Effort based release time of software for detection and correction processes using MAUT

Choudhary, Chetna; Kapur, P. K.; Khatri, Sunil Kumar; Muthukumar, R.; Shrivastava, Avinash K.

doi:10.1007/s13198-020-00955-2

Cited by 13 publications

(7 citation statements)

References 54 publications

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“…SRGMs assist us in observing the faults and their consequent removal. Several SRGMs that considered both fault observation and removal have been put forth 38,41 . But all these models assumed that debugging is perfect.…”

Section: Literature Reviewmentioning

confidence: 99%

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Modelling reliability growth for multi‐version open source software considering varied testing and debugging factors

Saraf

Iqbal

Shrivastava

et al. 2021

Quality & Reliability Eng

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Due to the continuous dependence of society on technology and the fast growth of Open Source Software (OSS), there is a need for the software industry to shift to multi‐release software development. To include the revisions in user demands and testing environment, factors that affect OSS reliability have to be considered. Here, we propose a quantitative method for assessing the reliability of multi‐release OSS by using Software Reliability Growth Models based on the Non‐Homogenous Poisson Process. Various factors like imperfect debugging, error generation, change‐point have been considered. The model has been estimated on Statistical Package for Social Sciences using three releases of the Apache dataset. It is concluded that the results obtained are improved than the existing ones.

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Section: Literature Reviewmentioning

confidence: 99%

“…With the help of NHPP, many critical decisions regarding reliability prediction, resource allocation, cost analysis, testing time etc. can be determined 1,2,35–36,38,39,41,43 . To improve software quality and achieve prosperity in the software industry, software industries are switching from closed source data to open‐source data.…”

Section: Introductionmentioning

confidence: 99%

Modelling reliability growth for multi‐version open source software considering varied testing and debugging factors

Saraf

Iqbal

Shrivastava

et al. 2021

Quality & Reliability Eng

Self Cite

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show abstract

“…10, No. 4, December 2021: 930 -937 932 to convert from multiple interests into numerical valueson a scale from 0-1 with 0 representing the worst choice and 1 being the best [13], [14]. This allows a direct comparison of various measures.…”

Section: Multy Atribute Utility Theory (Maut)mentioning

confidence: 99%

Comparison of TOPSIS and MAUT methods for recipient determination home surgery

Maharani

Ridwanto

Hatta

et al. 2021

IJ-AI

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<span lang="EN-US">House renovation is given by the government to the community, one of which is the assistance provided in the district. Long Mevery especially Tanah Abang Village, namely House Renovation Assistance. So it is necessary to implement a DSS in determining the recipient of home renovation assistance by comparing MAUT method and TOPSIS to assist the government in determining the right home renovation assistance recipient. There are 16 criteria and their weight values. This study uses the multi-attribute utility theory method (MAUT) and the order of preference technique based on the similarity to the ideal solution (TOPSI) as a calculation method to produce output and determine the level of accuracy of each method. The test in this study uses a confusion matrix and compares real data testing with the results of calculations on the system. The results of system testing using MAUT and TOPSIS methods, the accuracy of the MAUT method is 94.28% and the TOPSIS method is 35.71%.</span>

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“…This limits the application of analytical models. There have been some work, which presented analytical studies for an integration of fault detection, and correction processes in software reliability analysis [6,10,27]. An implemented software system has been examined in the software development procedure.…”

Section: Assumptionsmentioning

confidence: 99%

Integration of Testing Effort Function into Delayed S-Shaped Software Reliability Growth Model with Imperfect Debugging — a Proposed Bokhari Model

2021

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Effort based release time of software for detection and correction processes using MAUT

Cited by 13 publications

References 54 publications

Modelling reliability growth for multi‐version open source software considering varied testing and debugging factors

Modelling reliability growth for multi‐version open source software considering varied testing and debugging factors

Comparison of TOPSIS and MAUT methods for recipient determination home surgery

Integration of Testing Effort Function into Delayed S-Shaped Software Reliability Growth Model with Imperfect Debugging — a Proposed Bokhari Model

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