An Empirical Study to Compare the Accuracy of AHP and CBRanking Techniques for Requirements Prioritization

Perini, Anna; Susi, Angelo; Ricca, Filippo; Bazzanella, Cinzia

doi:10.1109/cere.2007.1

Cited by 11 publications

(1 citation statement)

References 13 publications

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“…Various researchers even had evaluated some of the prioritization techniques against some criteria or parameters of prime interest in order to compare these techniques and to find out a better one (Hasan et al, 2010;Iqbal et al, 2009;Ma 2009;Ahl 2005;Karlsson et al, 1998;Karlsson et al, 2004;Perini et al, 2007;Aasem et al, 2010;Racheva et al, 2008). But unfortunately the criteria are not well established or pre-defined and agreed by all so that the results of the comparison will be different when evaluated against different criteria's.…”

Section: Related Workmentioning

confidence: 99%

Requirement Prioritization of Complex Web 2.0 Application based on Effects on Regression Testing

Gupta¹,

Chauhan

Dutta

2015

International Journal of Systems and Service-Oriented Engineering

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Web 2.0 applications are complex information systems. Likewise any desktop applications, web applications are complex and require effective requirement prioritization preceded by effective decision aspect prioritization by involving diverse stakeholders. During the release of new increments, objective is to provide value to the software and simultaneously lowering the regression testing effort. This can be achieved by implementing all highest priority requirements along with those dependent on them so that next increments implemented requirements independent of already implemented ones. The challenges involved in aspect selection, requirement prioritization, and effective selection of the security requirements of Web 2.0 application makes its incremental deliveries a complex task as compared to that of desktop applications. The proposed requirement prioritization process is hybrid approach i.e. Based on combination of negotiations and methods to prioritize both decision aspects and software requirements. This technique reduces regression testing effort by taking an impact on regression testing as one of the parameters during prioritization and overcomes various problems related to prioritization of web 2.0 applications. This technique is applied on live system of “Virtual Classroom”, by employing three stakeholder groups with total 8 stakeholders. Results were promising since it resulted in the successful delivery of web application due to effective aspect and requirement prioritization thereby leading to reduced regression testing effort.

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Section: Related Workmentioning

confidence: 99%

Requirement Prioritization of Complex Web 2.0 Application based on Effects on Regression Testing

Gupta¹,

Chauhan

Dutta

2015

International Journal of Systems and Service-Oriented Engineering

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Analysis of Fuzzy AHP and Fuzzy TOPSIS Methods for the Prioritization of the Software Requirements

Nazim

Mohammad

Sadiq

2022

Studies in Systems, Decision and Control

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Crowd-Informed Goal Models

Kanchev¹,

Murukannaiah²,

Chopra³

2018

2018 5th International Workshop on Artificial Intelligence for Requirements Engineering (AIRE)

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A topic of recent interest is how to apply crowdsourced information toward producing better software requirements. A research question that has received little attention so far is how to leverage crowdsourced information toward creating better-informed models of requirements. In this paper, we contribute a method following which information in online discussions may be leveraged toward constructing goal models. A salient feature of our method is that it applies high-level queries to draw out potentially relevant information from discussions. We also give a subjective logic-based method for deriving an ordering of the goals based on the amount of supporting and rebutting evidence in the discussions. Such an ordering can potentially be applied toward prioritizing goals for implementation.

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An Empirical Study to Compare the Accuracy of AHP and CBRanking Techniques for Requirements Prioritization

Cited by 11 publications

References 13 publications

Requirement Prioritization of Complex Web 2.0 Application based on Effects on Regression Testing

Requirement Prioritization of Complex Web 2.0 Application based on Effects on Regression Testing

Analysis of Fuzzy AHP and Fuzzy TOPSIS Methods for the Prioritization of the Software Requirements

Crowd-Informed Goal Models

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