169,284 research outputs found

    Early component-based reliability assessment using UML based software models

    Get PDF
    In the last decade, software has grown in complexity and size, while development timelines have diminished. As a result, component-based software engineering is becoming routine. Component-based software reliability assessment combines the architecture of the system with the reliability of the components to obtain the system reliability. This allows developers to produce a reliable system and testers to focus on the vulnerable areas.;This thesis discusses a tool developed to implement the methodology previously created for early reliability assessment of component-based systems. The tool, Early Component-based Reliability Assessment (ECRA), uses Rational Rose Unified Modeling Language (UML) diagrams to predict the reliability of component-based software. ECRA provides the user with an easy interface to annotate the UML diagrams and uses a Bayesian algorithm to predict the system reliability. This thesis presents the methodology of ECRA, the steps taken to develop it, and its applications

    Empirical assessment of architecture-based reliability of open-source software

    Get PDF
    A number of analytical models have been proposed earlier for quantifying software reliability. Some of these models estimate the failure behavior of the software using black-box testing, which treats the software as a monolithic whole. With the evolution of component based software development, the necessity to use white-box testing increased. A few architecture-based reliability models, which use white-box approach, were proposed earlier and they have been validated using several small case studies and proved to be correct. However, there is a dearth of large-scale empirical data used for reliability analysis. This thesis enriches the empirical knowledge in software reliability engineering. We use a real, large-scale case study, GCC compiler, for our experiments. To the best of out knowledge, this is the most comprehensive case study ever used for software reliability analysis. The software is instrumented with a profiler, to extract the execution profiles of the test cases. The execution profiles form the basis for building the operational profile of the system, which describes the software usage. The test case failures are traced back to the faults in the source code to analyze the failure behavior of the components. These results are used to estimate the reliability of the software, as well as the uncertainty in the reliability analysis using entropy

    Model-based risk assessment

    Get PDF
    In this research effort, we focus on model-based risk assessment. Risk assessment is essential in any plan intended to manage software development or maintenance process. Subjective techniques are human intensive and error-prone. Risk assessment should be based on architectural attributes that we can quantitatively measure using architectural level metrics. Software architectures are emerging as an important concept in the study and practice of software engineering nowadays, due to their emphasis on large-scale composition of software product, and to their support for emerging software engineering paradigms, such as product line engineering, component based software engineering, and software evolution.;In this dissertation, we generalize our earlier work on reliability-based risk assessment. We introduce error propagation probability in the assessment methodology to account for the dependency among the system components. Also, we generalize the reliability-based risk assessment to account for inherent functional dependencies.;Furthermore, we develop a generic framework for maintainability-based risk assessment which can accommodate different types of software maintenance. First, we introduce and define maintainability-based risk assessment for software architecture. Within our assessment framework, we investigate the maintainability-based risk for the components of the system, and the effect of performing the maintenance tasks on these components. We propose a methodology for estimating the maintainability-based risk when considering different types of maintenance. As a proof of concept, we apply the proposed methodology on several case studies. Moreover, we automate the estimation of the maintainability-based risk assessment methodology

    Reliability model for component-based systems in cosmic (a case study)

    Get PDF
    Software component technology has a substantial impact on modern IT evolution. The benefits of this technology, such as reusability, complexity management, time and effort reduction, and increased productivity, have been key drivers of its adoption by industry. One of the main issues in building component-based systems is the reliability of the composed functionality of the assembled components. This paper proposes a reliability assessment model based on the architectural configuration of a component-based system and the reliability of the individual components, which is usage- or testing-independent. The goal of this research is to improve the reliability assessment process for large software component-based systems over time, and to compare alternative component-based system design solutions prior to implementation. The novelty of the proposed reliability assessment model lies in the evaluation of the component reliability from its behavior specifications, and of the system reliability from its topology; the reliability assessment is performed in the context of the implementation-independent ISO/IEC 19761:2003 International Standard on the COSMIC method chosen to provide the component\u27s behavior specifications. In essence, each component of the system is modeled by a discrete time Markov chain behavior based on its behavior specifications with extended-state machines. Then, a probabilistic analysis by means of Markov chains is performed to analyze any uncertainty in the component\u27s behavior. Our hypothesis states that the less uncertainty there is in the component\u27s behavior, the greater the reliability of the component. The system reliability assessment is derived from a typical component-based system architecture with composite reliability structures, which may include the composition of the serial reliability structures, the parallel reliability structures and the p-out-of-n reliability structures. The approach of assessing component-based system reliability in the COSMIC context is illustrated with the railroad crossing case study. © 2008 World Scientific Publishing Company

    UML Support for Reliability Evaluation

    Get PDF
    Abstract. Today's software systems are developed and targeted for satisfying sometimes very critical functions. Reliability is considered to be one of the most important nonfunctional quality attribute of such software systems. The aim of reliability estimation in early stages of software development process -analysis and design -should reduce the future costs for possible failure repairing through increasing the reliability before the construction of the software system. Because, the Unified Modeling Language (UML) becomes the standard for software system's specification, the last works done in architecture based reliability estimation and assessment use UML as the base for software architecture specification. In this paper, we discuss the existing approaches with critical overview and outline the directions for future research

    Software maintainability assessment based on collaborative CMMI model

    Get PDF
    Software constantly needs new features or bug fixes. Maintainable software is simple to extend and fix which encourages the software's uptake and use. The Software Sustainability Institute can advise you on the design and development of maintainable software that will benefit both you and your users. Therefore, capability maturity model integration (CMMI) is a process improvement approach that provides organisations with the essential elements of effective processes that ultimately improve their performance. The propose maintainability assessment of cmmi based on multi-agent system (MAS) to identify the processes measurement of SM. in order to verify our proposed CMMI framework based on MAS architecture, pilot study is conducted using a questionnaire survey. Rasch model is used to analyse the pilot data. Items reliability is found strong correlation between measured and the model designed. The results shows that the person raw score-to-measure correlation is 0.51 (approximate due to missing data) and Cronbach Alpha (kr-20) person raw score reliability = .94

    Estimating Software Reliability for Space Launch Vehicles in Probabilistic Risk Assessment (PRA)

    Get PDF
    It is acutely recognized in the Probabilistic Risk assessment (PRA) field that software plays a defining role in overall system reliability for all modern systems across a wide variety of industries. Regardless if the software is embedded firmware for working components or elements, part of a Human-Machine-Interface, or automated command and control logic, the success of the software to fulfill its function under nominal and off-nominal environments will be a dominant contributor to system reliability. It is also recognized that software reliability prediction and estimation is one of the more challenging and questionable aspects of any PRA or system analyses due to the nature of software and its integration with physics based systems. Irrespective of this dichotomy, any incorporation of software reliability methods requires that the contributions are accountable, quantitative, and tractable. This paper provides a brief overview of software reliability methods, establishes some minimum requirements that the methods should incorporate for completeness, and provides a logic structure for applying software reliability. Model resolution will be discussed that supports current testing plans and trade studies. We will provide initial recommendations for use in the NASA PRA and present a future dynamic option for software and PRA. Space Launch Vehicle Software is recognized to be reliable in static conditions, yet relatively vulnerable to a set of failure modes in changing environments/flight phases. Two quantitative methods were chosen to incorporate software reliability into a Space Launch Vehicle PRA accounting for phase adjustments. One method predicts latent software failure using statistical methods, and the second provides estimates of coding errors and software operating system failures based on test and historical data, respectively. Software uncertainty will also be discussed. We determined that recommendations for PRA software reliability should be modeled at the software module level where multiple software components compose a module and combinations of the software architecture can lead to a functional failure

    Software reliability prediction using neural network

    Get PDF
    Software engineering is incomplete without Software reliability prediction. For characterising any software product quality quantitatively during phase of testing, the most important factor is software reliability assessment. Many analytical models were being proposed over the years for assessing the reliability of a software system and for modeling the growth trends of software reliability with different capabilities of prediction at different testing phases. But it is needed for developing such a single model which can be applicable for a relatively better prediction in all conditions and situations. For this the Neural Network (NN) model approach is introduced. In this thesis report the applicability of the models based on NN for better reliability prediction in a real environment is described and a method of assessment of growth of software reliability using NN model is presented. Mainly two types of NNs are used here. One is feed forward neural network and another is recurrent neural network. For modeling both networks, back propagation learning algorithm is implemented and the related network architecture issues, data representation methods and some unreal assumptions associated with software reliability models are discussed. Different datasets containing software failures are applied to the proposed models. These datasets are obtained from several software projects. Then it is observed that the results obtained indicate a significant improvement in performance by using neural network models over conventional statistical models based on non homogeneous Poisson process

    A Free Industry-grade Education Tool for Bulk Power System Reliability Assessment

    Full text link
    A free industry-grade education tool is developed for bulk-power-system reliability assessment. The software architecture is illustrated using a high-level flowchart. Three main algorithms of this tool, i.e., sequential Monte Carlo simulation, unit preventive maintenance schedule, and optimal-power-flow-based load shedding, are introduced. The input and output formats are described in detail, including the roles of different data cards and results categorization. Finally, an example case study is conducted on a five-area system to demonstrate the effectiveness and efficiency of this tool.Comment: This paper was submitted to a conferenc
    corecore