Fault Removal Research Articles

Multi core Commercial Off-the-Shelf (Cots) Under the implementation of fault Tolerance

The fault-tolerant design is applicable to high performance IT systems, increased by an amount of false contacts from smaller structures. As a substitute for the hardware solutions that are based on software error tolerance mechanisms, proper solution can increase the reliability for the commercial-of-the-shelf (COTS) multicore processors within a cheaper range with efficiency for further use. This paper aims to create a hybrid approach to hardware-related software, the current Core Intel x86 family and Xeon multi-core platforms. To support memory transactional hardware (TSX Intel) in creating implicit hits and fast rollback redundant process execution and signature comparison for error detection and error recovery can be done through transactional packing. Existing applications have improved redundant instrumentation performance with tolerance to post-binary compound errors. Further physical improvement increases the applicability of the CPU SPEC benchmark approach proposed in 2006 with administrative costs and rated performance over 47% on average based on the existence of proposed hardware support. In this paper, all the techniques for hardware and software level that help us for the removal of faults in multi-core commercial-of-the-shelf (COTS) and that makes the system able enough to work properly.

A Discrete SRGM for Multi-Release Software System with Faults of Different Severity

To meet highly competitive market challenges along with technological upgrades and changing user requirements, software firms offer newer versions of their products by adding new features and new functionalities. But this also results in increase in the fault content of software. In this paper we propose a discrete software reliability growth model (SRGM) for fault removal process incorporating the effect of up-gradations on the subsequent releases of the software. It is further assumed that faults present in the software are not of the same type and may be classified as simple and hard faults depending upon the effort and time consumed for their removal. The proposed model has been validated on a real life dataset for software with four releases. The results obtained are encouraging and fairly accurate.

A two-phase software reliability modeling involving with software fault dependency and imperfect fault removal

Most existing software reliability growth models (SGRMs) often assume software faults are mutually independent and the detected faults can be perfectly removed. However, those two assumptions are not realistic in practice since the dependent faults can also exist in the program. At the same time, it is unlikely to correct all the detected faults in the testing phase due to the limitation of testing resource, the skill and experience of the programmer, and multi-release consideration for software organization. This paper presents a new non-homogeneous Poisson process (NHPP) software reliability model with a pioneering idea by considering software fault dependency and imperfect fault removal. In order to clearly explain software fault dependency, some facts and examples are discussed in Section 1. Two types of software faults are defined, Type I (independent) fault and Type II (dependent) fault, according to fault dependency. Two phases debugging processes, Phase I and Phase II, are proposed according to the debugged software fault type. A small portion of software faults that software testers are not able to remove is also considered in both phases in the proposed model. The illustration of the model effectiveness is based on the three datasets collected from industries. Some limitations of the proposed model are also discussed in the last section.

Design of Wind Turbine Dynamic Trip-Off Risk Alarming Mechanism for Large-Scale Wind Farms

The wind power in China is being developed mainly in terms of large scale, long distance, and high clustering. In this scenario, the uncertainty of wind farm operation gradually becomes a significant factor that power grid dispatcher needs to deal with. Among which, trip-off risk of wind turbine results from system disturbance, fault and fault removal of wind farm, etc. Besides, the geographical distribution of wind turbine usually also has the impact on the trip-off risk of wind farm. In view of above factors, existing security analysis methodology is difficult to satisfy the requirement of real-time alarming due to extreme analytical difficulty and huge computing complexity. Therefore, reasonable design of trip-off risk measure index of wind turbine becomes a key issue to implement a dynamic trip-off real-time alarming system. In this paper, a wind turbine trip-off decision tree system is constructed with the discrete characteristics of wind turbine distribution in wind farms taken into account. The decision trees can perform data mining using online information and make fast prediction on wind turbine voltage out-of-limit and trip-off situations under anticipated accident sets. The trip-off risk measure indexes are then output in light of the prediction results, which can provide intuitive risk level information and decision references for operators in wind farms and power systems. The results of case studies show that the proposed method can meet the requirement of prediction accuracy and resolve the contradictions between the amount of modeled nodes, the diversity of anticipated faults and the computation time when performing over-voltage early warning and control strategies.

Queueing-Theory-Based Models for Software Reliability Analysis and Management

Software reliability is one of the most important internal attributes of software systems. Over the past three decades, many software reliability growth models have been proposed and discussed. Some research has also shown that the fault detection and removal processes of software can be described and modeled using an infinite-server queueing system. But, there is practically no company that can afford unlimited resources to test and correct detected faults in the real world. Consequently, the number of debuggers should be limited, not infinite. In this paper, we propose an extended finite-server-queueing (EFSQ) model to analyze the fault removal process of the software system. Numerical examples based on real project data are illustrated. Evaluation results show that our proposed EFSQ model has a fairly accurate prediction capability of software reliability and also depict the real-life situation of software development activities more faithfully. Finally, the applications of our proposed model to project management are also presented. Our proposed model can provide a theoretically effective technique for managing the necessary activities of testing and debugging in software project management.

Stochastic Formulation of Fault Severity Based Multi Release SRGM Using the Effect of Logistic Learning

In today’s environment, software reliability is one of the major concerns for Software firms. Many Software Reliability Growth Model (SRGM) has been developed and many are under process. In order to meet the requirements of consumer and to excel in competitive environment, companies are coming up with multiple add –ons. We design the model as stochastic with continuous state space because of large software system, the count of failures observed is huge and so, the variation in count of errors detected/ removed in each debugging is petite compared to original error content at the beginning of testing. This study is an add on to the software reliability literature where we have developed multi release SRGM’s based on available concept of depending on previous releases. The errors have been categorically divided upon the severity of their removal as one stage, two stage, three stage fault removal process is applied in an environment of irregular fluctuations.

Superconducting magnetic energy storage (SMES) devices integrated with resistive type superconducting fault current limiter (SFCL) for fast recovery time

Energy storage devices experience load fluctuations due to fault currents, lightening and non-uniform load distribution. Hence, Superconducting Magnetic Energy Storage (SMES) devices are incorporated to balance these fluctuations as well as to store the energy with larger current density. Further, Superconducting Fault Current Limiter (SFCL) are integrated with SMES for avoiding fault currents. In addition, SFCL are preferred in electrical utility networks due to their better technical performance during faults as compared to the conventional Circuit Breakers. Self-triggering from superconducting state to normal state during fault and very fast recovery to its original superconducting state after fault removal is the fundamental operation of Resistive type Superconducting Fault Current Limiter (R-SFCL). Moreover, commercial applications of SFCL in electrical power systems are enormously increasing due to the availability of long length High Temperature Superconducting (HTS) tapes.In the present work, an algorithm is developed to estimate the recovery time of R-SFCL with three phases to be used in SMES. Further, the electrical and thermal strategies to develop R-SFCL are also presented. In addition, the short circuit behaviour under fault currents is investigated considering 440kV/1.2kA capacity line. Finally, the percentage of fault compensation in all the three phases of SMES integrated with R-SFCL is calculated.

What is a fault? and why does it matter?

Faults are an important concept in the study of system dependability, and most approaches to dependability can be characterized by the way in which they deal with faults (e.g., fault avoidance, fault removal, fault tolerance, fault forecasting). In their seminal work on modeling dependable computing, Laprie et al. define a fault as the adjudged or hypothesized cause of an error. In this paper, we propose a more formal definition of a fault in the context of software products and discuss some of its implications.

A testing-coverage software reliability model considering fault removal efficiency and error generation.

In this paper, we propose a software reliability model that considers not only error generation but also fault removal efficiency combined with testing coverage information based on a nonhomogeneous Poisson process (NHPP). During the past four decades, many software reliability growth models (SRGMs) based on NHPP have been proposed to estimate the software reliability measures, most of which have the same following agreements: 1) it is a common phenomenon that during the testing phase, the fault detection rate always changes; 2) as a result of imperfect debugging, fault removal has been related to a fault re-introduction rate. But there are few SRGMs in the literature that differentiate between fault detection and fault removal, i.e. they seldom consider the imperfect fault removal efficiency. But in practical software developing process, fault removal efficiency cannot always be perfect, i.e. the failures detected might not be removed completely and the original faults might still exist and new faults might be introduced meanwhile, which is referred to as imperfect debugging phenomenon. In this study, a model aiming to incorporate fault introduction rate, fault removal efficiency and testing coverage into software reliability evaluation is developed, using testing coverage to express the fault detection rate and using fault removal efficiency to consider the fault repair. We compare the performance of the proposed model with several existing NHPP SRGMs using three sets of real failure data based on five criteria. The results exhibit that the model can give a better fitting and predictive performance.

An Ideal Software Release Policy for an Improved Software Reliability Growth Model Incorporating Imperfect Debugging with Fault Removal Efficiency and Change Point

This paper presents a general software reliability growth model (SRGM) based on non-homogeneous Poisson process (NHPP) and optimal software release policy with cost and reliability criteria. The main motive of this study is to develop a software release time decision model considering maintenance cost and warranty cost under fuzzy environment. In previous studies, maintenance cost has been defined either in terms of warranty cost or fault debugging cost. In reality, maintenance cost includes the cost of free patches, updates, technical support and future enhancement. Also, it is possible that maintenance process causes the removal of software faults in the operational phase including the faults which occur outside the warranty period or warranty definition. In other words, warranty action may be included the maintenance action, but not the converse. Considering this fact, maintenance cost and warranty cost are defined separately in the proposed study. Initially, an SRGM has been proposed with the revised concept of imperfect debugging phenomenon considering fault removal efficiency (FRE). Furthermore, the effect of changes in various environmental factors on models parameters has been taken into account. Numerical examples based on real software failure data sets have been given to analyze the performance of the proposed models.

An imperfect software debugging model considering irregular fluctuation of fault introduction rate

ABSTRACTIn general, software testing is a complicated and uncertain process. New faults can be introduced into the software during each fault removal. This process is called imperfect debugging. For simplicity, fault introduction rates are generally assumed to be constant. However, software debugging can be affected by many factors, such as subjective and objective influences, the difficulty and complexity of fault removal, the dependent relationships among faults, the changes in different phases of software testing, and the test schedules. Thus, the rate of fault introduction is not a constant, but is an irregularly fluctuating variable in software debugging. In this article, we propose a model with imperfect software debugging considering the irregular changes in fault introduction rates during software debugging. Experimental results reveal that our proposed model has good fitting capability and considerably stronger forecasting performance than that of the other models, and that the proposed model assumptions are close to the actual software debugging situation. Moreover, research on the irregular fluctuation of the fault introduction rate in software debugging has a certain reference value and important significance for software-intensive product testing, for instance, cloud computing.

Development of Reclosing Method considering Interconnection of BESS as Uninterruptible Power Supply

In this paper, a reclosing method considering the battery energy storage system (BESS) as an uninterruptible power supply is proposed. The proposed method detects the fault condition and keeps the power supply from BESS in good condition. After passing of fixed dead time, a synchronism checking is performed between the utility power and the power from the BESS and then the reclosing is performed when it is completed. To verify the proposed method, the whole distribution system including BESS and proposed method are modeled by the ElectroMagnetic Transients Program (EMTP)/ATPDraw, and the various simulations are performed according to the fault removal time. The simulation results show that the BESS can be operated as a UPS and successful reclosing is possible.

Reliability analysis for multi-release open-source software systems with change point and exponentiated Weibull fault reduction factor

Evolutions in technology and rapid growth of open-source software (OSS) applications have made upgradation indispensable. To incorporate vagaries in users needs and environmental situations that affect the reliability growth of OSS, fault reduction factor (FRF) is one of the important factors to be considered during multi-release software development process. In this paper, a software reliability growth model (SRGM) has been proposed for successive releases to include some of the critical but realistic characteristics such as time variant FRF, effect of change point due to changing strategies and error generation during fault removal phenomena. For model validation, two popular open-source projects—Mozilla and Gnome—have been chosen for its multi-release real data sets. An optimal updation schedule problem is formulated, and a numerical illustration has been worked out. The goodness of fit of the proposed model is shown by comparing it with one of the well-known models reported in the literature.

Abstract TP100: Pharmacological Inhibition of ACC1 Restrains Peripheral T Cell Activation and Protects Against Cerebral Ischemic Stroke

Background and purpose: T cell activation, which is detrimental to the ischemic brain, requires metabolic reprogramming to meet the increased fuel demanding. ACC1 is an enzyme catalyzing the carboxylation of acetyl-CoA to malonyl CoA, a key substrate in the glycolytic-lipogenic pathway, which is extremely critical for T cell differentiation and phenotype polarization. We tested the hypothesis that pharmacologically inhibiting the enzyme ACC1 early after stroke may restrain T cell activation and protect against cerebral ischemic injury. Methods: Cerebral ischemia was induced by middle cerebral artery occlusion (MCAO) for 60 minutes in C57/B6 mice. Soraphen A, the specific pharmacological inhibitor of ACC1 was administered at 1 hour after reperfusion at the dose of 1mg/kg, 5mg/kg, 10mg/kg and 50mg/kg intraperitoneally. Infarct volume was assess at 3 days after surgery by staining with 2,3,5-triphenyltetrazolium chloride. Behavior assessments, such as body proprioception, climbing, forelimb walking, lateral turning, foot fault and adhesive removal were examined at 3, 5, 7, 14, 21 and 28 days after stroke. T cell infiltration into the ischemic brain was examined by immunofluorescent staining. Results: Mice treated with 5mg/kg or 10mg/kg soraphen A exhibited significantly smaller infarct volume at 3 days after stroke. 5mg/kg was chosen as the dose for further experiments. Soraphen A treatment improved the overall neurological assessment and enhanced the performance of mice in adhesive removal test and grid walking test. Soraphen A treatment significantly attenuated the CD3+ T cell and Gr-1+ neutrophil infiltration in the ischemic mice brain at 3 days after surgery. Conclusion: Pharmacological inhibition of T cell activation by soraphen A is protective against cerebral ischemic injury and may represent a novel strategy for stroke therapy.

Abstract 158: Pre-existing Cancer Exacerbates Cerebral Ischemic Stroke in Mice via Regulatory T Cell Redistribution

Background and purpose: Accumulating epidemic evidence suggest that a considerable number of ischemic stroke patients had 1 or more cancer diagnosis before stroke attack. How the pre-existing cancer impact the cerebral ischemic injury is remarkably unknown. We tested the hypothesis that pre-existing cancer exacerbates cerebral ischemic stroke via regulatory T cell (Treg) redistribution. Methods: MC38 colon cancer cells or B16 melanoma cells were injected subcutaneously at the dose of 5*10 5 cells in 200μl PBS 3 weeks before distal middle cerebral artery occlusion (d-MCAO) surgery. Infarct volume was assessed at 3 days after surgery by staining the mice brain with 2,3,5-triphenyltetrazolium chloride. Sensorimotor assessments, such as body proprioception, climbing, forelimb walking, lateral turning, foot fault and adhesive removal were examined at 3, 5, 7, 14, 21 and 28 days after stroke. Neuro-inflammation was examined by measuring inflammatory cytokines with RT-PCR and immune cell infiltration using immunofluorescence and flow cytometry. Results: Pre-existing colon cancer and melanoma both exacerbated infarct volume growth in d-MCAO mice at 3 days after surgery. Mice with colon cancer exhibited prominently deterioration in their performance in sensorimotor functions after stroke compared with mice without cancer. Pre-existing colon cancer augmented peripheral immune cell infiltration into the ischemic brain but hindered Tregs’ recruitment into the brain. Cerebral ischemic stroke induced reduction in the number of Tregs in the peripheral blood were significantly aggravated in mice with pre-existing colon cancer. Depletion of Tregs with CD25 monoclonal antibody increased infarct volume in stroke mice but did not further exacerbate infarct growth in colon cancer stroke mice. Conclusion: Pre-existing cancer exacerbates ischemic brain injury and neuro-inflammation after stroke. Tregs redistribution plays an indispensable role in the cancer related deterioration of ischemic brain injury and may represent a promising target for treating stroke patients with pre-existing cancer.

A Multi Release Cost Model in Distributed Environment

Software industry has reached far beyond since its origin. Technical advancements are taking place at a speed faster than ever. This has further enhanced the pressure on software developers. They are trying hard to keep a pace with these rapid developments by coming out with strategies to increase the pace of their work without significantly affecting the software quality and reliability. One such strategy is distributed development of software in which the software is composed of two different types of components viz. newly developed and re-used component. Software developed in Distributed Development Environment (DDE) is characterized by enhanced availability and reliability. At the same time, the ever growing contention in the market and increasing needs of customers obligate the developers to come out with enhanced functionalities in the software from time to time leading to multiple releases of a software. The added functionalities further enhance the existing complexity of the software and testing team may not be able to perfectly remove the faults leading to imperfect debugging or add more bugs due to lack of knowledge about the software in the initial phase known as error generation. In this paper, we incorporated this real-life phenomenon to come out with a multi up-gradations modeling for removal of software fault in a distributed environment. In the present framework we described a cost model to obtain optimal release time in multi up-gradation of software under distributed environment. To validate the analytical results of the proposed framework, numerical illustration is provided.

Сравнительный анализ способов ликвидации неустойчивых однофазных коротких замыканий в нетранспонированных линиях сверх- и ультравысокого напряжения

Сравнительный анализ способов ликвидации неустойчивых однофазных коротких замыканий в нетранспонированных линиях сверх- и ультравысокого напряжения

Change point–based software reliability model under imperfect debugging with revised concept of fault dependency

A detailed study about the characteristics of different types of faults is necessary to enhance the accuracy of software reliability estimation. Over the last three decades, some software reliability growth models have been proposed considering the possibility of existence of two types of faults in a software: (1) independent and (2) dependent faults. In these software reliability growth models, it is considered that the removal of a leading fault or independent fault causes detection of corresponding dependent faults. In practical, it is noticed that some dependent faults are possible in a software which are removed during the removal of other faults. Moreover, dependent faults may have different characteristics, which cannot be ignored. Considering these facts, a detailed study about the different characteristics of both dependent and independent faults has been performed, and based on this study, dependent faults have been categorized into different categories. Furthermore, a new software reliability growth model has been proposed with revised concept of fault dependency under imperfect debugging by introducing the fault removal proportionality. In addition, the effect of change point on model’s parameters due to different environmental factors has been considered. The fault reduction factor is considered as a proportionality function. Experimental results establish the fact that the performance of the proposed model is better with respect to estimated and predicted cumulative number of faults on some real software failure datasets.

Analysis of the Tools Used to Control the Parameters of Pump Units Intended for Oil-Trunk Pipelines in Ukraine

It has been established that oil pipelines never operate in one mode with the maximum efficiency (defined by the project). The pipelines operate in the modes of a different efficiency, which is very often much lower than the potential output and this can be caused by irregular oil deliveries by oil-producing companies, a change in the freight flow, withdrawal for the repair of the portion of oil-transfer units and the removal of faults in the linear part, etc. In this case it is required to control operating conditions in oil transfer systems to maintain the mode specified by the chart of operating practices (COP). This paper analyzes the control tools of the parameters of oil pumps designed for oil-trunk pipelines in Ukraine. It is shown that the operation of the systems of oil – trunk pipelines faces many technological problems related to the choice of energy-efficient operating conditions due to the irregular oil transfer for the specified time period. Available methods of the control of operating conditions for the ²pump equipment-oil trunk pipeline² system have many drawbacks that should be taken into account during their selection at the design stage or operation in specific conditions. A promising energy-efficient technique was suggested to control the operating conditions of superchargers, which is based on the minimization of drive power input and the assurance of the maximum values of efficiency factor.

An NHPP SRGM with Change Point and Multiple Releases

In an environment of intense competition, software upgrades have become the necessity for the survival in software industry. In this paper, the authors propose a discrete Software Reliability Growth Model (SRGM) for the software with successive releases by taking into consideration the realistic assumption that Fault Removal Rate (FRR) may not remain constant during the testing process, it changes due to severity of faults detected and due to change in strategies adapted by testing team and the time point where FRR changes is called the Change Point. Many researchers have developed SRGMs incorporating the concept of Change Point for single release software. The proposed model aims to present multi release software reliability modeling with change point. Discrete logistic distribution function has been used to model relationship between features enhancement and fault removal. It is helpul in developing a flexible SRGM, which is S-shaped in nature. In order to evaluate the proposed SRGM, parameter estimation is done using the real life data set for software with four releases and the goodness-of-fit of this model is analyzed.