Framework for modeling software reliability, using various testing-efforts and fault-detection rates

Kuo, Sy‐Yen; Huang, Chin‐Yu; Lyu, Michael R.

doi:10.1109/24.974129

Cited by 100 publications

(6 citation statements)

References 27 publications

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“…The general assumptions of the NHPP SRGM with Sshaped TEFs are shown as follows [4,7,8,12]: (i) The occurrence and removal process of software faults follows the NHPP;…”

Section: Nhpp Software Reliability Modeling With Two S-shaped Tefsmentioning

confidence: 99%

“…We integrate the ExpWeibull (6), logistic (7) and inect S-shaped (15) TEFs into the exponential-type (20), delayed S-shaped (30) and in ected S-shaped (33) NHPP SRGMs respectively to obtain following nine models, namely LO-TEFM, LO-TEFM-DS, LO-TEFM-IS, EW-TEFM, EW-TEFM-DS, EW-TEFM-IS, IS-TEFM, IS-TEFM-DS and IS-TEFM-IS. Then we compare these models by respectively applying them into DS1 -DS3.…”

Section: Comparison Of the S-shaped Nhpp Srgms With Various Tefsmentioning

confidence: 99%

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Incorporating S-shaped testing-effort functions into NHPP software reliability model with imperfect debugging

Li²,

2015

J. of Syst. Eng. Electron.

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Testing-effort (TE) and imperfect debugging (ID) in the reliability modeling process may further improve the tting and prediction results of software reliability growth models (SRGMs). For describing the S-shaped varying trend of TE increasing rate more accurately, rst, two S-shaped testing-effort functions (TEFs), i.e., delayed S-shaped TEF (DS-TEF) and in ected S-shaped TEF (IS-TEF), are proposed. Then these two TEFs are incorporated into various types (exponential-type, delayed S-shaped and inected S-shaped) of non-homogeneous Poisson process (NHPP) SRGMs with two forms of ID respectively for obtaining a series of new NHPP SRGMs which consider S-shaped TEFs as well as ID. Finally these new SRGMs and several comparison NHPP SRGMs are applied into four real failure data-sets respectively for investigating the tting and prediction power of these new SRGMs.The experimental results show that: (i) the proposed IS-TEF is more suitable and exible for describing the consumption of TE than the previous TEFs; (ii) incorporating TEFs into the in ected S-shaped NHPP SRGM may be more effective and appropriate compared with the exponential-type and the delayed S-shaped NHPP SRGMs; (iii) the in ected S-shaped NHPP SRGM considering both IS-TEF and ID yields the most accurate tting and prediction results than the other comparison NHPP SRGMs.

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“…The general assumptions of the NHPP SRGM with Sshaped TEFs are shown as follows [4,7,8,12]: (i) The occurrence and removal process of software faults follows the NHPP;…”

Section: Nhpp Software Reliability Modeling With Two S-shaped Tefsmentioning

confidence: 99%

Section: Comparison Of the S-shaped Nhpp Srgms With Various Tefsmentioning

confidence: 99%

Incorporating S-shaped testing-effort functions into NHPP software reliability model with imperfect debugging

Li²,

2015

J. of Syst. Eng. Electron.

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“…Various forms of testing-effort functions have been used in the literature such as exponential, Rayleigh, Weibull, logistic etc. Kuo et al, 2001;Kapur & Bardhan, 2002;Kapur et al, 2006;Huang et al, 2007;Kapur et al, 2008).…”

Section: Testing-effort Modellingmentioning

confidence: 99%

“…These models assume testing-effort to be constant throughout the testing period. Other SRGMs have incorporated the expenditures due to testing-effort Kuo et al, 2001;Kapur & Bardhan, 2002;Kapur et al, 2006;Huang et al, 2007;Kapur et al, 2008). They assumed that the fault detection rate is proportional to current fault-content and software testing-effort expenditures.…”

Section: Introductionmentioning

confidence: 99%

Testing-Effort Dependent Software Reliability Model for Distributed Systems

Shatnawi

2013

International Journal of Distributed Systems and Technologies

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Distributed systems are being developed in the context of the client-server architecture. Client-server architectures dominate the landscape of computer-based systems. Client-server systems are developed using the classical software engineering activities. Developing distributed systems is an activity that consumes time and resources. Even if the degree of automation of software development activities increased, resources are an important limitation. Reusability is widely believed to be a key direction to improving software development productivity and quality. Software metrics are needed to identify the place where resources are needed; they are an extremely important source of information for decision making. In this paper, an attempt has been made to describe the relationship between the calendar time, the fault removal process and the testing-effort consumption in a distributed development environment. Software fault removal phenomena and testing-effort expenditures are described by a non-homogenous Poisson process (NHPP) and testing-effort curves respectively. Actual software reliability data cited in literature have been used to demonstrate the proposed model. The results are fairly encouraging.

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“…Nearly all techniques consider failure data to measure software development and operational environment in a system. The authors have explained the various software reliability models and its features in [2], [3], [4], [5], [7], [8] and [11]. The challenges are remain exist with these measures; hence software reliability engineering is in use an active subject for Stakeholders to develop consistent software.…”

Section: Introductionmentioning

confidence: 99%

Advanced Program Complexity Metrics and Measurement

P¹,

Sarala²

2011

IJCA

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The complexity metrics has an important role in assessing the quality of source code. Obtainable complexity metrics is failed to accumulate precise system failure information. In this work proposes adequate complexity metrics for structural measure which collect the exact system information that cause the system failure in source code. Then, by censure M cCabe's cyclomatic number and the framework of adequate metrics that can be extensively observe the structural complexity of the various statements in the code. The proposed metrics verifies the accuracy of the source code evaluation, gains the proportion of software complexity metric by the experimental approach whereas, software complexity measurement is consistent with the actual result. General TermsComplexity measurement

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Framework for modeling software reliability, using various testing-efforts and fault-detection rates

Cited by 100 publications

References 27 publications

Incorporating S-shaped testing-effort functions into NHPP software reliability model with imperfect debugging

Incorporating S-shaped testing-effort functions into NHPP software reliability model with imperfect debugging

Testing-Effort Dependent Software Reliability Model for Distributed Systems

Advanced Program Complexity Metrics and Measurement

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