Application of requirements prioritization decision rules in software product line evolution

Inoki, Mari; Kitagawa, Takayuki; Honiden, Shinichi

doi:10.1109/reprico.2014.6895216

Cited by 4 publications

(4 citation statements)

References 8 publications

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“…In terms of the evaluation of stakeholders’ interests, we observed that researchers encountered two challenges. The first challenge was that stakeholders’ preferences were often vague or incomplete, thus making them unsuitable for further processing [54, 79 ]. The second challenge was that stakeholders had different preferences (priority levels) for the same cohort of requirements [43, 55 ].…”

Section: Discussionmentioning

confidence: 99%

Understanding requirements prioritisation: literature survey and critical evaluation

2020

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Requirements prioritisation deals with the ranking or classification of user requirements based on their importance. This process is central to releasing a software product with features most favoured by users. While studies have explored the efforts that are dedicated to this cause, these tend to focus on a subset of the solutions that are available in the software engineering domain. Current techniques investigated in the software engineering domain do not consider the strengths inherent in requirements prioritisation techniques developed in other disciplines (e.g. product manufacturing), a gap that should be addressed. The authors thus conducted a comprehensive systematic mapping study and critical evaluation of studies that have provided implementations of requirements prioritisation techniques across multiple disciplines (including software engineering, product manufacturing, and engineering). Among their findings, they observed that while many solutions are targeted, quite often researchers have proposed solutions that were not evaluated. Most solutions were only validated as being operational, and the attributes studied had limited effects on performance outcomes. Their evidence suggests that new techniques may address the requirements prioritisation challenge if they are inspired by hybrid approaches developed across multiple disciplines. In addition, performance trade‐offs are to be expected of such techniques, depending on their performance targets.

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Section: Discussionmentioning

confidence: 99%

Understanding requirements prioritisation: literature survey and critical evaluation

2020

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“…Hence, different studies have highlighted the importance of prioritization of features in requirement management and have also implemented reuse to reduce ambiguity, incompleteness, and delivery time [1,17,20]. These studies [9,21,22,43] described that prioritization is important for multiuser perspectives in component-based systems.…”

Section: Related Workmentioning

confidence: 99%

“…In SPLs, to deal with upcoming product changes, prediction of requirements is used to suggest to reuse existing re-quirements for changes at the early product development stage [31,44]. These products have several features and components, which increases significance for systematic reuse with complexity in configuration management [5,20,24]. To simplify the configuration management of features, the extraction of a feature model is adopted for recognizing common and variant features of highly configurable systems.…”

Section: Introductionmentioning

confidence: 99%

A Data Mining Technique to Improve Configuration Prioritization Framework for Component-Based Systems: An Empirical Study

Ali

Hafeez

Ali

et al. 2021

ITC

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Department of Software Engineering, In the current application development strategies, families of productsare developed with personalized configurations to increase stakeholders’ satisfaction. Product lines have theability to address several requirements due to their reusability and configuration properties. The structuringand prioritizing of configuration requirements facilitate the development processes, whereas it increases theconflicts and inadequacies. This increases human effort, reducing user satisfaction, and failing to accommodatea continuous evolution in configuration requirements. To address these challenges, we propose a framework formanaging the prioritization process considering heterogeneous stakeholders priority semantically. Featuresare analyzed, and mined configuration priority using the data mining method based on frequently accessed andchanged configurations. Firstly, priority is identified based on heterogeneous stakeholder’s perspectives usingthree factors functional, experiential, and expressive values. Secondly, the mined configuration is based on frequentlyaccessed or changed configuration frequency to identify the new priority for reducing failures or errorsamong configuration interaction. We evaluated the performance of the proposed framework with the help ofan experimental study and by comparing it with analytical hierarchical prioritization (AHP) and Clustering.The results indicate a significant increase (more than 90 percent) in the precision and the recall value of theproposed framework, for all selected cases.

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“…The major problem faced is the prioritising time and ease of use. Human interference in the process of prioritising increases the time to prioritise and in addition increases the cost involved in prioritising (Inoki et al, 2014).…”

Section: Challengesmentioning

confidence: 99%

WhaleRank: an optimisation based ranking approach for software requirements prioritisation

Anand

Dinakaran

2018

IJEWM

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Requirement prioritisation is one of the major areas in the software product development process. Ranking methods employed for prioritising orders the requirements based on their importance. Ranking the requirements contributes in enhancing the quality of the product using additional features and to attain customer satisfaction. However, effectiveness is the growing concern in requirement prioritisation. This paper proposes a ranking method WhaleRank to rank the requirement and the effectiveness of ranking gets enhanced using the whale optimisation algorithm (WOA). The WhaleRank method uses four ranking functions based on dictionary words, similarity measure, perception of the manager, and the newly updated requirements that are combined to form a linear rank using the ranking constants. WOA determines the optimal weights of the ranking constants that promote to determine the optimal rank for the requirements. Experimentation with the methods like CBRank, average rank, WhaleRank, and GA provide a comparative performance analysis that proves that the proposed WhaleRank outperforms all methods in terms of accuracy and disagreement measure (NDA) and the values of accuracy and NDA is 83.33% and 16.24% respectively.

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Application of requirements prioritization decision rules in software product line evolution

Cited by 4 publications

References 8 publications

Understanding requirements prioritisation: literature survey and critical evaluation

Understanding requirements prioritisation: literature survey and critical evaluation

A Data Mining Technique to Improve Configuration Prioritization Framework for Component-Based Systems: An Empirical Study

WhaleRank: an optimisation based ranking approach for software requirements prioritisation

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