scholarly journals Testing Resource based Optimal Release Policy for Software System Incorporating Fault Reduction Factor and Change point

2019 ◽  
Vol 8 (4) ◽  
pp. 1909-1920
Keyword(s):  
Change Point ◽  
Numerical Study ◽  
Reduction Factor ◽  
Performance Criteria ◽  
Model Parameters ◽  
Software System ◽  
Cost Component ◽  
Time Line ◽  
Testing Effort ◽  
Fault Removal

In today’s competitive scenario, it is essential for software developers to perform rigorous testing. It helps them to satisfy the demand for reliable software systems. Various external and internal factors like human expertise, fault dependency, code complexity, dynamic approaches etc. affect the process of fault removal. Hence, along the time-line fault removal rate may change. The point on time-line beyond which rates are altered is termed as the change point. Also in many practical situations, the number of failures experienced may not coincide with the number of faults removed from the system. This ratio is computed by Fault Reduction Factor (FRF). Here, we have proposed testing effort based model considering effort-dependent FRF with and without change point for gauging the failure pattern of a software system. The FRF has been modelled by logistic curve. The developed models have been verified using real-life software fault datasets. Model parameters are estimated and various performance criteria are employed to check the goodness of fit. Later, we have developed a software cost model to determine the optimal Release testing effort that minimizes total expected cost of fault removal during testing phase and operational phase of software life cycle subject to a reliability constraint. A numerical study has been also taken to demonstrate the results. Cost sensitivity analysis has been carried out to identify the crucial cost component and role of each cost component on optimal testing effort and overall cost of development.

A SOFTWARE RELIABILITY GROWTH MODEL WITH TESTING EFFORT DEPENDENT LEARNING FUNCTION FOR DISTRIBUTED SYSTEMS

2004 ◽  
Vol 11 (04) ◽  
pp. 365-377 ◽  
Author(s):  
P. K. KAPUR ◽  
D. N. GOSWAMI ◽  
AMIT GUPTA
Keyword(s):  
Software Reliability ◽  
Goodness Of Fit ◽  
Software Process Improvement ◽  
Software System ◽  
Reliability Growth ◽  
Development Environment ◽  
Testing Effort ◽  
Growth Phenomenon ◽  
Software Reliability Growth ◽  
Fault Removal

Effective software process improvement will not start until management insists that product development work be planned and properly managed. This becomes even more challenging in an increasing number of major system developments made up from distributed sub-system software projects. These sub-systems are integrated and validated to provide the final system and product release. The need is growing to estimate, risk assess, plan and manage the development of these distributed sub-systems and the final full system release. In this paper, an attempt has been made to model the software reliability growth phenomenon with testing effort in a distributed development environment. Proposed Non Homogeneous Poisson Process (NHPP) based model assumes that the software system consists of a finite number of reused and newly developed sub-systems. The reused sub-systems do not consider the effect of severity of the faults on the software reliability growth phenomenon because they stabilize over a period of time i.e., the growth is uniform whereas, the newly developed sub-system do consider that. Fault removal phenomenon for reused and newly developed sub-systems have been modeled separately and is summed up to get the total fault removal phenomenon of the software system. The applicability of our model is shown by validating it on software failure data sets obtained from different real software development projects. The comparisons with established models in terms of goodness of fit, the Akaike Information Criterion (AIC), Mean of Squared Errors (MSE) have been presented.

scholarly journals Testing effort based software reliability assessment incorporating FRF and change point

2020 ◽  
Vol 30 (3) ◽  
pp. 273-288
Author(s):  
Rajat Arora ◽  
Anu Aggarwal
Keyword(s):  
Software Reliability ◽  
Change Point ◽  
Goodness Of Fit ◽  
Removal Rate ◽  
Reduction Factor ◽  
Software Systems ◽  
Testing And Debugging ◽  
Testing Effort ◽  
Proposed Model ◽  
Software Reliability Growth

In today's World, to meet the demand of high quality and reliable software systems, it is imperative to perform comprehensive testing and debugging of the software code. The fault detection and removal rate may change over time. The time point after which the rates are changed is termed as the change point. Practically, the failure count may not coincide with the total fault count removed from the system. Their ratio is measured by Fault Reduction Factor (FRF). Here, we propose a Weibull testing effort dependent Software Reliability Growth Model with logistic FRF and change point for assessing the failure phenomenon of a software system. The models have been validated on two real software fault datasets. The parameters are estimated using Least squares and various criteria are employed to check the goodness of fit. The comparison is also facilitated with the existing models in literature to demonstrate that proposed model has better performance.

A Numerical Study of Sensitivity Coefficients for a Model of Amyloid Precursor Protein and Tubulin-Associated Unit Protein Transport and Agglomeration in Neurons at the Onset of Alzheimer's Disease

2019 ◽  
Vol 141 (3) ◽  
Author(s):  
I. A. Kuznetsov ◽  
A. V. Kuznetsov
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Amyloid Precursor Protein ◽  
Tau Protein ◽  
Protein Transport ◽  
Numerical Study ◽  
Amyloid Β ◽  
Precursor Protein ◽  
Model Parameters ◽  
In The Beginning

Modeling of intracellular processes occurring during the development of Alzheimer's disease (AD) can be instrumental in understanding the disease and can potentially contribute to finding treatments for the disease. The model of intracellular processes in AD, which we previously developed, contains a large number of parameters. To distinguish between more important and less important parameters, we performed a local sensitivity analysis of this model around the values of parameters that give the best fit with published experimental results. We show that the influence of model parameters on the total concentrations of amyloid precursor protein (APP) and tubulin-associated unit (tau) protein in the axon is reciprocal to the influence of the same parameters on the average velocities of the same proteins during their transport in the axon. The results of our analysis also suggest that in the beginning of AD the aggregation of amyloid-β and misfolded tau protein have little effect on transport of APP and tau in the axon, which suggests that early damage in AD may be reversible.

Numerical study of Zika model as a mosquito-borne virus with non-singular fractional derivative

2021 ◽  
Author(s):  
Sachin Kumar ◽  
Dia Zeidan
Keyword(s):  
Fractional Derivative ◽  
Zika Virus ◽  
Numerical Study ◽  
Asymptomatic Carrier ◽  
Virus Transmission ◽  
Model Parameters ◽  
Human Society ◽  
Sexual Interaction ◽  
Virus Model ◽  
Global Threat

Zika virus infection, which is closely related to dengue, is becoming a global threat to human society. The transmission of the Zika virus from one human to another is spread by bites of Aedes mosquitoes. Recent studies also reveal the fact that the Zika virus can be transmitted by sexual interaction. In this paper, we use the fractional derivative with Mittag–Leffler non-singular kernel to study Zika virus transmission dynamics. This fractional is also known as the Atangana–Baleanu Caputo (ABC) derivative which is employed for the resulting system of ordinary differential equations. We investigate the proposed Zika virus model by using the Legendre spectral method. The model parameters are estimated and validated numerically by investigating the effect of fractional order exponent on various cases such as Susceptible human, infected human, asymptomatic carrier, exposed human, and recovered human. Numerical results obtained with the proposed method have been compared with exact solutions, showing in all parameters a very satisfactory agreement.

scholarly journals Change Point Detection for Airborne Particulate Matter (PM2.5, PM10) by Using the Bayesian Approach

Mathematics ◽  
2019 ◽  
Vol 7 (5) ◽  
pp. 474 ◽  
Author(s):  
Muhammad Rizwan Khan ◽  
Biswajit Sarkar
Keyword(s):  
Particulate Matter ◽  
Bayesian Approach ◽  
Change Point ◽  
Airborne Particulate Matter ◽  
Change Point Detection ◽  
Model Parameters ◽  
Numerical Verification ◽  
Airborne Particulate ◽  
M 10 ◽  
The Bayesian Approach

Airborne particulate matter (PM) is a key air pollutant that affects human health adversely. Exposure to high concentrations of such particles may cause premature death, heart disease, respiratory problems, or reduced lung function. Previous work on particulate matter ( P M 2.5 and P M 10 ) was limited to specific areas. Therefore, more studies are required to investigate airborne particulate matter patterns due to their complex and varying properties, and their associated ( P M 10 and P M 2.5 ) concentrations and compositions to assess the numerical productivity of pollution control programs for air quality. Consequently, to control particulate matter pollution and to make effective plans for counter measurement, it is important to measure the efficiency and efficacy of policies applied by the Ministry of Environment. The primary purpose of this research is to construct a simulation model for the identification of a change point in particulate matter ( P M 2.5 and P M 10 ) concentration, and if it occurs in different areas of the world. The methodology is based on the Bayesian approach for the analysis of different data structures and a likelihood ratio test is used to a detect change point at unknown time (k). Real time data of particulate matter concentrations at different locations has been used for numerical verification. The model parameters before change point ( θ ) and parameters after change point ( λ ) have been critically analyzed so that the proficiency and success of environmental policies for particulate matter ( P M 2.5 and P M 10 ) concentrations can be evaluated. The main reason for using different areas is their considerably different features, i.e., environment, population densities, and transportation vehicle densities. Consequently, this study also provides insights about how well this suggested model could perform in different areas.

Numerical Study of Liquid Core Solidification in Influence of Soft Reduction Deformation on Steel Slab Continuous Casting Process

2008 ◽  
Vol 575-578 ◽  
pp. 80-86 ◽  
Author(s):  
J. Luo ◽  
Xin Lin ◽  
Yan Hong Ye ◽  
K.W. Liu
Keyword(s):  
Continuous Casting ◽  
Numerical Study ◽  
Liquid Core ◽  
Solidification Process ◽  
Casting Process ◽  
Reduction Factor ◽  
Two Dimensions ◽  
Temperature Function ◽  
Soft Reduction ◽  
Steel Slab

A two dimensions (2D) multiphase solidification model is used to study the liquid core solidification in the influence of deformation during soft reduction of continuous casting (CC). The transient transport equations (mass, momentum and enthalpy) for each phase of a thin steel slab CC are solved. Four different cases including of density-temperature function and deformation reduction factor on this CC are simulated. The solidification ending point position of liquid core, temperature, velocity and fracture of liquid and solid phases are compared. Understandings to the deformation and liquid core formation mechanism on soft reduction solidification process of CC are improved.

A Sensitivity Study of the Porcine Head Subjected to Bump Impact

2016 ◽  
Author(s):  
Kimberly A. Thompson ◽  
Adam C. Sokolow ◽  
Juliana Ivancik ◽  
Timothy G. Zhang ◽  
William H. Mermagen ◽  
...  
Keyword(s):  
Human Brain ◽  
3D Model ◽  
Porcine Model ◽  
Load Transfer ◽  
Numerical Study ◽  
Sensitivity Study ◽  
Complex Problem ◽  
Model Parameters ◽  
Skin Thickness ◽  
The Impact

Understanding load transfer to the human brain is a complex problem that has been a key subject of recent investigations [4–6]. Because the porcine is a gyrencephalic species, having greater structural and functional similarities to the human brain than other lower species outlined in the literature, it is commonly chosen as a surrogate for human brain studies [7]. Consequently, we have chosen to use a porcine model in this work. To understand stress wave transfer to and through the brain, it is important to fully characterize the nature of the impact (i.e. source, location, and speed) as well as the response of the constituent tissues under such impact. We suspect the material and topology of these tissues play an important role in their response. In this paper, we report on a numerical study assessing the sensitivity of model parameters for a 6-month old Gottingen mini-pig model, under bump loading. In this study, 2D models are used for computational simplicity. While a 3D model is more realistic in nature, a 2D representation is still valuable in that it can provide trends on parameter sensitivity that can help steer the development of the 3D model. In this work, we investigate the variation of skull and skin thickness, evaluate material variability of the skull, and consider the effects of nasal cavities on load transfer. Eighty simulations are computed in LS-DYNA and analyzed in MATLAB. The results of this study will provide useful knowledge on the necessary components and parameters of the porcine model and therefore provide more confidence in the analysis. This is an essential first step as we look toward bridging the gap between correlates of injury in animal and human models.

scholarly journals Residual Compressive Strength of Short Tubular Steel Columns with Artificially Fabricated Local Corrosion Damage

Materials ◽  
2020 ◽  
Vol 13 (4) ◽  
pp. 813
Author(s):  
Kyra Kamille Toledo ◽  
Hyoung-Seok Kim ◽  
Young-Soo Jeong ◽  
In-Tae Kim
Keyword(s):  
Compressive Strength ◽  
Numerical Study ◽  
Corrosion Damage ◽  
Reduction Factor ◽  
Local Corrosion ◽  
Percentage Error ◽  
Steel Columns ◽  
Residual Compressive Strength ◽  
Short Columns ◽  
Half Wavelength

Corrosion is considered as one of the main factors in the structural performance deterioration of steel members. In this study, experimental and numerical methods were used to assess the reduction in compressive strength of short tubular steel columns with artificially fabricated local corrosion damage. The corrosion damage was varied with different depths, heights, circumferences, and locations along the column. A parametric numerical study was performed to establish a correlation between the residual compressive strength and the severity of corrosion damage. The results showed that as the corrosion depth, height and circumference increased, the compressive strength decreased linearly. As for the corrosion height, the residual compressive strength became constant after decreasing linearly when the corrosion height was greater than the half-wavelength of buckling of the short columns. An equation is presented to evaluate the residual compressive strength of short columns with local corrosion wherein the volume of the corrosion damage was used as a reduction factor in calculating the compressive strength. The percentage error using the presented equation was found to be within 11.4%.

Sign in / Sign up

Export Citation Format

Share Document