Total Software Cost Research Articles

Optimal software testing-resource allocation with operational profile: computational aspects

Software testing-resource allocation plays a significant role in software project management. During the last two decades, a number of software-resource allocation problems have been formulated from various points of view, by taking account of several optimization criteria with constraints. First, we consider three optimization problems with constraints in a combination of expected total software cost, cumulative software testing effort and desired software reliability level. Especially, we focus on the operational profile of a software product and formulate rather different software testing-resource allocation problems from the existing ones. The optimization algorithms to determine the software testing resource for each software component are given by means of nonlinear programming. Next, we consider a statistical estimation problem of the optimal software testing-resource allocation, where a simulation-based parametric bootstrap method is applied to obtain not only the confidence interval, but also the higher moments of an estimator of the optimal software testing effort for each software component. In simulation experiments, we give an illustrative example on how to evaluate the uncertainty of the estimator of the optimal software testing-effort allocation.

Software Reliability and Cost Analysis Considering Service User for Cloud with Big Data

At present, the cloud computing with big data is known as a next-generation software service paradigm. However, the effective methods of software reliability analysis considering the big data and cloud computing have been only few presented. In particular, it is important to consider the optimal data partitioning in terms of cloud computing with big data. Considering the cloud computing with big data, it will be useful for the software managers to estimate the total software cost in order to make allocations the optimal data area to the cloud user. We propose the method of component-oriented reliability assessment based on neural network in order to the optimal data partitioning for cloud computing with big data in this paper. Moreover, we propose the method of system-wide reliability assessment based on the jump diffusion process model considering the big data on cloud computing. Furthermore, we propose the optimal maintenance problem based on the jump diffusion model. Considering the contract cost for the maximum number of subscriber as the cloud user, we find the optimum maintenance time by minimizing the total software cost.

The Impacts of Test Automation on Software's Cost, Quality and Time to Market

In spite of the availability of most proficient quality assurance teams and tools, software testing has always been a time-consuming task. Thus test automation is being profoundly practiced in most of the software industries to leverage the total development time. Although the test automation has its own advantages and disadvantages and it influences various other development phases, the higher management is particularly interested in reckoning its effects on total software's cost, quality and time. In this paper, we have tried to ascertain some of the critical factors related to test automation and cost/return of/from automation. As automation is itself a pricy activity, it requires development effort and significant time, we have attempted to enumerate test automation's impacts on software's cost, time and quality on three different softwares. The results of our experiments clearly show the positive effects of test automation on cost, quality and time to market of the software.

Multi-Attribute Utility Theory for Estimation of Optimal Release Time and Change-Point

Existing optimal software release problems have been discussed by using an evaluation criterion such as cost, reliability, delivery. When we use the methods by those evaluation criteria, the optimal release time is determined by an evaluation criterion. However, it is more realistic that we determine the optimal release time with multiple attributes. Therefore, in this study, we estimate the optimal release time by using multi-attribute utility theory (MAUT). Since MAUT is one of utility theories, we can estimate an optimal release time and change-point from the perspective of utility by maximizing the multi-attribute utility function. Especially, we consider the both of two attributes: cost and reliability. Then, we apply a software reliability growth model (SRGM) with change-point to represent the cost and reliability attributes. Concretely, we use an exponential SRGM with change-point. That is, we can estimate not only the optimal release time but also change-point. Finally, we show numerical examples by using actual data sets. Especially, we check the behavior of the optimal release time, change-point, total software cost and utility.

A Review on Software Maintenance Issues and How to Reduce Maintenance Efforts

Software Maintenance and evolution are identifying by their huge cost and slow speed of implementation. Survey showed that around 60% of the maintenance effort was on the total cost of software. But after delivering the software to the client, the maintenance work begins. This paper suggests some issues and problems faced by software maintenance process. There are some issues of software maintenance i.e.: database size, system age, maintenance budget, system size, staff size or restructuring for change. This paper presents several ways to reduce cost and efforts involved in software maintenance. Software maintenance costs can be reduced significantly if the software architecture is well defined, clearly documented, and creates an environment that promotes design consistency through the use of guidelines and testing quality.

Regression Testing Cost Reduction Suite

The estimated cost of software maintenance exceeds 70 percent of total software costs [1], and large portion of this maintenance expenses is devoted to regression testing. Regression testing is an expensive and frequently executed maintenance activity used to revalidate the modified software. Any reduction in the cost of regression testing would help to reduce the software maintenance cost. Test suites once developed are reused and updated frequently as the software evolves. As a result, some test cases in the test suite may become redundant when the software is modified over time since the requirements covered by them are also covered by other test cases. Due to the resource and time constraints for re-executing large test suites, it is important to develop techniques to minimize available test suites by removing redundant test cases. In general, the test suite minimization problem is NP complete. This paper focuses on proposing an effective approach for reducing the cost of regression testing process. The proposed approach is applied on real-time case study. It was found that the reduction in cost of regression testing for each regression testing cycle is ranging highly improved in the case of programs containing high number of selected statements which in turn maximize the benefits of using it in regression testing of complex software systems. The reduction in the regression test suite size will reduce the effort and time required by the testing teams to execute the regression test suite. Since regression testing is done more frequently in software maintenance phase, the overall software maintenance cost can be reduced considerably by applying the proposed approach.

Modeling optimal release policy under fuzzy paradigm in imperfect debugging environment

ContextIn this study, a software optimal release time with cost-reliability criteria has been discussed in an imperfect debugging environment. ObjectiveThe motive of this study is to model uncertainty involved in estimated parameters of the software reliability growth model (SRGM). MethodInitially the reliability parameters of SRGM are estimated using least square estimation (LSE). Considering the uncertainty involved in the estimated parameters due to human behavior being subjective in nature and the dynamism of the testing environment, the concept of fuzzy set theory is applicable in developing SRGM. Finally, using arithmetic operations on fuzzy numbers, the reliability and total software cost are calculated. ResultsVarious reliability measures have been computed at different levels of uncertainties, and a comparison has been made with the existing results reported in the literature. ConclusionIt is evident from the results that a better prediction of reliability measures, namely, software reliability and total software cost can be made under the fuzzy paradigm.

An Improved, Efficient and Cost Effective Software Inspection Meeting Process

Normally, the inspection process is seemed to be just finding defects in software during software development process lifecycle. Software inspection is considered as a most cost effective technique, but if these defects are not properly corrected or handled it would cost you more than double later in the project. This paper focus on the last phase of inspection meeting process showing the importance of Follow-Up Stage in software inspection meeting process. This paper also suggests a set of activities that should be performed during the Rework and Follow-Up Stages so to get inspection meeting results productive and efficient. In this paper we focus on the over the shoulder reviews so to ensure the software quality having less impact on the total software cost.

Software Testing Model for Quality

Software testing plays an important role during the software developing period. Any saving on software test will significantly reduce the total cost of software. The key point of this paper is to build a software testing process with the cost control management and to make tradeoffs between the software quality and the software cost. Typical software testing model are analysed and compared. A Quality controlled 3-D testing model is introduced. The model combined with software test process, software quality cost and the testing type. The computational formula is defined to calculate software quality cost. A software quality balance law is introduced to balance control and failure cost. By adjusting software testing method and strategy, organization can reach the objective of the best balance between software quality and the software cost. The result shows an optimistic point that will prove the accurate of the model and the law introduced.

A Study of When to Release a Software Product from the Perspective of Software Reliability Models

If a software product with a significant number of defects is released too early to users, the software manufacturer will incur post-release costs of fixing the faults. If a product is released too late, the additional development cost and the risk of missing a market window could be substantial. Software Reliability Growth Models (SRGMs) can capture the quantitative aspects of testing and are used to estimate software release time. From a cost-benefit viewpoint, SRGMs aid developers to decide the optimal release time of the software product by providing effective approaches to minimising the expected total software system cost. This paper helps answer the question of when to stop testing a software product by presenting the perspectives from a study of cost models. The study focuses on aspects of the relationship between development cost and schedule delivery of the software product and the total software cost including the risk costs, such as the penalty cost incurred due to late delivery of software product and the cost of fixing a fault during the warranty period.We also investigate various software release policies, for example, policies based on the dual constraints of cost and reliability.

Laptops and Inspired Writing

Can daily access to laptop computers help students become better writers? Are such programs affordable? Evidence from the Inspired Writing program in Littleton Public Schools, Colorado, USA, provides a resounding yes to both questions. The program employs student netbooks, open‐source software, cloud computing, and social media to help students in grades 5 through 10 develop their skills and identities as writers, all at a total hardware and software cost of less than $280 per student. Students use these tools to learn about diverse genres and write in them for authentic purposes and audiences.

The Comparative Study of Software Optimal Release Time Based on Burr Distribution

It is great practical interest to decide when to stop testing a software system in development phase and transfer it to the user. This problem is called as the optimal software release policies. In this research, it was studied about this software release problem. Because of the possibility of introducing new faults when correcting or modifying the software, infinite failure NHPP models presented and propose an optimal release policies of the life distribution applied Burr distribution which makes out efficiency application for software reliability. In this paper, discuss optimal software release policies which minimize a total software cost of development and maintenance under the constraint of satisfying a software reliability requirement. In a numerical example, after trend test applied and estimated the parameters using maximum likelihood estimation of inter-failure time data (Lyu, M. R. [13]), make out estimating software optimal release time.

지수 및 비지수족 분포 모형에 근거한 소프트웨어 최적방출시기에 관한 비교 연구

본 연구에서는 소프트웨어 제품을 개발하여 테스팅을 거친 후 사용자에게 인도하는 시기를 결정하는 방출문제에 대하여 연구 하였다. 방출문제의 분포는 소프트웨어의 결함을 제거하거나 수정 작업 중에도 새로운 결함이 발생될 가능성이 있는 무한고장수를 가진 비동질적인 포아송 과정에 기초하였다. 수명분포는 지수 족 분포와 비지수족 분포를 이용한 최적 방출시기에 관한 문제를 비교 제시하였다. 이러한 지수 및 비지수분포에 근거하여 소프트웨어 요구 신뢰도를 만족시키고 소프트웨어 개발 및 유지 총비용을 최소화 시키는 최적 소프트웨어 방출 정책에 대하여 논의 되었다. 본 논문의 수치적인 예에서는 고장 간격 시간 자료를 적용하고 모수추정 방법은 최우추정법을 이용하고 추세분석을 통하여 자료의 효율성을 입증한 후 최적 방출시기를 추정하였다. Decision problem called an optimal release policies, after testing a software system in development phase and transfer it to the user, is studied. The applied model of release time exploited infinite non-homogeneous Poisson process. This infinite non-homogeneous Poisson process is a model which reflects the possibility of introducing new faults when correcting or modifying the software. The failure life-cycle distribution used exponential and non-exponential family which has various intensity. Thus, software release policies which minimize a total average software cost of development and maintenance under the constraint of satisfying a software reliability requirement becomes an optimal release policies. In a numerical example, after trend test applied and estimated the parameters using maximum likelihood estimation of inter-failure time data, estimated software optimal release time.

강도함수 특성에 근거한 소프트웨어 최적 방출시기에 관한 비교 연구

Abstract In this paper, we were researched decision problem called an optimal release policies after testing a software system in development phase and transferring it to the user. The applied model of release time exploited infinite failure non-homogeneous Poisson process This infinite failure non-homogeneous Poisson process is a model which reflects the possibility of introducing new faults when correcting or modifying the software. The intensity function used Gompertz, Preto and Log-logstic pattern which has the efficient various property. Thus, optimal software release policies which minimize a total average software cost of development and maintenance under the constraint of satisfying a software reliability requirement becomes an optimal release policies. In a numerical example, after trend test applied and estimated the parameters using maximum likelihood estimation of inter-failure time data, estimated software optimal release time. Key Words : Software Release Policies, Infinite Non-Homogeneous Poisson Process, Intensity Function Property

와이블 분포 특성에 근거한 소프트웨어 최적 방출시기에 관한 비교 연구

본 연구에서는 소프트웨어 제품을 개발하여 테스팅을 거친 후 사용자에게 인도하는 시기를 결정하는 방출문제에 대하여 연구하였다. 인도시기에 관한 모형은 무한 고장수에 의존하는 비동질적인 포아송 과정을 적용하였다. 이러한 포아송 과정은 소프트웨어의 결함을 제거하거나 수정 작업 중에도 새로운 결함이 발생될 가능성을 반영하는 모형이다. 고장발생 수명분포는 여러 분포들을 적합시키는데 효율적인 특성을 가진 와이블분포를 이용하였다. 따라서 소프트웨어 요구 신뢰도를 만족시키고 소프트웨어 개발 및 유지 총비용을 최소화시키는 방출시간이 최적 소프트웨어 방출 정책이 된다. 본 논문의 수치적인 예에서는 고장 간격 시간 자료를 적용하고 모수추정 방법은 최우추정법과 추세분석을 통하여 자료의 효율성을 입증한 후 최적 방출시기를 추정하였다. In this paper, we were researched decision problem called an optimal release policies after testing a software system in development phase and transferring it to the user. The applied model of release time exploited infinite failure non-homogeneous Poisson process This infinite failure non-homogeneous Poisson process is a model which reflects the possibility of introducing new faults when correcting or modifying the software. The failure life-cycle distribution used the Weibull distribution which has the efficient various property which has the place efficient quality. Thus, optimal software release policies which minimize a total average software cost of development and maintenance under the constraint of satisfying a software reliability requirement becomes an optimal release policies. In a numerical example, after trend test applied and estimated the parameters using maximum likelihood estimation of inter-failure time data, estimated software optimal release time.

Bayesian Optimal Release Time Based on Inflection S-Shaped Software Reliability Growth Model

The inflection S-shaped software reliability growth model (SRGM) proposed by Ohba (1984) is one of the well- known SRGMs. This paper deals with the optimal software release problem with regard to the expected software cost under this model based on the Bayesian approach. To reflect the effect of the learning experience for the updated software system, we consider several improvement factors to adjust the values of parameters characterizing the inflection S-shaped SRGM. Appropriate prior distributions are assumed for such factors and the expected total software cost is formulated. The optimal release time is shown to be finite and uniquely determined. Because of the flexibility of prior distributions, the proposed Bayesian methods may be applied in many different situations. Numerical results are presented on the basis of the real data.

A flexible stochastic differential equation model in distributed development environment

In recent years, the dependence on a computer system has become large in our social life. Especially, a software development environment has been changing into distributed development environment interconnected with work-stations. Therefore, it becomes more difficult for software developers to produce highly reliable software systems efficiently, because of the more diversified and complicated software requirements. Also, in the software development process, the software testing-cost occupies more than a half of the total development cost. In this paper, we derive a flexible stochastic differential equation model describing a fault-detection process during the system testing phase of the distributed development environment by applying a mathematical technique of stochastic differential equations of an It o ˆ type. Moreover, we discuss optimal software release problems based on the reusable rate of software components minimizing the expected total software cost, and also minimizing the cost with satisfying a software reliability requirement based on the coefficient of variation.

Bayesian Approach to Optimal Release Policy of Software System

In this paper, we propose a new software reliability growth model which is the mixture of two exponential reliability growth models, one of which has the reliability growth and the other one does not have the reliability growth after the software is released upon completion of testing phase. The mixture of two such models is characterized by a weighted factor p, which is the proportion of reliability growth part within the model. Firstly, this paper discusses an optimal software release problem with regard to the expected total software cost incurred during the warranty period under the proposed software reliability growth model, which generalizes Kimura, Toyota and Yamada's (1999) model with consideration of the weighted factor. The second main purpose of this paper is to apply the Bayesian approach to the optimal software release policy by assuming the prior distributions for the unknown parameters contained in the proposed software reliability growth model. Some numerical examples are presented for the purpose of comparing the optimal software release policies depending on the choice of parameters by the non-Bayesian and Bayesian methods.

Determining the optimal software warranty period under various operational circumstances

Purpose – To determine the optimal software warranty period in continuous and discrete circumstances where the difference between the software testing environment and the operational environment can be characterised by an environment factor.Design/methodology/approach – Software reliability models based on continuous and discrete time non‐homogeneous Poisson processes are assumed to describe the failure occurrence phenomena under both environments. Based on the idea of accelerated life testing for hardware products, the operational profile of the software is modeled, and the total expected software cost incurred in both testing and operational phases is formulated.Findings – Under a milder condition, the optimal warranty period which minimizes the total software cost is derived analytically.Originality/value – This paper introduces the operational profile of software to model the difference between the testing environment and the operational environment.

On the economics of requirements-based test case prioritization

Software testing is a strenuous and expensive process. At least 50% of the total software cost is spent on testing activities [12]. Companies are often faced with time and resource constraints that limit their ability to effectively complete testing efforts. Companies generally save suites for reuse; test suite reuse accounts for almost half of the maintenance cost [9]. As the product goes thru several versions, executing all the test cases in a test suite can be expensive [9]. Prioritization of test cases can be cost effective when the time allocated to complete testing is limited [9]. Test case prioritization (TCP) involves the explicit planning of the execution of test cases in a specific order and is shown to improve the rate of fault detection [3, 9]. The current software TCP techniques are primarily coverage-based (statement, branch or other coverage) [3,9]. Coverage-based white-box prioritization techniques are most applicable for regression testing at the unit level and are harder to apply on complex systems [2]. These techniques require testers to read and understand the code, which can be time consuming [2], and may assume that all faults are equally severe.