Meta-Model for global software development to support portability and interoperability

Global Software Development (GSD) considers the coordinated activity of software development that is not localized and central but geographically distributed. To support coordination among sites, usually it is aimed to adopt the same development and execution platform. Unfortunately, adopting a single platform might not be always possible due to technical or organizational constraints of the different sites in GSD projects. As such, very often GSD projects have to cope with portability and interoperability problems. To address these problems we propose to apply model-driven architecture design (MDA) approach. For this we present a common metamodel of GSD that we have derived from a systematic domain analysis process. The meta-model enhances the understanding of GSD, is used to define platform independent models of GSD architecture, and transform platform independent models to platform specific models

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

An MDE Approach for Modular Program Analyses

Program analyses are an important tool to check if a system fulfills its specification. A typical implementation strategy for program analyses is to use an imperative, general-purpose language like Java, and access the program to be analyzed through libraries that offer an API for reading, writing and manipulating intermediate code, such as BCEL or ASM for Java bytecode. We claim that this hampers reuse and interoperability. In this paper, we propose an Ecore-metamodel for covering Java bytecode completely, which can act as a common basis for program analyses. Code analyses as well as instrumentations can then be defined as model transformations in a declarative language. As a consequence, the implementation of program analysis becomes more concise, more readable and more modular. We demonstrate the effectiveness of this approach by two case studies: profiling of timing performance and model checking of reachability requirements. We also provide tools to generate instances of our bytecode metamodel from Java code in the class file format and vice versa

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 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

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

Can We Improve Confusion, Uremia, Respiratory Rate, Blood Pressure, Age >65 with Lactate and Procalcitonin to Predict Mortality in Pneumonia?

Introduction: Pneumonia is a common diagnosis in the emergency department (ED). Some scoring systems such as Confusion, Uremia, Respiratory Rate, Blood Pressure, Age>65 (CURB-65) are used to determine the severity of this disease. We aimed to determine the best scoring system (CURB-65, serum lactate+CURB-65, serum procalcinonin+CURB-65) to predict the severity and 30-day mortality of pneumonia patients admitted to our ED. Methods: This study was planned as a prospective study. 480 community-acquired pneumonia patients admitted to our ED between February 1, 2020, and January 31, 2021, were included. CURB-65 score, CURB-65+lactate levels, and CURB65+procalcitonin levels were evaluated to predict disease severity. Results: A total of 480 pneumonia patients, 281 (58.5%) men and 199 (41.5%) women, with a mean age of 61.7 ± 19.06 years, were included in the study. The sensitivity/specificity pair and cut-off value of CURB-65 for 30-day mortality was 71.9/74.8%. These values were 68.5% and 61.9% for CURB-65+lactate (cut-off = 17.50) and 78.1% and 90.7% for CURB-65+procalcitonin (cut-off = 2.095). Discussion: Infectious diseases such as pneumonia, urinary tract infection, and sepsis are common reasons for ED presentations and may be fatal, especially in the elderly population. In such infectious diseases, it is difficult to predict the prognosis of the patients including discharge, hospitalization service, mortality probability in the EDs those are becoming much more crowded each day and several scoring systems have been improved. In this study, the highest sensitivity and specificity were determined in CURB-65+procalcitonin. Conclusion: CURB-65 is superior to CURB-65+lactate; however, CURB-65+procalcitonin is superior to both in predicting 30-day mortality

A Model-Driven Framework for Hardware-Software Co-design of Dataflow Applications (extended version)

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 and model transformations 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

Endothelial function is more impaired in hemodialysis patients than renal transplant recipients

Backgound: Endothelial dysfunction (ED) is a common precursor and denominator of cardiovascular events including development of atherosclerosis. In this cross-sectional, controlled study, we aimed to investigate ED measured by ischemia-induced forearm vasodilatation in chronic hemodialysis (HD) patients and renal transplant recipients (rTX)