DRank: A semi-automated requirements prioritization method based on preferences and dependencies

Shao, Fei; Peng, Rong; Lai, Han; Wang, Bangchao

doi:10.1016/j.jss.2016.09.043

Cited by 59 publications

(77 citation statements)

References 12 publications

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“…A TOPSIS-based tool was provided in [9] to consider the prerequisites for the requirement dependencies, which change the score of each requirement provided by TOPSIS to set the score of each as less than each of its prerequisites/dependencies. Moreover, [25] proposed Drank (a method of semiautomated requirements prioritization) to integrate the preferences and dependencies of the requirements using a weighted page rank algorithm. In Drank, a prioritization evaluation attributes tree (PEAT) is developed, and then a subjective requirements prioritization using RankBoost is created.…”

Section: Related Workmentioning

confidence: 99%

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Prioritizing interdependent software requirements using tensor and fuzzy graphs

Misaghian¹,

Motameni²,

Rabbani³

2019

Turk J Elec Eng & Comp Sci

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Owing to the special stance of prioritizing tasks in requirements engineering processes, and as the requirements are not independent in nature, considering their dependencies is essential during the prioritizing process. Although different classifications of dependency types among requirements exist, only a few approaches in the prioritization process consider such valuable data (dependency among requirements). To achieve a practical prioritization, this study proposes a method based on the effects of the requirement dependencies (increase/decrease cost of) on the value of prioritization provided by the tensor concept. Since the strengths of dependencies are also influential factors in the act of prioritization, the algebraic structure of fuzzy graphs is used to model the requirement dependencies and their strengths. Moreover, a weighted page rank algorithm based on the fuzzy concept is provided to determine the final dependency strength of the dependent requirements of the fuzzy graph. To evaluate the proposed approach, a controlled experiment is also conducted. The proposed approach is compared with an analytic hierarchy process-based approach, TOPSIS, and EVOLVE in the experiment. The results analysis demonstrates that our approach is less time-consuming, much easier to use, and highly accurate.

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Section: Related Workmentioning

confidence: 99%

“…Since the dependencies are analyzed in negative and positive manners, the two dependency orders calculated from the fuzzy cost graph are combined to achieve a conflict-free ordered list. Furthermore, in order to achieve the influence rank of each requirement in the fuzzy cost graph, the following modified formula is provided based on [25]:…”

Section: Examplementioning

confidence: 99%

Prioritizing interdependent software requirements using tensor and fuzzy graphs

Misaghian¹,

Motameni²,

Rabbani³

2019

Turk J Elec Eng & Comp Sci

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show abstract

“…Various dependency types are identified (Pohl, 1996;Dahlstedt and Persson, 2005;Zhang et al, 2014). Dependent on interrelations, requirements are prioritized (Shao et al, 2016). Additionally, the stability of a software release is assessed on basis of requirements stability indices (Christoper and Chandra, 2012).…”

Section: Figure 2 Checklist For Setting Up a Requirements List (Feldmentioning

confidence: 99%

Semi-Automatized Assessment of Requirement Interrelations

Graessler¹,

Scholle²,

Hentze³

et al. 2018

Proceedings of the DESIGN 2018 15th International Design Conference

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Changing requirements have a broad impact on product development processes. In this paper, a novel approach towards structuring requirements is proposed. Based on a requirements list, interrelations of requirements are assessed semi-automatically by a rule basis. Here, generic interrelations funded on either physical fundamentals or working principles are recorded. By this approach, requirements structure matrices are derived semi-automatically. Combined with selecting critical requirements based on structured criterions, iterations due to changing requirements will be reduced.

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“…A novel technique [10] was developed to prioritize optional requirements. In this technique, a prioritization evaluation attributes tree was constructed for creating the ranking criteria selection.…”

Section: Related Workmentioning

confidence: 99%

A Firefly Approach for Prioritizing Functional and Nonfunctional Requirements

Yesudoss

Ramani²

2018

ijarcs

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Abstract:The prioritization of requirements is an important task in software development to implement requirements based on budget, time, customer expectations and practical constraints. An Interactive Genetic Algorithm (IGA) has been used to prioritize requirements by satisfying constraints. IGA sometimes provides a poor ranking due to population divergence. This is resolved in this paper by utilizing Firefly algorithm. The methods for prioritizing both functional and non functional requirements together are very less and have several drawbacks like of considering a small number of non functional requirements and applying less ranking weight. The firefly algorithm provides random prioritization initially, then improves the prioritization iteratively by minimizing disagreement between priorities and constraints while maximizing agreement between priority and customer satisfaction. The sum of disagreement is considered as light intensity of firefly. The population of firefly generates an ordered list of functional and nonfunctional requirements. The fitness value (intensity) is found for all fireflies then each firefly updates its position towards the best search of a firefly until all fireflies obtain same fitness value. The experimental result proves that the firefly based prioritization outperforms than Genetic Algorithm based prioritization.

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DRank: A semi-automated requirements prioritization method based on preferences and dependencies

Cited by 59 publications

References 12 publications

Prioritizing interdependent software requirements using tensor and fuzzy graphs

Prioritizing interdependent software requirements using tensor and fuzzy graphs

Semi-Automatized Assessment of Requirement Interrelations

A Firefly Approach for Prioritizing Functional and Nonfunctional Requirements

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