. The tool framework is based on a common meta-model for GSD and a question framework, which includes a predefined set of questions that are related to abstract design rules for designing GSD systems. Based on the answers provided to the questions of the question framework, the tool automatically selects and instantiates the necessary rules and generates the GSD architecture. Global Architect has been applied to design the GSD architecture for a real industrial project of Cybersoft, a leading GSD company in Turkey

A Model-Driven Framework for Hardware-Software Co-design of Dataflow Applications

Hardware-software (HW-SW) co-design allows to meet system-level objectives by exploiting the synergy of hardware and software. Current tools and approaches for HW-SW co-design face difficulties coping with the increasing complexity of modern-day application due to, e.g., concurrency and energy constraints. Therefore, an automated modeling approach is needed which satisfies modularity, extensibility and interoperability requirements. Model-Driven Engineering (MDE) is a prominent paradigm that, by treating models as first-class citizens, helps to fulfill these requirements. This paper presents a state-of-the-art MDE-based framework for HW-SW co-design of dataflow applications, based on synchronous dataflow (SDF) graph formalism. In the framework, we introduce a reusable set of three coherent metamodels for creating HW-SW co-design models concerning SDF graphs, hardware platforms and allocation of SDF tasks to hardware. The framework also contains model transformations that cast these models into priced timed-automata models, the input language of the well-known model checker Uppaal Cora. We demonstrate how our framework satisfies the requirements of modularity, extensibility and interoperability in an industrial case study