Summary Many open‐source software are included in commercial software. Also, several open‐source software are used in the cloud service such as OpenStack and Eucalyptus from standpoint of the unified management, cost reduction and maintainability. In particular, the operation phase of cloud service has a unique feature with uncertainty such as big data and network connectivity, because the operation phase of cloud service changes depending on many external factors. On the other hand, the effective methods of performance assessments for cloud service have only a few presented. Recently, edge computing is the focus of attention because of the problems of connection and processing delay in case of cloud computing. It is known as that cloud computing treats big data. On the other hand, edge computing operates on instant data. We focus on the performance assessments based on the relationship between the cloud and edge services operated by using several open‐source software. Then we propose a two‐dimensional stochastic differential equation model considering the unique features with uncertainty from big data under the operation of cloud and edge services. Also, we analyse actual data to show numerical examples of performance assessments considering the network connectivity as characteristics of cloud and edge services. Moreover, we compare the noise terms of the proposed model for actual data.

We discuss SIL (safety integrity level) assessment for software of E/E/PE (Electrical/Electronic/Programmable Electronic) safety-related systems. The SIL is known as a graded measure representing the safety integrity of E/E/PE safety-related systems, and has been defined in IEC 61508, which is an international standard issued totally in 2000 (the second version has been issued in 2010) for E/E/PE safety-related systems. We try to develop mathematical models for estimating the approximations of the PFD (time-averaged probability of failure on demand) and PFH (time-averaged frequency of dangerous failure per hour), which are the target failure measures of SIL, for the E/E/PE safety-related software by applying the notion of software reliability modeling and assessment methods.

In this paper, we inquire aesthetical aspects of the Japanese tea ceremony, described as the aesthetics in the imperfection, based on novel fabrication technologies: 3D-modeling and 3D-printing. To do so, 3D-printed utensils (chashaku and chasen) were iteratively designed for the ceremony and were evaluated using constructivist interviews, eliciting personal construct of a tea master on the beauty of these utensils. Our findings suggest that (1) beauty in the imperfection is feasible with 3D-printers, (2) such beauty can be created at the mechanical limits of the printer, creating uncontrolled yet beautiful irregularities, (3) further research can be made on the dialogue between the designer and the machine, leaving space for beautiful mechanical uncertainty. We invite designers and design researchers (1) to look at the potential of new technologies beyond what is classically expected, (2) to consider other cultural perspectives on aesthetics and on making, leading to potential novel practices in design.

A software hazard rate model is known as one of the important and useful mathematical models for describing a software failure-occurrence phenomenon and conducting quantitative software reliability assessment. It is known that there exists a case that characteristic of the software failure-occurrence or the fault-detection phenomenon is changed notably in a testing-phase or an operational phase due to changes of factors influencing on the software reliability growth process. Taking into consideration of the effect of the change in software reliability growth modeling is expected to conduct more accurate software reliability assessment because it is said that such approach enables us to conduct more plausible software reliability assessment reflecting an actual testing-environment. Especially in this paper, we develop exponential-type software hazard rate models with effect of change-point, and discuss change-point detection methods for applying our model to quantitative software reliability assessment. Finally, we conduct goodness-of-fit comparisons of our models with existing software hazard rate models, and show numerical examples for software reliability assessment based on our specific change-point models by using actual data.

We discuss a bootstrap method for estimating software reliability and cost-reliability-optimal software release time via a discretized software reliability growth model, which conserves the properties of the continuous analog of the discretized model. And then, we conduct interval estimations of them by three types of bootstrap confidence interval estimation methods, such as basic, standard normal, and percentile bootstrap confidence intervals. In our numerical examples, we confirm that our bootstrap approach yields simulation-based probability distributions of model parameters, software reliability assessment measures, and cost-reliability-optimal software release time without deriving these probability distributions analytically.

We discuss interval estimation methods for cost-optimal software release time based on a discretized software reliability growth model. In our approach, we use a bootstrap method, in which we do not need to derive probability distributions of model parameters and optimal software release time analytically by using an asymptotic theory assuming a large number of samples. Then we estimate bootstrap confidence intervals of cost-optimal software release time based on two kinds of bootstrap confidence interval methods. Our numerical examples confirm that our bootstrap approach yields a simulation-based probability distribution of cost-optimal software release time from software fault-count data.

SUMMARY Embedded Open Source Software (OSS) systems have been gaining a lot of attention in the embedded system area. The successful experience of embedded OSSs include Android, BusyBox, TRON, etc. Also, OSS market will be expanded not only to mobile phone OSS areas but also to other embedded OSS areas in the future. However, the poor handling of quality problem and customer support prohibit the progress of embedded OSS. Also, it is difficult for developers to assess the reliability and portability of embedded OSS on a single‐board computer. A method of software reliability assessment based on flexible hazard rate modeling for the embedded OSS is proposed in this paper. Also, several numerical examples are shown by using actual data. Moreover, this paper compares the proposed model with the conventional hazard rate models by using the comparison criteria of goodness‐of‐fit. Copyright © 2011 John Wiley & Sons, Ltd.

A cloud computing is attracting attention as a network service to share the computing resources such as networks, servers, storage, applications, and services. We focus on a cloud computing environment by using open source software such as OpenStack and Eucalyptus because of the unification management of data, low cost. In this paper, we propose a new approach to software dependability assessment based on a stochastic differential equation model in order to consider the interesting aspect of the numbers of components and users. Also, we analyze actual data to show numerical examples of software dependability assessment considering such characteristics of cloud computing environment. Moreover, we formulate a total expected software cost model for the environment of cloud computing. Then, we discuss the determination of optimum software maintenance times minimizing the total expected software cost.

In the functional safety standard (IEC 61508), development methods and quantitative analytical methods are defined for establishment of safety-related systems. However, only development methods are recommended to establish the software of safety-related systems. That is, the safety integrity level for software is determined only by the number of the development methods applied to practical safety-related system development. This is not reasonable to evaluate the safety integrity level, because various risk factors should be taken up. In this paper, we propose how to calculate the safety integrity level for software. Especially, we propose the calculation method based on software reliability growth models that have been utilized for many years in the large-scale system development.

We discuss the performability evaluation model for the computer-based system, introducing the concept of codesign. We assume that the computer system consists of one hardware, and one software subsystems; and consider both of hardware, and software failure & restoration characteristics. In particular, the reliability growth process, the upward tendency of difficulty in debugging, and the imperfect debugging environment are described for the software subsystem. Assuming that the system can process the multiple tasks simultaneously, and that the arrival process of the tasks follows a nonhomogeneous Poisson process (NHPP), we use infinite server queueing theory to analyze the distribution of the number of tasks whose processes can be completed within the processing time limit. We derive several performability measures considering the real-time property, which are given as the functions of time, and the number of debugging activities. Finally we illustrate several numerical examples of the measures to investigate the impact of hardware and software failure & restoration characteristics on the system performability evaluation.

An OSS (open source software) system is frequently applied as server use, instead of client use. Especially, embedded OSS systems have been gaining a lot of attention in the embedded system area, i.e., Android, BusyBox, TRON, etc. However, the poor handling of quality problem and customer support prohibit the progress of embedded OSS. Also, it is difficult for developers to assess the reliability and portability of embedded OSS on a single-board computer. We focus on software quality/reliability problems that can prohibit the progress of embedded OSS. In this paper, we propose a method of software reliability assessment based on a hazard rate model for the embedded OSS. In particular, we derive several assessment measures from the model. Also, we analyze actual software failure-occurrence time-interval data to show numerical examples of software reliability assessment for the embedded OSS. Moreover, we discuss the optimal software release problem for the porting-phase based on the total expected software maintenance cost.

Open source software serve as key components of critical infrastructures in the social life. We focus on the quality problems of open source software developed under open source project. In case of considering the effect of the debugging process on an entire system in the development of a method of reliability assessment for open source project, it is necessary to grasp the deeply-intertwined factors, such as programming path, size of each component, skill of fault reporters, and so on.

Eliciting customer's requirements is the most important issue for a system integration project. Failure to elicit the customer's requirements can cause an enormous correction cost. However there are only a few practical, concrete guidelines to do. In this paper, we describe a method to extract viewpoints and checklists for eliciting customer's requirements more effectively based on analyzing specification change records. The flow of the method is 1) representing the records in an easy-readable format, 2) identifying the causes and the phases, 3) categorizing them, 4) putting a name to a category, namely a viewpoint and 5) deriving check-items for each viewpoint. We applied the method to 135 records from 4 system development cases, and we derived 39 check-items in total. We found 78% of the specification change cases could have been prevented by only 10 check-items of requirements elicitation process. This result shows that the proposed method works effectively to extract the viewpoints for eliciting customer's requirements.

Network technologies have made rapid progress with the dissemination of computer systems in all areas. The current software development environment has been changing into new development paradigms such as concurrent distributed development environment and the so-called open source project by using network computing technologies. Especially, OSS (Open Source Software) systems which serve as key components of critical infrastructures in the society are still ever-expanding now.We focus on OSS developed under open source project. In case of considering the effect of the debugging process on an entire system in the development of a method of reliability assessment for open source project, it is necessary to grasp the deeply-intertwined factors, such as programming path, size of each component, skill of fault reporter, and so on. In order to consider the effect of each software component on the reliability of an entire system under such open source software development, we propose a new approach to software reliability assessment by creating a fusion of neural networks and a software reliability growth model. Also, it has been necessary to manage the software development process in terms of reliability, effort, and version-upgrade time. In this paper, we .nd the optimal total version-upgrade time based on the total expected software maintenance effort.

Generalized methods for software reliability growth modeling have been proposed so far. But, most of them are on continuous-time software reliability growth modeling. Many discrete software reliability growth models (SRGM) have been proposed to describe a software reliability growth process depending on discrete testing time such as the number of days (or weeks); the number of executed test cases. In this paper, we discuss generalized discrete software reliability growth modeling in which the software failure-occurrence times follow a discrete probability distribution. Our generalized discrete SRGMs enable us to assess software reliability in consideration of the effect of the program size, which is one of the influential factors related to the software reliability growth process. Specifically, we develop discrete SRGMs in which the software failure-occurrence times follow geometric and discrete Rayleigh distributions, respectively. Moreover, we derive software reliability assessment measures based on a unified framework for discrete software reliability growth modeling. Additionally, we also discuss optimal software release problems based on our generalized discrete software reliability growth modeling. Finally, we show numerical examples of software reliability assessment by using actual fault-counting data

Software development environment has been changing into new development paradigms such as concurrent distributed development environment and the so-called open source project by using network computing technologies. In case of considering the effect of the debugging process on an entire system in the development of a method of reliability assessment for open source project, it is necessary to grasp the deeply-intertwined factors, such as programming path, size of each component, skill of fault reporter, and so on. In order to consider the effect of each software component on the reliability of an entire system under such new distributed development paradigm, we propose a new approach to software reliability assessment by creating a fusion of neural network and software reliability growth model. In this paper, we show application examples of software reliability assessment based on neural network and software reliability growth model for open source software. Also, we analyze actual software fault count data to show numerical examples of software reliability assessment for the open source software. Then, we consider the efficiency and effectiveness of the software reliability assessment method for the actual open source software.

An observational system for tele-micro-operation has been proposed with a dynamic focusing system and a high-speed image processing system using the "depth from focus" criteria. In our past work (2000), we proposed the system which has the "all-in-focus image" and the "depth" of an object, simultaneously. Actually, in micro operation, such as for micro-surgery, DNA operation and etc., the small depth of a focus on the microscope gives bad observability. In this sense, the "all-in-focus image", which holds the in-focused texture all over the image, is useful for observing micro environments with a microscope. It is also important to obtain the depth map, and to show the 3D micro virtual environments in real-time to actuate the micro objects, intuitively. The past system with dynamic focusing lens and smart sensor could obtain the "all-in-focus image" and the "depth" in 2 sec. To realize real-time micro operation, at least, a 30 frame/sec system should be required. The paper briefly reviews the criteria of "depth from focus" to achieve the all-in-focus image and the 3D micro environments' reconstruction, simultaneously. After discussing the problem in our past system, a new frame-rate system is constructed with high-speed video camera and FPGA hardware. To apply this system in a real microscope, new criteria to reconstruct the all-in-focus image is proposed. Finally, micro observation shows the validity of the system.

We propose a criterion to determine a more appropriate software reliability growth model in the early development phase. The criterion with a discrete software reliability growth model determines the absolute worth of a model because the discrete software reliability growth model perfectly reproduces the parameter estimates when the data are used as an exact solution of the equation. The values of the proposed criterion of a discrete software reliability growth model are smaller than those of another software reliability growth model in all periods during the test phase with actual data sets. The discrete software reliability growth models are described with difference equations which have exact solutions. The models yield accurate parameter estimates in spite of a small amount of input data in an actual software testing. Therefore, the criterion and discrete software reliability growth models enable us to predict in the early development phase when software can be released.

A software reliability growth model incorporating the amount of test effort expenditures during the software testing phase is described. The time-dependent behavior of test-effort expenditures is described by a Weibull curve due to the flexibility. Assuming that the error detection rate to the amount of test-effort spent during the testing phase is proportional to the current error content, the model is formulated by a nonhomogeneous Poisson process. Using this model, the method of data analysis for software reliability measurement is presented. Also, this model is applied to the prediction of additional test-effort expenditures to obtain the objective number of errors detected by software testing and the determination of the optimum time to stop software testing for release.>

This paper summarizes existing software reliability growth models (SRGM's) described by nonhomogeneous Poisson processes. The SRGM's are classified in terms of the software reliability growth index of the error detection rate per error. The maximum-likelihood estimations based on the SRGM's are discussed for software reliability data analysis and software reliability evaluation. Using actual software error data observed by software testing, application examples of the existing SRGM's are illustrated.