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testing coverage based NHPP software reliability growth modeling with testing effort and change-point

INTERNATIONAL JOURNAL OF SYSTEM ASSURANCE ENGINEERING AND MANAGEMENT 2024年第11期15卷 5157-5166页

作者： Aggarwal, Anu Kumar, Sudeep Gupta, Ritu Univ Delhi Dept Operat Res Delhi India Amity Univ Uttar Pradesh AIAS Noida India Manipal Acad Higher Educ T A Pai Management Inst Manipal India

This paper investigates a software reliability growth model based on non-homogeneous Poisson process that includes coverage testing and change-points. The model integrate effort spent into a model to evaluate software reliability based on testing coverage. The amount of testing effort spent follows the Weibull distribution, while the amount of coverage is modeled by logistic, delayed S-shaped and exponential functions. Additionally, we look into the cost requirement-based software release time for exponential functions with a reliability constraint. We introduce the genetic algorithm, which is a powerful tool for dealing with search and optimization issues. For the purpose of testing the model's goodness of fit, two real failure datasets are used, and the model's performance is analyzed based on goodness-of-fit metrics. By comparing the proposed model to perfect debugging models that have been described in the literature, it is demonstrated that the proposed model demonstrates notable advancements in this regard. The results of our analysis indicate that a software reliability estimation model should include change-points in a testing process if they exist.

关键词： NHPP testing coverage Software reliability growth model testing effort function (TEF) Change point

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testing coverage-based software modeling incorporating random effect with change point and its release

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INTELLIGENT DECISION TECHNOLOGIES-NETHERLANDS 2023年第3期17卷 839-851页

作者： Bibyan, Ritu Anand, Sameer Aggarwal, Anu Gputa Kaur, Gurjeet Univ Delhi Dept Operat Res Delhi India

The use of computers has been increasingly prevalent in our social lives in recent years. As a result, software engineers must create trustworthy software systems. Companies often release improved versions of the core program due to the constant demand and growing competition in the software field. A variety of growth models have been created to track and measure reliability by software managers and engineers. In the testing phase, the fault content and size of the software system increase, and consequently, the fault content found and eliminated during each debugging process decreases in comparison to the fault content present at the initial stage. In this scenario, we can consider the software fault detection process to be stochastic. The fault detection process is expressed in terms of testing coverage with random effects. In this study, we construct a testing coverage-based software model incorporating random effect with change point. We have used different testing coverage functions such as Exponential and Delayed S-shaped to study the effect of randomness. Further, multi-release planning for the proposed model has been studied and validated on the real-time failure dataset from Tandem Computers with four releases. Different performance measures and goodness-of-fit have been presented using a graphical representation.

关键词： Software reliability growth model testing coverage change point stochastic differential equation multi-release model

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NHPP-Based testing coverage model with Fault Removal Efficiency and Error Generation

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INTERNATIONAL JOURNAL OF RELIABILITY QUALITY AND SAFETY ENGINEERING 2025年第1期32卷

作者： Iqbal, Javaid Nazir, Rabia Rasool, Tariq Univ Kashmir Dept Comp Sci Srinagar 190006 India Chandigarh Univ Univ Inst Comp Mohali 140413 Punjab India

This paper introduces an innovative approach aimed at enhancing software reliability by integrating testing coverage within a nonhomogeneous Poisson process (NHPP). The reliability of software holds paramount significance for both developers and users, hinging on precise reliability estimations. In this paper, three real-world datasets are used to examine goodness-of-fit of the proposed model and the performance is compared with 11 other existing NHPP models. The performance of all the models is evaluated using five goodness-of-fit criteria including mean square error (MSE), Akaike's information criterion (AIC), Bayesian information criterion (BIC), predictive risk ratio (PRR) and Pham's criterion (PC). The results reveal that, when it comes to predictive power and goodness-of-fit, our proposed model surpasses the other models.

关键词： testing coverage fault removal efficiency error generation imperfect debugging NHPP SRGM

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Modeling the impact of noise and uncertain operational environment on software release decisions considering testing coverage-based SRGM

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INTELLIGENT DECISION TECHNOLOGIES-NETHERLANDS 2024年第3期18卷 2339-2352页

作者： Anand, Sameer Jaiswal, Ajay Verma, Vibha Singh, Atul Univ Delhi Dept Operat Res Delhi India Univ Delhi Campus Open Learning Delhi India Jaipuria Sch Business Ghaziabad 201014 India Univ Delhi Ramjas Coll Dept Stat Delhi India

The operational environment of software differs from the debugging environment. Therefore, the study explores the impact of irregular consumption by diverse users on the development cost of software, reliability of software, and release decisions. To accomplish this, a release model has been formulated considering logistic testing coverage-based reliability growth model built as a stochastic process including the error generation. The stochastic nature has been captured by considering the noise factor due to irregular fluctuations occurring during testing while usage uncertainty has been captured by introducing a constant parameter in the cost function of the operational phase. It is assumed that the testing phase cost is affected by the noise and the operation phase cost is affected by the severity of noise which is the result of uncertain usage by users. The model was evaluated against a real failure dataset. The release model creates a trade-off between software development cost, release timing, and reliability aspirations. This study contributes to software reliability literature and provides insights to practitioners to make software release decisions. The sensitivity analysis results give information about various aspects during the operational phase that affect the overall development cost.

关键词： testing coverage noise-based SRGM error generation operational phase release planning environmental factor sensitivity analysis

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Multi-release testing coverage-based SRGM considering error generation and change-point incorporating the random effect

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INTERNATIONAL JOURNAL OF SYSTEM ASSURANCE ENGINEERING AND MANAGEMENT 2023年第5期14卷 1877-1887页

作者： Bibyan, Ritu Anand, Sameer Aggarwal, Anu G. G. Tandon, Abhishek Univ Delhi Dept Operat Res New Delhi 110007 India

The most essential step during the development of the software is the testing procedure which makes the software dependable and efficient. During this procedure, the observation and rectification of the faults play a significant role in increasing the reliability of the software. Various Software Reliability growth models (SRGMs) with multiple assumptions were presented by various researchers to study the software's reliability. It is well known that the fault observation/removal rate may get affected by irregular factors causing arbitrary effects. In this study, we aim to capture this irregular variation in fault observation/removal rate by expressing it in terms of testing coverage. The fault observation/removal process has been assumed as a stochastic process and modeled it using an Ito type of stochastic differential equation. testing coverage enables software designers to check the software's excellence and to see if any extra efforts are required to enhance reliability. In this paper, we have developed an SRGM based on testing coverage by introducing the concept of chang-epoint, error generation, and fault detection rate with irregular fluctuations. The error generation implies that during the testing procedure faults are not disclosed entirely and more faults get introduced. Later on, we focused on the idea of multi-release by considering four releases. We have estimated the parameters of the model by using the fault dataset for consecutive releases of Tandem Computers and validated the performance by evaluating the various goodness-of-fit criteria.

关键词： SRGMs Error generation Stochastic differential equation testing coverage Multi-release modeling

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Software reliability testing coverage model using feed-forward back propagation neural network

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INTERNATIONAL JOURNAL OF MODELLING IDENTIFICATION AND CONTROL 2023年第2期43卷 126-133页

作者： Bibyan, Ritu Anand, Sameer Jaiswal, Ajay Aggarwal, Anu Gupta Univ Delhi Dept Operat Res Delhi 110007 India Univ Delhi Shaheed Sukhdev Coll Business Studies Delhi 110089 India Univ Delhi Coll Vocat Studies Delhi 110017 India Univ Delhi Dept Operat Res New Delhi 110007 India

The paper presents software reliability growth model (SRGM) with testing coverage which covers both detection as well as correction process under imperfect debugging. The estimation is done using feed forward back propagation artificial neural network (ANN). Many researchers have studied the importance of modelling fault detection instead of modelling fault correction. We have proposed generalised testing coverage model by adopting different testing coverage for both the processes. We have also compared proposed model with existing traditional models based on three failure datasets. Different performance criteria like goodness of fit, accuracy of the model, mean square error (MSE), and coefficient of determination (R-2) are evaluated for the datasets. The comparison results shows that the model proposed in this paper provides more efficient accuracy than the existing traditional models.

关键词： software reliability testing coverage machine learning feed-forward back-propagation neural network

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Modelling of NHPP Based Software Reliability Growth Model from the Perspective of testing coverage, Error Propagation and Fault Withdrawal Efficiency

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INTERNATIONAL JOURNAL OF RELIABILITY QUALITY AND SAFETY ENGINEERING 2022年第6期29卷 2250013-2250013页

作者： Khurshid, Shozab Iqbal, Javaid Malik, Ishfaq Ahmad Yousuf, Basrah Univ Kashmir Dept Comp Sci Srinagar 190006 Jammu & Kashmir India Univ Kashmir Dept Math Srinagar 190006 India

This paper presents a software reliability growth model framework modeled from a non-homogenous poisson process (NHPP). Invariably, software testing continues to be a paramount measure for validating the standard of software. Test coverage measures appraise and estimate the proportion and gradation of testing in software. Therefore, presenting a correct picture of the test coverage becomes a prime requisite to guarantee software reliability. As an enhancement over the existing models, the proposed model integrates testing coverage (TC), error propagation, and fault withdrawal efficiency while keeping the number of parameters restrained to make the framework more reliable for parameter estimation. A relative analysis to assess the efficacy of the proposed model and some existing models has been carried out on the failure data obtained from three realworld software applications using six comparison criteria. Finally, the weighted criteria rank method has been used to rank the models and assess their performance. In addition, sensitivity analysis has been carried out to demonstrate the effect of the parameters of the proposed model on the mean value function.

关键词： testing coverage software reliability growth model SRGM error propagation fault removal efficiency non-homogenous poisson process NHPP weighted criteria rank

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Multi-release software model based on testing coverage incorporating random effect (SDE)

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METHODSX 2023年 10卷 102076页

作者： Bibyan, Ritu Anand, Sameer Aggarwal, Anu G. Kaur, Gurjeet Univ Delhi Dept Operat Res New Delhi India Univ Delhi Shaheed Sukhdev Coll Business Studies New Delhi India

In the past, various Software Reliability Growth Models (SRGMs) have been proposed using dif-ferent parameters to improve software worthiness. testing coverage is one such parameter that has been studied in numerous models of software in the past and it has proved its influence on the reliability models. To sustain themselves in the market, software firms keep upgrading their soft-ware with new features or enhancements by rectifying previously reported faults. Also, there is an impact of the random effect on testing coverage during both the testing and operational phase. In this paper, we have proposed a Software reliability growth model based on testing coverage with random effect along with imperfect debugging. Later, the multi-release problem is presented for the proposed model. The proposed model is validated on the dataset from Tandem Computers. The results for each release of the models have been discussed based on the different performance criteria. The numerical results illustrate that models fit the failure data *** dot The random effect in the testing coverage rate is handled using Stochastic Differential Equa-tions (SDE).center dot Three testing coverage functions used are Exponential, Weibull, and *** dot Four Releases of the software model has been presented.

关键词： testing coverage Software reliability growth models Stochastic Differential Equation Multi-release software Imperfect debugging Non-homogeneous poisson process (NHPP) Method name testing coverage incorporating sde with multi release SRGM

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Correlation of population mortality of COVID-19 and testing coverage: a comparison among 36 OECD countries

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EPIDEMIOLOGY AND INFECTION 2020年 149卷 e1-e1页

作者： Wei, C. Lee, C. C. Hsu, T. C. Hsu, W. T. Chan, C. C. Chen, S. C. Chen, C. J. Harvard Med Sch Boston MA 02115 USA Natl Taiwan Univ Hosp Dept Emergency Med Taipei Taiwan Natl Taiwan Univ Hosp Ctr Intelligent Healthcare Taipei Taiwan Natl Taiwan Univ Hosp Hlth Data Sci Res Grp Taipei Taiwan Harvard TH Chan Sch Publ Hlth Dept Epidemiol Boston MA USA Natl Taiwan Univ Coll Publ Hlth Inst Environm & Occupat Hlth Sci Taipei Taiwan Acad Sinica Genom Res Ctr Taipei Taiwan

Although testing is widely regarded as critical to fighting the COVID-19 pandemic, what measure and level of testing best reflects successful infection control remains unresolved. Our aim was to compare the sensitivity of two testing metrics - population testing number and testing coverage - to population mortality outcomes and identify a benchmark for testing adequacy. We aggregated publicly available data through 12 April on testing and outcomes related to COVID-19 across 36 OECD (Organization for Economic Development) countries and Taiwan. Spearman correlation coefficients were calculated between the aforementioned metrics and following outcome measures: deaths per 1 million people, case fatality rate and case proportion of critical illness. Fractional polynomials were used to generate scatter plots to model the relationship between the testing metrics and outcomes. We found that testing coverage, but not population testing number, was highly correlated with population mortality (r(s) = -0.79, P = 5.975 x 10(-9) vs. r(s) = -0.3, P = 0.05) and case fatality rate (r(s) = -0.67, P = 9.067 x 10(-6) vs. r(s) = -0.21, P = 0.20). A testing coverage threshold of 15-45 signified adequate testing: below 15, testing coverage was associated with exponentially increasing population mortality;above 45, increased testing did not yield significant incremental mortality benefit. Taken together, testing coverage was better than population testing number in explaining country performance and can serve as an early and sensitive indicator of testing adequacy and disease burden.

关键词： COVID-19 SARS-CoV-2 testing coverage

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Software Reliability Growth Model for Imperfect Debugging Process Considering testing-Effort and testing coverage

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Transactions of Nanjing University of Aeronautics and Astronautics 2018年第3期35卷 455-463页

作者： Zang Sicong Pi Dechang College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics

Because of the inevitable debugging lag,imperfect debugging process is used to replace perfect debugging process in the analysis of software reliability growth *** neither testing-effort nor testing coverage can describe software reliability for imperfect debugging completely,by hybridizing testing-effort with testing coverage under imperfect debugging,this paper proposes a new model named *** the assumption that the number of faults is proportional to the current number of detected faults,this model combines generalized modified Weibull(GMW)testing-effort function with logistic(LO)testing coverage function,and inherits GMW's amazing flexibility and LO's high fitting ***,the fitting accuracy and predictive power are verified by two series of experiments and we can draw a conclusion that our model fits the actual failure data better and predicts the software future behavior better than other ten traditional models,which only consider one or two points of testing-effort,testing coverage and imperfect debugging.

关键词： software reliability testing-effort testing coverage imperfect debugging(ID) non-homogeneous Poisson process(NHPP)

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