Optimal Software Release Time Research Articles

Modeling Software Release Time and Software Patch Release Time Based on Testing Effort and Warranty

In this world of software technology, our dependency on software’s is increasing continuously. As a result, software industries are working hard to develop highly reliable software and to meet the expectation of customers. Generally, software companies release software early in market to take gain market share, but rigorous software testing is required for early release software to ensure reliability of software and meet the customer’s expectations. This requires a huge amount of resources, and it increases financial burden on the company, consequently, decreases the overall profit of company. Further, late release due to prolong testing of a software may improves reliability but results into a loss of market opportunity cost or may not be fulfil the customer’s aspirations. As a result, to stay competitive, companies release software early and release patches later to fix the bugs, improve the functionality of software, and to update the software. Software industries are improving the performance or usability of software by releasing patches which may increase the consumption of testing effort and consequently increase in cost. On the other hand, software firms also provide warranty on their products. To address the above said issues, we have developed a testing effort-based software reliability growth model, which incorporates warranty policy and estimates the optimal software release and patch time with the objective to minimise the total testing cost. Further, we have used Genetic Algorithm (GA) to estimate optimum software release and patch time. A numerical illustration has been presented on a real time data set to validate the proposed model.

Software reliability and cost models with warranty and life cycle

With increasing number of tech-savvy users, the demand for software with advanced features is also growing exponentially. To meet these expectations, software firms are coming up with innovative strategies to attract customers to buy their products and remain loyal. One of the key strategies is to provide product assurance is post-sales support. Software firms provide a warranty to fix the failures encountered during the operational phase for a pre-defined time period. Software reliability literature consists of various modeling framework to decide release time under pre-defined warranty period under the consideration of no post-release testing. Very limited work has been done in the direction of post-release testing with warranty. In this work, we propose a framework to obtain optimal release and warranty time of software to minimize the overall cost under reliability constraint. We have provided the algorithm to obtain the analytical solution of release and warranty time. To make our proposed work more realistic we have considered the change point phenomenon and imperfect debugging of fault in our modeling framework. We have also conducted a sensitivity analysis on the model parameters to check their impact of the firms scheduling strategy. The proposed work is validated on a real-life data set.

Software release and testing stop time decision with change point

Information technology has seen enormous growth in the last few decades. The backbone of this growth is the developments in the software industry who is working day and night to meet all the expectations. As we know a reliable software can ease our work but developing reliable software may take a longer time. At the same time, huge market competition has forced firms to deliver reliable products as quick as possible as per the user’s expectation. Due to this trade-off between reliability and market competition firms have started releasing software products with the assurance that they will repair their products if any failure is detected while operating. Keeping this phenomenon in mind various researchers proposed a framework based on a different set of assumptions. During the software development at some point of time the rate of detection/removal changes due to various reasons such as a change in testing efficiency, team composition, the addition of extra testing team, etc. This change in the fault removal has an impact on the release and testing stop time of software. In this paper, we propose a software cost model to determine optimal software release and testing stop time considering the change in detection/removal rate before the release of the software. The proposed model is validated on real-life data set.

Two-Dimensional NHPP Models Based on Several Testing-Time Functions and Their Applications

Enormous testing-time and testing-effort (central processing unit (CPU) time, execution time, man-hour, test coverage, executed test case, and so forth) are invested in testing-phase for enhancing software reliability. Although they are software reliability growth factors, existing software reliability growth models (SRGMs) are not introduced simultaneously. Also, the software reliability growth factors enable to substitute each other partly. Therefore, we develop new bivariate nonhomogeneous Poisson process (NHPP) models based on two types of testing-time functions in this paper. Concretely, we assume that the testing-time as a software reliability growth factor is composed of the testing-time and testing-effort factors. Then, the testing-time as the software reliability growth factor is expressed by the Cobb–Douglas and constant elasticity of substitution (CES) type testing-time functions. We conduct goodness-of-fit comparisons of existing models with proposed bivariate models. Also, we discuss estimation method of the optimal software release time and optimal amount of testing-effort as an application. Finally, we show numerical examples by using actual datasets.

Assessing software upgradation attributes and optimal release planning using DEMATEL and MAUT

This study analyses the software upgradations aspects of industries by applying the DEMATEL method and then finding the optimal release time of the upgraded software using MAUT to remain competitive in the market. Founded on the literature reviews and based on expert's opinion, three significant viewpoints and eight attribute were identified as key factors and then further confirmed by industry professionals. The result exhibited that the strategic perception from management point of view was the most significant perception and greatly influenced the remaining two viewpoints. The applicability of DEMATEL method is to confirm interrelationships among diverse attributes and helps to recognise the key attributes whereas the role of MAUT process is to identify the release time of software based on casual relations among attributes. So here the objective is: 1) to identify and analyses upgradation attributes; 2) based on analysis/outcome of DEMATEL method optimal release time of software is determined.

Optimal Release Time Estimation of Software System using Box-Cox Transformation and Neural Network

The determination of the software release time for a new software product is the most critical issue for designing and controlling software development processes. This paper presents an innovative technique to predict the optimal software release time using a neural network. In our approach, a three-layer perceptron neural network with multiple outputs is used, where the underlying software fault count data are transformed into the Gaussian data by means of the well-known Box-Cox power transformation. Then the prediction of the optimal software release time, which minimizes the expected software cost, is carried out using the neural network. Numerical examples with four actual software fault count data sets are presented, where we compare our approach with conventional Non-Homogeneous Poisson Process (NHPP) -based Software Reliability Growth Models (SRGMs).

A Unified Approach for Optimal Release, Patching and Testing Time of a Software

The ever growing consumer's expectations for innovative and reliable software products within no time have driven developers to reframe the whole development process accordingly. To sustain in the stiff market competition, nowadays software firms are releasing their product early and continue testing to fix the remaining number of bugs in the operational phase by providing patches. A patch is a small program to fix the bugs. But continuing testing to provide patches for better product experience to users is also not economical from the firm's point of view. In the existing software reliability literature, few researchers have worked on to determine the optimal release and testing stop time of a software, but no work has been done to determine the optimal time for releasing, patching and to stop testing the software. In this paper, we present a unified framework of optimal policy to determine optimal software release time, patching time and testing stop time, to minimise overall testing cost. The proposed cost model is validated on a real life software failure dataset of tandem computers.

A New Reliability Model for Optimal Software Release Time

A New Reliability Model for Optimal Software Release Time

NHPP software reliability model considering the uncertainty of operating environments with imperfect debugging and testing coverage

• The uncertainty of operating environments and imperfect debugging are considered. • Fault detection rate is based on testing coverage and the model is based on NHPP. • The performance of the proposed model is compared with other 15 existing models. • Optimal software release time and its sensitivity analysis are discussed based on cost and reliability. • Seven criteria and improved normalized criteria distance method are used in the experiments. In this paper, we propose a testing-coverage software reliability model that considers not only the imperfect debugging (ID) but also the uncertainty of operating environments based on a non-homogeneous Poisson process (NHPP). Software is usually tested in a given control environment, but it may be used in different operating environments by different users, which are unknown to the developers. Many NHPP software reliability growth models (SRGMs) have been developed to estimate the software reliability measures, but most of the underlying common assumptions of these models are that the operating environment is the same as the developing environment. But in fact, due to the unpredictability of the uncertainty in the operating environments for the software, environments may considerably influence the reliability and software's performance in an unpredictable way. So when a software system works in a field environment, its reliability is usually different from the theory reliability, and also from all its similar applications in other fields. In this paper, a new model is proposed with the consideration of the fault detection rate based on the testing coverage and examined to cover ID subject to the uncertainty of operating environments. We compare the performance of the proposed model with several existing NHPP SRGMs using three sets of real software failure data based on seven criteria. Improved normalized criteria distance (NCD) method is also used to rank and select the best model in the context of a set of goodness-of-fit criteria taken all together. All results demonstrate that the new model can give a significant improved goodness-of-fit and predictive performance. Finally, the optimal software release time based on cost and reliability requirement and its sensitivity analysis are discussed.

어랑분포의 형상모수 변화에 따른 소프트웨어 개발 비용모형에 관한 비교 연구

소프트웨어 개발과정에서 소프트웨어 신뢰성은 매우 중요한 문제 중에 하나이다. 소프트웨어 고장현상을 분석하기 위하여 비동질적인 포아송과정에서 고장 발생 추이를 의미하는 위험함수가 고장시간에 독립적으로 일정하거나, 종속적인 경우, 즉 비-증가 또는, 비-감소하는 속성을 가질 수 있다. 본 연구에서는 소프트웨어 제품 테스팅 과정에서 고장 수명분포로서 어랑분포의 다양한 형상모수를 고려한 소프트웨어 개발 비용 분석에 대하여 연구되었다. 소프트웨어 고장현상을 분석하기 위하여 모수추정은 최우추정법이 사용되었다. 따라서 본 논문에서는 어랑분포의 형상모수를 고려한 소프트웨어 개발비용모형 분석을 위하여 소프트웨어 고장간격 시간자료를 이용하여 비교 및 평가하였다. 그 결과 형상모수에 따른 비용곡선을 비교 하였을 때 형상모형이 작을수록 비용이 많고 소프트웨어 최적 방출시간이 지연 됨을 알 수 있었다. 이 연구를 통하여 소프트웨어 개발자들에게 소프트웨어 형상모수에 따른 개발 비용을 탐색하는데, 기본적으로 도움을 줄 수 있는 사전정보의 역할을 할 수 있을 것으로 판단된다. Software Reliability implemented in software development is one of the most important issues. In finite failure NHPP software reliability models for software failure analysis, the hazard function that means a failure rate may have constant independently for failure time, non-increasing or non-decreasing pattern. In this study, software development cost analysis considering the variable shape parameter of Erlang distribution as the failure life distribution in the software product testing process was studied. The software failure model was applied finite failure Non-Homogeneous Poisson Procedure and the parameters approximation using maximum likelihood estimation was accompanied. Thus, this paper was presented comparative analysis by applying a software failure time data to the software, considering the shape parameter of Erlang distribution for development cost model analysis. When compared to the cost curve in accordance with the shape parameter, the model of smaller shape can be seen that the optimal software release time delay and more cost. Through this study, it is thought that it can serve as a preliminary information which can basically help the software developers to search for development cost according to software shape parameters.

When to Release and Stop Testing of a Software

For several decades both practitioners as well as researchers have contributed immensely towards solving one of the prime concerns of software firms regarding how long to continue testing? Although, efficient testing ensures reliable software but costs a lot to developer in terms of higher testing and market opportunity cost. Hence it’s imperative to obtain optimal testing time of software. Product release marking the end to software testing has been the phenomenon commonly observed in both practice and theory but often leaves customer dissatisfied either in the form of delayed release (prolonged testing phase) or lower reliability (shortened testing phase). To address this issue, current practices in software industry involve a post release testing phase during which organization aims at treating remaining software faults and subsequently enhance product experience for customers. In this paper we present a generalized framework of optimal scheduling policy to determine optimal software release and testing stop time separately, to minimize overall testing cost under reliability and budget constraints. One of the biggest advantages of early release is capitalizing market opportunity while post release testing ensures adequate software reliability. We also propose that software testing & operational phases are governed by different distribution functions in our proposed cost model. Numerical illustration is provided at the end of the paper to validate the proposed cost model.

Optimal release and patching time of software with warranty

As we know in a competitive market, software firms are looking to sell their products at the earliest for maximum gains. Early delivery of a product is beneficial in terms of gaining market potential but may include some defects in it. On the other hand late delivery of a product ensures reliability but may results into disinterest of the customers. Thus, a vendor must focus on the best time for releasing the software. In recent times, early software release and updating it by providing patches in the operational phase is in trend. Also to satisfy customer’s primary concern of reliable software, firms are providing warranty on their products. Warranty period is the time in which firm provide assurance to the customers that under this period product will work properly and if any defect is found, firm will either repair or replace the software without charging the customer. But servicing during warranty period by updating with patches is also not economical from firm’s point of view. Hence it is important to find the optimal patch release time. In this paper we have proposed a generalized framework to find out the optimal release and patching time of software under warranty so that the total cost is minimized. Numerical example is given at the end to validate the proposed cost model.

Testing effort based modeling to determine optimal release and patching time of software

In this era of information technology, our dependence on software systems is increasing day by day. This dependence on software systems has increased the pressure on software firms to fulfill the customer’s demand for highly reliable software. On the other hand, for ensuring high reliability of the software prolonged testing is required, which consumes large amount of resources hence not feasible in the current stiff market competition. Further delay in release can cost a lot in terms of market opportunity. Therefore, to sustain in the market, firms are releasing the software early and removing the remaining number of bugs by updating with patches. A patch is a piece of software designed to update a computer program or its supporting data, to fix or improve it. With such patches usually called bug fixes, firms improve the usability or performance of the software. Providing patches needs extra amount of effort and manpower which costs high. Also early patch release may result in improper removal of bugs and late release can increase the risk of more of failures in the operational phase To overcome the above issues we have proposed a testing effort based cost model to determine the optimal release and patch time of a software so that the total cost is minimized. In the proposed cost model developing team continues removing the faults even after software release. Further, we have taken different distribution function in pre and post release phase (before and after patching) to develop the proposed cost model. Numerical illustration is provided at the end of the paper for validation of the proposed cost model.

The Property of Learning effect based on Delayed Software S-Shaped Reliability Model using Finite NHPP Software Cost Model

Software testing in the debugging process is more efficient if it knows, in advance, to reduce costs in terms of changes in the software reliability and testing costs. In this process, essential items for software development are the reliability, cost, and consideration of release time. In this paper, the software reliability growth cost model based on Non-Homogenous Poisson Process (NHPP) about the property of learning effect for delayed software s-shaped reliability model was proposed, that was considered the actual number of faults removed in the software operation period after release time. Then discuss the relationship between release time and software testing-effort for determine the optimal release time so that can minimize the cost of software development and get more profit. Finally, according to some empirical studies, directly explain the effect of different parameters about the optimal software release time during testing process.

Application of multi attribute utility theory in multiple releases of software

One of the important applications of software reliability models is the determination of software release time. Most of the existing studies on this topic use models based on non homogeneous Poisson process with a bounded mean value function. Multi up gradation based software reliability growth model is developed for successive release modelling and analysis. Based on this model, maximum fault removal for upgraded software and optimal release time of upgraded software are investigated as well. This paper proposes a new practical method for determining when to stop software testing considering failure intensity and cost as two factors simultaneously. This issue has been widely known as the optimal release problem of software product. The proposed new decision model based on multi-attribute utility analysis is tested on the real world data sets. In addition, the proposed decision model can help companies to make a rational decision on the optimal timing of the software.

Release time problem with multiple constraints

Quality of software system generally depends on how much time testing takes and what testing methodologies are used. One attribute of quality is reliability which can be increased by removing more faults from the software and this can be done by spending more time on testing. However, spending more time on testing will increase cost of the software development process. On the other hand, if testing time is too short, testing cost of software may be reduced but it will increase the chance of getting unreliable software and customers may not take higher risk of buying unreliable software. Highly competitive market conditions have forced developers to offer highly reliable products to the users. Software warranty is one such indicator used by the users to judge its reliability with the perception that a longer warranty period indicates higher reliability. Software warranty is a tool which provides assurance about the quality. Warranty cost may be reduced by providing more reliable product. Therefore software reliability, testing, warranty period and cost needs to be considered jointly. In this paper, we propose a new method to estimate the optimal software release time of a software with warranty under imperfect debugging environment by using Multi Attribute Utility Theory. More precisely, three significant attributes, namely Reliability, Cost and Detection rate indicator are used to determine the optimal release time of software under warranty. The proposed new decision model based on multi-attribute utility analysis is tested on the real world data set.

NONPARAMETRIC BOOTSTRAP INTERVAL ESTIMATION OF SOFTWARE RELIABILITY AND ITS APPLICATION TO AN OPTIMAL RELEASE PROBLEM BASED ON A DISCRETIZED MODEL

We discuss a simulation-based interval estimation method of software reliability and cost-optimal software release time based on a nonparametric bootstrap method via a discretized software reliability growth model. In general, it is very difficult to derive probability distributions of model parameters, software reliability assessment measures, and optimal software release time analytically even if we assume an asymptotic theory assuming a large number of samples. The bootstrap method overcomes the problem above by obtaining the probability distributions of the parameter based on the simulation-based approach. This paper includes numerical examples for confirming that our bootstrap approach yields simulation-based probability distributions of model parameters, software reliability assessment measures, and cost-optimal software release time from actual software fault-count data.

A risk-reduction approach for optimal software release time determination with the delay incurred cost

Most existing research on software release time determination assumes that parameters of the software reliability model (SRM) are deterministic and the reliability estimate is accurate. In practice, however, there exists a risk that the reliability requirement cannot be guaranteed due to the parameter uncertainties in the SRM, and such risk can be as high as 50% when the mean value is used. It is necessary for the software project managers to reduce the risk to a lower level by delaying the software release, which inevitably increases the software testing costs. In order to incorporate the managers’ preferences over these two factors, a decision model based on multi-attribute utility theory (MAUT) is developed for the determination of optimal risk-reduction release time.

SOFTWARE RELEASE TIME BASED ON DIFFERENT MULTI-ATTRIBUTE UTILITY FUNCTIONS

The decision to release a software product will become an even more complex and important decision. A decision has strategic value when it has the potential for large prospective financial losses to a software manufacturer or its customers or end-users. A software release decision is a tradeoff between early release to capture the benefits of an earlier market introduction and the deferral of product release to the reliability. If a software product is released too early, the software manufacturer incurs post-release costs of later fixing failures. If a software product is released too late, the additional development cost and the opportunity cost of missing a market window could be substantial. These two attribute reliability and cost need to be combined to determine the optimal release time of software. This paper proposes a new practical method for determining when to stop software testing considering reliability and cost as two factors simultaneously. The proposed new decision model is based on three different weighted combination of utility function in Multi-attribute utility theory.

Confidence Interval Estimation of Software Reliability Growth Models based on Ohba’s Inflection S-shaped Model

Software reliability growth models with confidence intervals (SRGMs) are often utilized in software industry in that they provide useful information for software developers to decide the optimal software release time and to refine the quality of software testing tasks. Most SRGMs, nonetheless, do not have transparent explanations for the variance estimation of cumulative software errors. They might not be effective in deducing the confidence interval regarding the mean value function. In such cases, software developers cannot estimate the possible risk variation of software system by using the randomness of mean value function, and it might debase the practicability of applications. In this paper, we utilize Ohba’s Inflection Sshaped model to build the SRGM with confidence intervals that can assist the software developers in determining the optimal release time.