Search

The classification of the IEC-62304 considers the risks of failure due to the software, and ranges from "failure of the software does not contribute to a dangerous situation" (class A) to "failure of the software results in death or serious injury" (class C). Using off-the-shelf software One may wonder whether it's allowed to incorporate tools or off-the-shelf software in your in-house developed software product. Keywords: in vitro diagnostics regulation (IVDR); medical device software; quality management; software development EN in vitro diagnostics regulation (IVDR) medical device software quality management software development 982 988 7 05/26/22 20220601 NES 220601 Introduction The right treatment starts with the right diagnosis. IVDR software can often be seen as software that will drive or inform clinical management, i.e. the results from the software are used to diagnose a patient or to provide information about which treatment to start. [Extracted from the article]

Software size estimation is a vital activity of software project planning and management. Early software size estimation is a challenging task due to the limited information available during the early phases of software development. The goal of this paper is to construct and validate early software size estimation models based on four analysis-to-design adjustment factor (ADAF)-adjusted analysis class diagram metrics (i.e. ADAF-adjusted number of classes, ADAF-adjusted number of attributes, ADAF-adjusted number of methods and ADAF-adjusted number of relationships) using stepwise multiple linear regression and leave-one-out cross-validation. Furthermore, the prediction accuracy of the best-performing proposed model is also compared with the model based on objective class points. The results of this comparison reveal that our proposed method reduces errors significantly (i.e. on average, 16% reduction in mean absolute residual and 24% reduction in mean squared error). [ABSTRACT FROM AUTHOR]

The validation of formal specifications is a challenging task. It is one of the factors that impede the penetration of formal methods into the common practices of software development. This paper discusses the issue of validating formal models by executing them in the context of Event-B. The most important problem lies in the non-determinism which often prevents purely automatic tools to execute models. In this paper, we first present and discuss the techniques we have created to allow the execution of models at all levels of abstraction. These techniques rely on users to overcome the barriers resulting from non-deterministic features by either modifying the model or providing ad hoc implementations. Then, we present our main contribution, the formal definition of the notion of fidelity, that guarantees that all the observable behaviors of the executable models are indeed specified by the original (non-deterministic) models. The notion of fidelity can be expressed in terms of proof obligations. [ABSTRACT FROM AUTHOR]

Software development requires adequate methods for requirements engineering, design, development, testing and maintenance. The more complex the system is, the more sophisticated methods should be applied. A significant part of software projects is short on appropriate requirements engineering, communication, development and testing method, furthermore, verification and validation processes; i.e., not the right method is applied, and the project turns into ad hoc design and development decisions. This paper introduces our quality assured model-driven requirements engineering and software development method. The method is based on the modeling of the software requirements in a way that these models can be used to automatically generate several artifacts during the engineering process. This method is continuously developed during the last 12 years driven by our software projects. In the last two years, we have developed new tool support and also reworked the method. In this paper, as an experience report, we introduce the method: a framework to specify software requirements with four domain-specific languages and automated solutions to process the models. We focus on the requirements engineering method of the whole development cycle. We also report the lessons learned and share our best practices on the field of model-driven requirements engineering and software development. [ABSTRACT FROM AUTHOR]

Model validation methods (e.g., k‐fold cross‐validation) use historical data to predict how well an estimation technique (e.g., random forest) performs on the current (or future) data. Studies in the contexts of software development effort estimation (SDEE) and software fault prediction (SFP) have used and investigated different model validation methods. However, no conclusive indications to suggest which model validation method has a major impact on the prediction accuracy and stability of estimation techniques. Some studies have investigated model validation methods specific to data about either SDEE or SFP. To the best of our knowledge, there is no study in the literature, which has employed different validation methods both with SDEE and SFP data. The aim of this paper is to consider different methods (10) from the family of cross‐validation (CV) and bootstrap validation methods to identify which one contributes to obtaining a better prediction accuracy for both types of data. We also evaluate which model validation methods allow the estimation techniques to provide stable performances (i.e., with lower variance). To this aim, we present an empirical study involving six datasets from the domain of SDEE and six datasets from the SFP domain. The results reveal that repeated 10‐fold CV with SDEE and optimistic boot with SFP data are the model validation methods that provide a better prediction accuracy in a greater number of experiments than the other model validation methods. Furthermore, a model validation method can improve the prediction accuracy up to 60% with SDEE data and up to 36% when employing SFP data. The analysis also reveals that repeated fivefold CV produces more stable performances when the experiments are repeated on the same data. [ABSTRACT FROM AUTHOR]

Background. Smartphone compared to the traditional pen-paper method could enhance oral health data recording procedure by reducing the cost of data collection, risk of data loss, early detection of errors and reducing data entry time. The present research developed a mobile/tablet-based software application to capture oral health data and test its adaptability and operations in oral health surveys. Methods. A comparative cross-sectional study was conducted among the general population of Sanwer town, Indore district. The initial testing of the application was done on 120 individuals. A random sampling (lottery method) followed by a systematic sampling strategy was employed to select 120 households. A "one per household" design was implemented for the survey. The initial oral health data collection was done using mobile-assisted software application followed by a second examination scheduled after 15 days on the same participants using the conventional Pen-paper method to collect oral health data. Results. Six Investigator Recorder (IR) teams conducted the oral health data collection. Data collection through Smartphone-based application displayed less meantime (3.57 minutes) in comparison to pen-paper method (4.87 minutes) (p=0.001). Survey team response showed the majority of investigators having strong agreement on user satisfaction and speed of data entry using software application. Conclusion. The initial testing of mobile-assisted recording system (MARS) efficiently captured oral health data among the general population with wide variations in oral disease level. The application facilitated minimal or no wastage of paper and had a high level of user-satisfaction, accuracy, speed of entry and low potential for any data loss. [ABSTRACT FROM AUTHOR]

The aerospace industry is undergoing unprecedented transformation. New players, new ventures, and new technologies drive the established business towards a transition from traditional models and strategies to automated production and innovative methods. Software architecture for space systems needs to become more agile while preserving a high standard of quality. To that end, the rigorous verification and validation process that yields high quality software products should embrace automation and take full advantage of COTS hardware and software products. In line with the industry transformation, SSL's Flight Software Development and Validation Department uses a modular, layered architecture that has evolved over decades of orbital experience. This paper describes the SSL Flight Software Development and Validation Workflow Management System and the advantages of such a system/framework for development and verification of very complex spacecraft. This system/framework allows faster cyclical test-fix-test process and also provides a platform that can be extended for a multitude of applications. [ABSTRACT FROM AUTHOR]

This paper describes an early development of built-up software for semi-automatic measurement of the multifunction calibrator using the direct method with the high-resolution digital multimeter (DMM) and its validation. The software was developed by SNSU-BSN to control the calibrator and DMM using the GPIB interface. The key advantages of this development were that the software could be used easily, safely, and fast with high accuracy and precision. The developed software has been validated by comparing it to manual measurement. The type A uncertainties achieved by semi-automatic measurement were less than 0.1 µV/V for dc voltage, 0.2 µA/A for dc current, 2 µV/V for ac voltage at 1 kHz, 100 µA/A for ac current at 1 kHz, and 0.1 µΩ/Ω for resistance with each absolute normalized error of the comparison was less than 1. It showed that both the manual and semi-automatic measurements had a good agreement in each measurement, and also the evaluated type A uncertainty in the semi-automatic measurement was smaller than the manual measurement. [ABSTRACT FROM AUTHOR]

Software testing is a complex and critical process for achieving product quality. Its importance has been increasing and well recognized, and there is a growing concern in improving the accomplishment of this process. In this context, Knowledge Management (KM) emerged as an important supporting approach to improve the software testing process. However, managing relevant testing knowledge requires effective means to represent and to associate semantics to a large volume of testing information. To address this concern, we have developed a Reference Ontology on Software Testing (ROoST). ROoST establishes a common conceptualization about the software testing domain, which can serve several KM-related purposes, such as defining a common vocabulary for knowledge workers with respect to the testing domain, structuring testing knowledge repositories, annotating testing knowledge items, and for making search for relevant information easier. In this paper, we present ROoST, and we discuss how it was developed using two ontology pattern languages. Moreover, we discuss how we evaluated ROoST following four complementary approaches: assessment by humans, data-driven evaluation, ontology testing, and application-based evaluation. [ABSTRACT FROM AUTHOR]

This paper presents the software development meta-process (SD-MP) as a proposal to set up software projects. Within this proposal we offer conceptual elements that help solve the war of methodologies and processes in favor of an integrating viewpoint, where the main flaws associated with conventional and agile approaches are removed. Our newly developed software platform to support the meta-process is also presented together with three case studies involving projects currently in progress, where the framework proposed in SD-MP has been applied. [ABSTRACT FROM AUTHOR]

The subject of validation and verification (V&V) of knowledge-based systems (KBS) has been one of decreasing importance in the last decade. Research and development in the field reduced drastically. One of the main reasons is the persistent software challenges and failures. These failures have been categorized in different ways. One initiative however, which most researchers in the field agree upon, is that the only way to eliminate these problems is by rigorously performing V&V. Although there have been vast improvements in the field of V&V methodology, studies indicate that KBS industry still lacks rigorous validation methods. In this paper, we review the most important validation paradigms described in literature for KBS during the years of their fame. Additionally, this article studies the significant methods, aims to reassess these methods in light of recent advances, and propose new future directions for validation of KBS. [ABSTRACT FROM AUTHOR]

Copyright of Revista Ingeniería e Investigación is the property of Universidad Nacional de Colombia, Facultad de Ingenieraia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The number of programming languages is large and steadily increasing. However, little structured information and empirical evidence is available to help software engineers assess the suitability of a language for a particular development project or software architecture. We argue that these shortages are partly due to a lack of high-level, objective programming language feature assessment criteria: existing advice to practitioners is often based on ill-defined notions of ‘paradigms’ [3, p. xiii] and ‘orientation’, while researchers lack a shared common basis for generalisation and synthesis of empirical results. This paper presents a feature model constructed from the programmer's perspective, which can be used to precisely compare general-purpose programming languages in the actor-oriented, agent-oriented, functional, object-oriented, and procedural categories. The feature model is derived from the existing literature on general concepts of programming, and validated with concrete mappings of well-known languages in each of these categories. The model is intended to act as a tool for both practitioners and researchers, to facilitate both further high-level comparative studies of programming languages, and detailed investigations of feature usage and efficacy in specific development contexts. [ABSTRACT FROM AUTHOR]

A software development process comprises all the steps necessary to produce a software product. This research proposes a new process for developing augmented reality serious games (ARSGs), which comprises three phases: analysis, configuration, and generation. The analysis phase involves examining the standard project structure of a typical serious game to identify the applicable actions to which AR content can be added. The configuration phase involves configuring the AR features and the AR library to be integrated into the game structure. Finally, the generation phase entails inserting the AR code in the game structure, as well as all the files necessary to in-corporate AR features in the game. Our process allows generating ARSGs step by step, both easily and rapidly. To implement this process, we propose an ARSG development software architecture. The underlying assumption of this architecture is that software development tools are essential validation elements of the software generation process. By implementing our ARSG development process through a software architecture, we provide users with a formal, automated method for creating ARSGs. The ARSG development process and the architecture, collectively called ZeusAR, are not dependent on specific software development technologies and/or programming languages. To perform a proof-of-concept of our process, we developed an ARSG generator tool based on the proposed architecture and conducted a case study in which geometry ARSGs are developed to help high school students learn about geometric shapes and their properties. We conducted a qualitative evaluation of the ZeusAR tool through a System-Usability-Scale (SUS) based survey, which was administered to a group of geometry teachers to evaluate the tool's characteristics, such as ease of use and ease of configuration. Additionally, a group of software developers and professors assessed the performance of the ZeusAR tool in terms of game development time. [ABSTRACT FROM AUTHOR]

Diagnostic testing is an oft-recommended use of sensitivity analysis to assess correctness or plausibility of model behavior. In this paper we demonstrate the use of sensitivity analysis as a complementary first-pass software test for the validation of model behavior. Typical testing processes rely on comparing model outputs to results known to be correct. Such approaches are limited to specific model configurations and require that correct results be known in advance. Property-based Sensitivity Analysis (PbSA) examines model properties in terms of the behavior of parameter sensitivities to provide a line of evidence that the expected conceptual relationships between model factors and their effects are present. Unanticipated results can indicate issues to be corrected. The PbSA approach is also scalable as it can complement existing testing practices and be applied in conjunction with global sensitivity methods that can reuse existing model evaluations or are otherwise independent of the sampling scheme. • Property-based testing is a common approach for diagnostic assessment and validation in software development. • Sensitivity analysis is used for similar purposes in model development. • Realities of integrated model development may complicate the use of global sensitivity analyses for diagnostic purposes. • Parameter sensitivities can be treated as a property to test to aid in identifying issues during the model development cycle. • Sensitivity analyses should be leveraged to complement other model testing and validation processes. [ABSTRACT FROM AUTHOR]

Early formal verification of a system during initial stages of development has the potential to improve the confidence in the system specifications, in addition to improving the formal verifiability throughout the software development cycle. A formal verification methodology is derived to achieve system modelling and verification during the requirements specification and system design phase. This is achieved by using Focus Stream theory for developing a formal system model derived from requirements analysis leading to a preliminary software design. This results into component architecture and it incorporates the development of component behaviour using Finite Sate Machines. The models developed for real time system encompass modelling of infinite state domains. After model development, formal property enumeration under various categories is done. An enhanced safety property verification is proposed and implemented using Linear Temporal Logic propositions, pattern based properties and system safety based property patterns. Properties verification on the model is done in order to validate and refine the specifications. Derived properties are verified using NuXMV Satisfiability Modulo Theories based algorithms. Tool verification as mandated in RTCA DO-330 is incorporated in the proposed methodology. The proposed approach is practical, implementable by system designers and scalable to handle industrial systems. [ABSTRACT FROM AUTHOR]