scholarly journals Software Reliability Modeling Incorporating Fault Detection and Fault Correction Processes with Testing Coverage and Fault Amount Dependency

Mathematics ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 60
Author(s):  
Qiuying Li ◽  
Hoang Pham
Keyword(s):  
Fault Detection ◽  
Software Reliability ◽  
Estimation Methods ◽  
Time Dependency ◽  
Modeling Framework ◽  
Reliability Modeling ◽  
Imperfect Debugging ◽  
Detection Process ◽  
Correction Process ◽  
Testing Coverage

This paper presents a general testing coverage software reliability modeling framework that covers imperfect debugging and considers not only fault detection processes (FDP) but also fault correction processes (FCP). Numerous software reliability growth models have evaluated the reliability of software over the last few decades, but most of them attached importance to modeling the fault detection process rather than modeling the fault correction process. Previous studies analyzed the time dependency between the fault detection and correction processes and modeled the fault correction process as a delayed detection process with a random or deterministic time delay. We study the quantitative dependency between dual processes from the viewpoint of fault amount dependency instead of time dependency, then propose a generalized modeling framework along with imperfect debugging and testing coverage. New models are derived by adopting different testing coverage functions. We compared the performance of these proposed models with existing models under the context of two kinds of failure data, one of which only includes observations of faults detected, and the other includes not only fault detection but also fault correction data. Different parameter estimation methods and performance comparison criteria are presented according to the characteristics of different kinds of datasets. No matter what kind of data, the comparison results reveal that the proposed models generally give improved descriptive and predictive performance than existing models.

Toward a Unified Approach to Software Reliability Modeling under Imperfect Debugging

2015 ◽  
Vol 764-765 ◽  
pp. 979-982
Author(s):  
Jung Hua Lo
Keyword(s):  
Software Reliability ◽  
Growth Models ◽  
Failure Detection ◽  
Mean Value ◽  
Unified Approach ◽  
Development Environment ◽  
Reliability Modeling ◽  
Imperfect Debugging ◽  
Correction Process ◽  
Function Number

Many software reliability growth models (SRGMs) have been developed to estimate some useful measures such as the mean value function, number of remaining faults, and failure detection rate. Most of these models have focused on the failure detection process and not given equal priority to modeling the fault correction process. But, most latent software errors may remain uncorrected for a long time even after they are detected, which increases their impact. The remaining software faults are often one of the most unreliable reasons for software quality. Therefore, we develop a general framework of the modeling of the failure detection and fault correction processes. Furthermore, it is assumed that a detected fault is immediately removed and is perfectly repaired with no new faults being introduced for the traditional SRGMs. In reality, it is impossible to remove all faults from the fault correction process and have a fault-free effect on the software development environment. In order to relax this perfect debugging assumption, we introduce the possibility of imperfect debugging phenomenon. Finally, numerical examples are shown to illustrate the results of the unified approach for integration of the detection and correction process under imperfect debugging.

Markovian Multiple Change-Point Modeling for Software Reliability Assessment

2020 ◽  
Vol 27 (06) ◽  
pp. 2050017
Author(s):  
Shinji Inoue ◽  
Shigeru Yamada
Keyword(s):  
Software Reliability ◽  
Change Point ◽  
Reliability Assessment ◽  
Testing Time ◽  
Modeling Framework ◽  
Reliability Modeling ◽  
Imperfect Debugging ◽  
Testing Environment ◽  
Software Failure ◽  
Testing Phase

We discuss software reliability modeling reflecting actual situation in a testing phase based on a Markovian software reliability modeling framework. Concretely, we discuss Markovian imperfect debugging modeling for software reliability assessment with multiple changes of testing environment. Testing-time changing the testing environment is called change-point. Taking into account the effect of change-point in software reliability growth modeling is expected to improve the accuracy of software reliability assessment because it is often observed that the stochastic characteristic of software failure-occurrence or fault-detection phenomenon is changed in an actual testing phase. Numerical examples for software reliability assessment based on our proposed approach are also shown by using actual software failure-occurrence time data. Further, we discuss the usefulness of considering the effect of the imperfect debugging and the multiple change-point into software reliability modeling by comparing the estimated behavior of the mean time between software failures based on our model and the existing related models.

Software reliability prediction and release time management with coverage

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Saurabh Panwar ◽  
Vivek Kumar ◽  
P.K. Kapur ◽  
Ompal Singh
Keyword(s):  
Fault Detection ◽  
Software Reliability ◽  
Release Time ◽  
Software System ◽  
Reliability Growth ◽  
Time To Market ◽  
Content Type ◽  
Detection Process ◽  
Growth Phenomenon ◽  
Testing Coverage

PurposeSoftware testing is needed to produce extremely reliable software products. A crucial decision problem that the software developer encounters is to ascertain when to terminate the testing process and when to release the software system in the market. With the growing need to deliver quality software, the critical assessment of reliability, cost of testing and release time strategy is requisite for project managers. This study seeks to examine the reliability of the software system by proposing a generalized testing coverage-based software reliability growth model (SRGM) that incorporates the effect of testing efforts and change point. Moreover, the strategic software time-to-market policy based on costreliability criteria is suggested.Design/methodology/approachThe fault detection process is modeled as a composite function of testing coverage, testing efforts and the continuation time of the testing process. Also, to assimilate factual scenarios, the current research exhibits the influence of software users refer as reporters in the fault detection process. Thus, this study models the reliability growth phenomenon by integrating the number of reporters and the number of instructions executed in the field environment. Besides, it is presumed that the managers release the software early to capture maximum market share and continue the testing process for an added period in the user environment. The multiattribute utility theory (MAUT) is applied to solve the optimization model with release time and testing termination time as two decision variables.FindingsThe practical applicability and performance of the proposed methodology are demonstrated through real-life software failure data. The findings of the empirical analysis have shown the superiority of the present study as compared to conventional approaches.Originality/valueThis study is the first attempt to assimilate testing coverage phenomenon in joint optimization of software time to market and testing duration.

scholarly journals Modeling Software Fault-Detection and Fault-Correction Processes by Considering the Dependencies between Fault Amounts

2021 ◽  
Vol 11 (15) ◽  
pp. 6998
Author(s):  
Qiuying Li ◽  
Hoang Pham
Keyword(s):  
Time Delay ◽  
Fault Detection ◽  
Software Reliability ◽  
Growth Models ◽  
Predictive Performance ◽  
Real Data ◽  
Reliability Estimation ◽  
Model Parameters ◽  
Dual Processes ◽  
Correction Process

Many NHPP software reliability growth models (SRGMs) have been proposed to assess software reliability during the past 40 years, but most of them have focused on modeling the fault detection process (FDP) in two ways: one is to ignore the fault correction process (FCP), i.e., faults are assumed to be instantaneously removed after the failure caused by the faults is detected. However, in real software development, it is not always reliable as fault removal usually needs time, i.e., the faults causing failures cannot always be removed at once and the detected failures will become more and more difficult to correct as testing progresses. Another way to model the fault correction process is to consider the time delay between the fault detection and fault correction. The time delay has been assumed to be constant and function dependent on time or random variables following some kind of distribution. In this paper, some useful approaches to the modeling of dual fault detection and correction processes are discussed. The dependencies between fault amounts of dual processes are considered instead of fault correction time-delay. A model aiming to integrate fault-detection processes and fault-correction processes, along with the incorporation of a fault introduction rate and testing coverage rate into the software reliability evaluation is proposed. The model parameters are estimated using the Least Squares Estimation (LSE) method. The descriptive and predictive performance of this proposed model and other existing NHPP SRGMs are investigated by using three real data-sets based on four criteria, respectively. The results show that the new model can be significantly effective in yielding better reliability estimation and prediction.

Software Reliability Modeling Incorporating Log-Logistic Testing-Effort with Imperfect Debugging

2010 ◽  
Author(s):  
N. Ahmad ◽  
M. G. M. Khan ◽  
L. S. Rafi ◽  
Swapan Paruya ◽  
Samarjit Kar ◽  
...  
Keyword(s):  
Software Reliability ◽  
Reliability Modeling ◽  
Imperfect Debugging ◽  
Testing Effort
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