Release and testing stop time of a software using multi-attribute utility theory

Majumdar, Rana; Shrivastava, Avinash K.; Kapur, P. K.; Khatri, Sunil Kumar

doi:10.1007/s41872-017-0005-9

Cited by 18 publications

(9 citation statements)

References 31 publications

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“…Later Jiang et al 16 proposed a quantitative model and claimed that it is better release the software early to get the opportunity to acquire higher market potential and continue to test the software in the operational phase to remove the maximum number of faults before terminating the testing of the software. This phenomenon attracted various other researchers to develop more literature in this direction 1,18,26,32–34,36,40 . Kapur and Shrivastava 20 extended the Jiang et al 16 model by considering the cost of fault detection by testing team during post release testing phase.…”

Section: Literature Reviewmentioning

confidence: 99%

Change‐points‐based software scheduling

Shrivastava¹,

Kapur

2021

Quality & Reliability Eng

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Software reliability literature consists of various change‐point‐based software reliability growth models and related release time problems. The primary assumption of the existing models is the existence of change‐point before software release time only. This does not look practical as the testing team becomes more proficient in detecting the faults due to their continuous involvement in software development by the software release time. Hence the fault detection rate in the pre‐ and postrelease phase is not the same. To capture this change in fault detection rate in the pre‐ and postrelease testing phase, we propose a new software reliability modeling framework by considering two change‐points during the software lifecycle; that is, there exists a change‐point before release time and release time as a change‐point. Further, in the last one‐decade software firms have changed their strategy of stop testing the software after release and continue to test even after release to remove the number of faults to provide better user experiences. This phenomenon attracted academicians to develop theoretical as well empirical study on postrelease testing and formulation of related release time problem. In this paper, we propose a software cost model to determine optimal release and testing stop time considering under the assumption of two change‐points as mentioned above. The proposed model is validated on real‐life data set.

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Section: Literature Reviewmentioning

confidence: 99%

Change‐points‐based software scheduling

Shrivastava¹,

Kapur

2021

Quality & Reliability Eng

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“…Metode MAUT mengolah kriteria penilaian berdasarkan fungsi utilitas setiap alternatif. Fungsi utilitas ditentukan oleh banyaknya karakteristik terbaik dan nilai-nilai pada kasus terburuk dari setiap atribute [4]. Maka dengan menggunakan metode tersebut, dapat dihasilkan nilai evaluasi yang dapat dijadikan saran keputusan dalam penentuan mutasi jabatan.…”

Section: Pendahuluanunclassified

Evaluasi Mutasai Jabatan Anggota Kepolisian Menggunakan Metode Profile Matching dan Multi Attribute Utility Theory

Nas¹,

Defit²,

Santony³

2018

SITEKIN

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Mutasi jabatan bertujuan untuk menunjang operasional dan meningkatkan efektifitas kerja dari institusi kepolisian. Tujuan dari penelitian ini membantu dalam pengambilan keputusan untuk mutasi jabatan dengan mengevaluasi nilai kriteria setiap anggota kepolisian. Dalam penelitian ini dilakukan pengolahan data kriteria penilaian dan data personel kepolisian yang diperoleh melalui hasil wawancara bersama kepala bagian sumber daya serta pengisian quisioner oleh 15 anggota kepolisian. Dari data tersebut dilakukan pengujian dengan menggunakan metode Profile Matching dan Multi Atribute Utility Theory. Hasil dari pengujian metode-metode tersebut adalah dihasilkan sebuah keputusan pada sebuah alternatif dengan nilai total sebesar 83,3%. Maka metode ini dibutuhkan untuk mengevaluasi penentuan mutasi jabatan sehingga menghasilkan keputusan terbaik.

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“…It includes questions like when to quit testing, what is more, to test, which module has high coupling, the bug occurrence pattern. The objective is to release software as early as possible without identifying bugs in the system, and all stated targets are achieved [1]. Several programming driven models have been given in the literature to decide the release time, which may depend upon a non-homogeneous Poisson process (NHPP) [2], or consider proper investigation for targets defined some uses defect amplification model.…”

Section: Introductionmentioning

confidence: 99%

A time-variant fault detection software reliability model

et al. 2021

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In this work, we propose a time-variant software reliability model (SRM)which considers the fault detection and the highest number of faults in software. The time-variant genetic algorithm process is implemented for the assessment of the SRM parameters. The proposed model works upon a non-homogeneous Poisson process (NHPP) and incorporates fault dependent detection and software failure intensity and the un-removed error in the software. We had considered programmers proficiency, software complexity, organization hierarchy, and perfect debugging as the determining factors for SRM. The dataset collected from 74 software projects was experimented with to establish and validate the proposed software reliability model's better fit. Data is collected over a period, which is initiated with the start of the project and is continuously monitored until its completion. Several parameters are analyzed, and a collection of 115 attributes are given with 11 different time frames in terms of product and process characteristics. A total of 383 persons were involved in software design, where the issue count total is 255. The proposed time-variant fault detection SRM is implemented in Jira and is also compared with the existing reliability model presented in the literature. It is observed that the proposed fault detection SRM works better in terms of different parameters like mean square error (MSE), root mean square error (RMSE), and r-squared (R2). The work is carried out, ensuring time-varying fault detection, which is measured by considering response count, coding and non-coding deliverables, and the number of bugs in the software. We considered the programmer's proficiency, software complexity, organization hierarchy, and perfect debugging as the determining factors for presenting the software reliability model. The proposed Software reliability model shows improvement over existing algorithms as the residual errors are reduced, and prediction accuracy is high in terms of cumulative fault detection.

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Release and testing stop time of a software using multi-attribute utility theory

Cited by 18 publications

References 31 publications

Change‐points‐based software scheduling

Change‐points‐based software scheduling

Evaluasi Mutasai Jabatan Anggota Kepolisian Menggunakan Metode Profile Matching dan Multi Attribute Utility Theory

A time-variant fault detection software reliability model

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