A model driven approach for software reliability prediction

Software reliability, one of the major software quality attributes, quantitatively expresses the continuity of correct service delivery. In current practice, reliability models are typically measurement-based models, and mostly employed in isolation at the later stage of the soft ware development process, after architectural decisions have been made that cannot easily be reversed early software reliability prediction models are often insufficiently formal to be ana- lyzable and not usually connected to the target system. We postulate it is possible to overcome these issues by supporting software reliability engineering from requirements to deployment using scenario specifications. We contribute a novel reliability prediction technique that takes into account the component structure exhibited in the scenarios and the concurrent nature of component-based systems by extending scenario specifications to model (1) the probability of component failure, and (2) scenario transition probabilities. Those scenarios are subsequently transformed into enhanced behaviour models to compute the system reliability. Additionally we enable the integration between reliability and development models through profiles that extend the core Unified Modelling Language (UML). By means of a reli ability profile, the architecture of a component-based system can express both method invoca tions and deployment relationships between the application components in one environment. To facilitate reliability prediction, and determine the impact of concurrency on systems reliability, we have extended the Label Transition System Analyser Tool (LTSA), implementing a plugin for reliability analysis. Finally, we evaluate our analysis technique with a case study focusing on Condor, a dis tributed job scheduler and resource management system. The purpose of the case study is to evaluate the efficacy of our analysis technique and to compare it with other reliability tech niques

Reliability prediction in model driven development

Evaluating the implications of an architecture design early in the software development lifecycle is important in order to reduce costs of development. Reliability is an important concern with regard to the correct delivery of software system service. Recently, the UML Profile for Modeling Quality of Service has defined a set of UML extensions to represent dependability concerns (including reliability) and other non-functional requirements in early stages of the software development lifecycle. Our research has shown that these extensions are not comprehensive enough to support reliability analysis for model-driven software engineering, because the description of reliability characteristics in this profile lacks support for certain dynamic aspects that are essential in modeling reliability. In this work, we define a profile for reliability analysis by extending the UML 2.0 specification to support reliability prediction based on scenario specifications. A UML model specified using the profile is translated to a labelled transition system (LTS), which is used for automated reliability prediction and identification of implied scenarios; the results of this analysis are then fed back to the UML model. The result is a comprehensive framework for addressing software reliability modeling, including analysis and evolution of reliability predictions. We exemplify our approach using the Boiler System used in previous work and demonstrate how reliability analysis results can be integrated into UML models

Sensitivity Analysis for a Scenario-Based Reliability Prediction Model

As a popular means for capturing behavioural requirements, scenariosshow how components interact to provide system-level functionality.If component reliability information is available, scenarioscan be used to perform early system reliability assessment. Inprevious work we presented an automated approach for predictingsoftware system reliability that extends a scenario specificationto model (1) the probability of component failure, and (2) scenariotransition probabilities. Probabilistic behaviour models ofthe system are then synthesized from the extended scenario specification.From the system behaviour model, reliability predictioncan be computed. This paper complements our previous work andpresents a sensitivity analysis that supports reasoning about howcomponent reliability and usage profiles impact on the overall systemreliability. For this purpose, we present how the system reliabilityvaries as a function of the components reliabilities and thescenario transition probabilities. Taking into account the concurrentnature of component-based software systems, we also analysethe effect of implied scenarios prevention into the sensitivity analysisof our reliability prediction technique

Methods of Technical Prognostics Applicable to Embedded Systems

Hlavní cílem dizertace je poskytnutí uceleného pohledu na problematiku technické prognostiky, která nachází uplatnění v tzv. prediktivní údržbě založené na trvalém monitorování zařízení a odhadu úrovně degradace systému či jeho zbývající životnosti a to zejména v oblasti komplexních zařízení a strojů. V současnosti je technická diagnostika poměrně dobře zmapovaná a reálně nasazená na rozdíl od technické prognostiky, která je stále rozvíjejícím se oborem, který ovšem postrádá větší množství reálných aplikaci a navíc ne všechny metody jsou dostatečně přesné a aplikovatelné pro embedded systémy. Dizertační práce přináší přehled základních metod použitelných pro účely predikce zbývající užitné životnosti, jsou zde popsány metriky pomocí, kterých je možné jednotlivé přístupy porovnávat ať už z pohledu přesnosti, ale také i z pohledu výpočetní náročnosti. Jedno z dizertačních jader tvoří doporučení a postup pro výběr vhodné prognostické metody s ohledem na prognostická kritéria. Dalším dizertačním jádrem je představení tzv. částicového filtrovaní (particle filtering) vhodné pro model-based prognostiku s ověřením jejich implementace a porovnáním. Hlavní dizertační jádro reprezentuje případovou studii pro velmi aktuální téma prognostiky Li-Ion baterii s ohledem na trvalé monitorování. Případová studie demonstruje proces prognostiky založené na modelu a srovnává možné přístupy jednak pro odhad doby před vybitím baterie, ale také sleduje možné vlivy na degradaci baterie. Součástí práce je základní ověření modelu Li-Ion baterie a návrh prognostického procesu.The main aim of the thesis is to provide a comprehensive overview of technical prognosis, which is applied in the condition based maintenance, based on continuous device monitoring and remaining useful life estimation, especially in the field of complex equipment and machinery. Nowadays technical prognosis is still evolving discipline with limited number of real applications and is not so well developed as technical diagnostics, which is fairly well mapped and deployed in real systems. Thesis provides an overview of basic methods applicable for prediction of remaining useful life, metrics, which can help to compare the different approaches both in terms of accuracy and in terms of computational/deployment cost. One of the research cores consists of recommendations and guide for selecting the appropriate forecasting method with regard to the prognostic criteria. Second thesis research core provides description and applicability of particle filtering framework suitable for model-based forecasting. Verification of their implementation and comparison is provided. The main research topic of the thesis provides a case study for a very actual Li-Ion battery health monitoring and prognostics with respect to continuous monitoring. The case study demonstrates the prognostic process based on the model and compares the possible approaches for estimating both the runtime and capacity fade. Proposed methodology is verified on real measured data.

A compositional method for reliability analysis of workflows affected by multiple failure modes

We focus on reliability analysis for systems designed as workflow based compositions of components. Components are characterized by their failure profiles, which take into account possible multiple failure modes. A compositional calculus is provided to evaluate the failure profile of a composite system, given failure profiles of the components. The calculus is described as a syntax-driven procedure that synthesizes a workflows failure profile. The method is viewed as a design-time aid that can help software engineers reason about systems reliability in the early stage of development. A simple case study is presented to illustrate the proposed approach

Overview of Remaining Useful Life prediction techniques in Through-life Engineering Services

Through-life Engineering Services (TES) are essential in the manufacture and servicing of complex engineering products. TES improves support services by providing prognosis of run-to-failure and time-to-failure on-demand data for better decision making. The concept of Remaining Useful Life (RUL) is utilised to predict life-span of components (of a service system) with the purpose of minimising catastrophic failure events in both manufacturing and service sectors. The purpose of this paper is to identify failure mechanisms and emphasise the failure events prediction approaches that can effectively reduce uncertainties. It will demonstrate the classification of techniques used in RUL prediction for optimisation of products’ future use based on current products in-service with regards to predictability, availability and reliability. It presents a mapping of degradation mechanisms against techniques for knowledge acquisition with the objective of presenting to designers and manufacturers ways to improve the life-span of components