Optimal software release policies for a non-homogeneous software error detection rate model

Optimal software release policies, which decide when to stop testing a software system and transfer it to the user, are discussed for a software reliability growth model with nonhomogeneous error detection rate. Two evaluation criteria, i.e. total expected software cost and software reliability, are introduced. The optimal software release policies respectively derived for each criterion and those simultaneously evaluating both criteria are discussed. Numerical examples on those optimal software release policies are presented for illustration.     

Software reliability release policy with testing effort

An improved software reliability release policy is presented, based on the nonhomogeneous Poisson process (NHPP) and incorporating the effect of testing effort. Testing effort functions are modelled by exponential, Rayleigh and Weibull curves. The optimal software release time is determined by minimizing the total expected software cost under the conditions of satisfying a software reliability objective. Numerical examples have been included to illustrate the software release policy.     

A New Methodology for Predicting Software Reliability in the Random Field Environments

This paper presents a new methodology for predicting software reliability in the field environment. Our work differs from some existing models that assume a constant failure detection rate for software testing and field operation environments, as this new methodology considers the random environmental effects on software reliability. Assuming that all the random effects of the field environments can be captured by a unit-free environmental factor,$eta$, which is modeled as a random-distributed variable, we establish a generalized random field environment (RFE) software reliability model that covers both the testing phase and the operating phase in the software development cycle. Based on the generalized RFE model, two specific random field environmental reliability models are proposed for predicting software reliability in the field environment: the$gamma$-RFE model, and the$beta$-RFE model. A set of software failure data from a telecommunication software application is used to illustrate the proposed models, both of which provide very good fittings to the software failures in both testing and operation environments. This new methodology provides a viable way to model the user environments, and further makes adjustments to the reliability prediction for similar software products. Based on the generalized software reliability model, further work may include the development of software cost models and the optimum software release policies under random field environments.     

Optimal release time for software systems considering cost, testing-effort, and test efficiency

In this paper, we study the impact of software testing effort & efficiency on the modeling of software reliability, including the cost for optimal release time. This paper presents two important issues in software reliability modeling & software reliability economics: testing effort, and efficiency. First, we propose a generalized logistic testing-effort function that enjoys the advantage of relating work profile more directly to the natural flow of software development, and can be used to describe the possible testing-effort patterns. Furthermore, we incorporate the generalized logistic testing-effort function into software reliability modeling, and evaluate its fault-prediction capability through several numerical experiments based on real data. Secondly, we address the effects of new testing techniques or tools for increasing the efficiency of software testing. Based on the proposed software reliability model, we present a software cost model to reflect the effectiveness of introducing new technologies. Numerical examples & related data analyzes are presented in detail. From the experimental results, we obtain a software economic policy which provides a comprehensive analysis of software based on cost & test efficiency. Moreover, the policy can also help project managers determine when to stop testing for market release at the right time.     

Optimum software release policy with random life cycle

A software release problem based on four software reliability growth models (SRGMs) with random life-cycle length is studied. Test of the software system is terminated after time T and released (sold) to the user at a price. The price of the software system and three cost components are considered, and average total profit is used as a criterion. The optimal values of release times are shown to be finite and unique. Hence, the optimal solutions can be obtained numerically by, for example, a bisection method. A numerical example indicates that the optimal release time increases as (1) the error rate in each model decreases and (2) the difference between the error fixing cost during the test phase and that during the operational phase increases. The case of unknown model parameters is considered only for the Jelinski-Moranda model because a Bayes model is not available for other SRGMs. The release decision depends on testing time, but other stopping rules, for example based on the number of corrected errors, can be considered     

Incorporating fault debugging activities into software reliability models: a simulation approach

A large number of software reliability growth models have been proposed to analyse the reliability of a software application based on the failure data collected during the testing phase of the application. To ensure analytical tractability, most of these models are based on simplifying assumptions of instantaneous & perfect debugging. As a result, the estimates of the residual number of faults, failure rate, reliability, and optimal software release time obtained from these models tend to be optimistic. To obtain realistic estimates, it is desirable that the assumptions of instantaneous & perfect debugging be amended. In this paper we discuss the various policies according to which debugging may be conducted. We then describe a rate-based simulation framework to incorporate explicit debugging activities, which may be conducted according to the different debugging policies, into software reliability growth models. The simulation framework can also consider the possibility of imperfect debugging in conjunction with any of the debugging policies. Further, we also present a technique to compute the failure rate, and the reliability of the software, taking into consideration explicit debugging. An economic cost model to determine the optimal software release time in the presence of debugging activities is also described. We illustrate the potential of the simulation framework using two case studies.     

Application of a software reliability model to decide software release time

In this paper, using a Binomial reliability model, we formulate the optimal software release time problem as a probabilistic dynamic programming. Using some properties of the cost functions associated with this problem, we develop an efficient algorithm to obtain the optimal release time decision.     

Software Reliability Analysis by Considering Fault Dependency and Debugging Time Lag

Over the past 30 years, many software reliability growth models (SRGM) have been proposed. Often, it is assumed that detected faults are immediately corrected when mathematical models are developed. This assumption may not be realistic in practice because the time to remove a detected fault depends on the complexity of the fault, the skill and experience of personnel, the size of debugging team, the technique(s) being used, and so on. During software testing, practical experiences show that mutually independent faults can be directly detected and removed, but mutually dependent faults can be removed iff the leading faults have been removed. That is, dependent faults may not be immediately removed, and the fault removal process lags behind the fault detection process. In this paper, we will first give a review of fault detection & correction processes in software reliability modeling. We will then illustrate the fact that detected faults cannot be immediately corrected with several examples. We also discuss the software fault dependency in detail, and study how to incorporate both fault dependency and debugging time lag into software reliability modeling. The proposed models are fairly general models that cover a variety of known SRGM under different conditions. Numerical examples are presented, and the results show that the proposed framework to incorporate both fault dependency and debugging time lag for SRGM has a better prediction capability. In addition, an optimal software release policy for the proposed models, based on cost-reliability criterion, is proposed. The main purpose is to minimize the cost of software development when a desired reliability objective is given.     

Reliability optimization models for embedded systems with multiple applications

Summary and Conclusions-This paper presents four models for optimizing the reliability of embedded systems considering both software and hardware reliability under cost constraints, and one model to optimize system cost under multiple reliability constraints. Previously, most optimization models have been developed for hardware-only or software-only systems by assuming the hardware, if any, has perfect reliability. In addition, they assume that failures for each hardware or software unit are statistically independent. In other words, none of the existing optimization models were developed for embedded systems (hardware and software) with failure dependencies. For our work, each of our models is suitable for a distinct set of conditions or situations. The first four models maximize reliability while meeting cost constraints, and the fifth model minimizes system cost under multiple reliability constraints. This is the first time that optimization of these kinds of models has been performed on this type of system. We demonstrate and validate our models for an embedded system with multiple applications sharing multiple resources. We use a Simulated Annealing optimization algorithm to demonstrate our system reliability optimization techniques for distributed systems, because of its flexibility for various problem types with various constraints. It is efficient, and provides satisfactory optimization results while meeting difficult-to-satisfy constraints.     

An exponential SRGM with a bound on the number of failures

An exponential software reliability growth model (SRGM) incorporating a situation where more than one failure can be attributed to one fault/error has been proposed. Different model parameters have been estimated and an optimal release policy which minimizes the software cost, subject to achieving a given level of reliability, has been discussed. Finally, a numerical example illustrating the applicability of the model and a few practical situations where this model can be applied are also given.     

An S-shaped software reliability growth model with two types of errors

An S-shaped software reliability growth model (SRGM) based on a non-homogeneous Poisson process (NHPP) with two types of errors has been proposed. The errors have been classified depending upon their severity. We have estimated the model parameters and obtained the optimum release policies which minimize the cost subject to achieving a given level of reliability. Numerical results illustrating the applicability of the proposed model are also presented.     

Determination of software release instant using a nonhomogeneous error detection rate model

The nonhomogeneous error detection rate model has been extensively used in software reliability modelling. An important management responsibility is to make a decision about the release of software, so as to result in maximum cost effectiveness. It is well known that the effort for correction of an error increases, rather heavily, from an initial testing phase to a final testing phase and then to the operational phase. In this paper, a method is presented to systematically determine this optimum release instant. The fact that some faults can be regenerated during the process of correction has also been considered in the modelling—this has been ignored in previous literature. Also, the partition of the testing phase into initial and final phases is considered to be desirable as effort per error correction will be significantly different in these two phases. An example illustrates the entire procedure for various values of the total number of errors and the trends of cost and release time.     

Optimal design for software reliability and development cost

A process for reliability-related quality programming is developed to fill existing gaps in software design and development so that a quality programming plan can be achieved. The tradeoffs among system reliability improvement, resource consumption, and other relevant constraints through the management phase are investigated. A software reliability-to-cost relation is developed both from a software reliability-related cost model and from software redundancy models with common-cause failures. A generic N-component redundancy model is also developed. The software reliability optimization problems can be formulated into a mixed-integer programming problem     

Optimal design of large software-systems using N-versionprogramming

Fault tolerant software uses redundancy to improve reliability; but such redundancy requires additional resources and tends to be costly, therefore the redundancy level needs to be optimized. Our optimization models determine the optimal level of redundancy within a software system under the assumption that functionally equivalent software components fail independently. A framework illustrates the tradeoff between the cost of using N-version programming and the improved reliability for a software system. The 2 models deal with: a single task, and multitask software. These software systems consist of several modules where each module performs a subtask and, by sequential execution of modules, a major task is performed. Major assumptions are: 1) several versions of each module, each with an estimated cost and reliability, are available, 2) these module versions fail independently. Optimization models are used to select the optimal set of versions for each module such that the system reliability is maximized and total cost remains within budget     

Software reliability analysis based on a nonhomogeneous error detection rate model

A software reliability growth model discussed here assumes a nonhomogeneous error detection rate per error which characterizes a software reliability growth process during the testing phase. The methods for software reliability assessment are reviewed, and the model fitting and software reliability analysis for some software error data sets are presented. The optimum software release times are also given for the data analysis results.     

Modeling and Analysis of Software Fault Detection and Correction Process by Considering Time Dependency

Software reliability modeling & estimation plays a critical role in software development, particularly during the software testing stage. Although there are many research papers on this subject, few of them address the realistic time delays between fault detection and fault correction processes. This paper investigates an approach to incorporate the time dependencies between the fault detection, and fault correction processes, focusing on the parameter estimations of the combined model. Maximum likelihood estimates of combined models are derived from an explicit likelihood formula under various time delay assumptions. Various characteristics of the combined model, like the predictive capability, are also analyzed, and compared with the traditional least squares estimation method. Furthermore, we study a direct, useful application of the proposed model & estimation method to the classical optimal release time problem faced by software decision makers. The results illustrate the effect of time delay on the optimal release policy, and the overall software development cost.     

Integrating reliability and timing analysis of CAN-based systems

This paper presents and illustrates a reliability analysis method developed with a focus on controller-area-network-based automotive systems. The method considers the effect of faults on schedulability analysis and its impact on the reliability estimation of the system, and attempts to integrate both to aid system developers. The authors illustrate the method by modeling a simple distributed antilock braking system, and showing that even in cases where the worst case analysis deems the system unschedulable, it may be proven to satisfy its timing requirements with a sufficiently high probability. From a reliability and cost perspective, this paper underlines the tradeoffs between timing guarantees, the level of hardware and software faults, and per-unit cost.     

Software-reliability growth with a Weibull test-effort: a model andapplication

Software reliability measurement during the testing phase is essential for examining the degree of quality or reliability of a developed software system. A software-reliability growth model incorporating the amount of test effort expended during the software testing phase is developed. The time-dependent behavior of test-effort expenditures is described by a Weibull curve. 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 Poission process. Using the model, the method of data analysis for software reliability measurement is developed. This model is applied to the prediction of additional test-effort expenditures to achieve the objective number of errors detected by software testing, and the determination of the optimum time to stop software testing for release     

单片机电力监控系统交流采样的实现及抗干扰措施

以８０９８单片机为主体设计远程电力监控系统的用户级分站，能做到低成本、高性能，适用于监控中小型电力用户的用电情况．电力参数的数据采集是其从重要的环节，要求硬件投资少，软件占用ＣＰＵ时间少．本文介绍了用８０９８单片机实现电力参数交流直接采样技术的一套经济实用而又稳定可靠的方法，对其硬件结构原理、软件设计思想以及去除现场干扰的软硬件措施等进行了阐述．     

Reliability-estimation and stopping-rules for software testing,based on repeated appearances of bugs

Software-testing (debugging) is one of the most important components in software development. An important question in the debugging process is, when to stop. The choice is usually based on one of two decision criteria: (1) when the reliability has reached a given threshold, and (2) when the gain in reliability cannot justify the testing cost. Various stopping rules and software reliability models are compared by their ability to deal with these two criteria. Two new stopping rules, initiated by theoretical study of the optimal stopping rule based on cost, are more stable than other rules for a large variety of bug structures. The 1-step-ahead stopping rules based on the Musa et. al. basic execution and logarithmic Poisson models, as well as the stopping rule by Dalal and Mallows (1990), work well for software with many relatively small bugs (bugs with very low occurrence rates). The comparison was done by simulation