A systematic mapping study on crowdsourced requirements engineering using user feedback

Wang, Chong; Daneva, Maya; Sinderen, Marten van; Liang, Peng

doi:10.1002/smr.2199

Cited by 21 publications

(14 citation statements)

References 27 publications

(41 reference statements)

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“…Text mining tools: focus on analyzing available data without actively involving stakeholders. Thereby not supporting elicitation directly, rather, they determined the relevance and importance of a sentence or statement through natural language algorithms, usually based on app store reviews [32], [33], [34]. Hosseini et al [35] surveyed experts to support the use of crowdsourcing for the help of requirements elicitation.…”

Section: B Crowdsourcing-based Requirements Engineeringmentioning

confidence: 99%

CREeLS: Crowdsourcing based Requirements Elicitation for eLearning Systems

Rizk¹,

Mervat²,

Ahmed³

et al. 2019

IJACSA

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Crowdsourcing is the process of having a task performed by the crowd. Because of the Web evolution, recently crowdsourcing is being used in the field of Requirements Engineering to help in simplifying its activities. Among the information systems that were highly affected by the Web evolution are the eLearning Systems (eLS). eLS has special characteristics, such as the large number and diversity of users who could be geographically dispersed. To the best of our knowledge, there is little evidence that a crowdsourcing based requirements elicitation approach especially tailored for eLS that addresses their special characteristics exists. In this paper we attempt to fill in this gap. We present Crowdsourcing based Requirements Elicitation for eLS (CREeLS), which is made up of a framework of the necessary elements of crowdsourcing suggesting specific tools for each element, and a phased approach to implement the framework. We evaluated our approach through analyzing real-life users' reviews and extracted keywords that represent users' requirements by using topic modeling techniques. The reached results were then evaluated by manual text reviewing and the extracted features were found to be coherent. CREeLS has 0.66 precision and 0.79 recall. Hence we contend that CREeLS can help requirements engineers of eLS to analyze users' opinions and identify the most common users' requirements for better software evolution.

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Section: B Crowdsourcing-based Requirements Engineeringmentioning

confidence: 99%

CREeLS: Crowdsourcing based Requirements Elicitation for eLearning Systems

Rizk¹,

Mervat²,

Ahmed³

et al. 2019

IJACSA

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“…Axial coding refers to the formation of the main category after the analysis and induction of the initial category obtained by the open coding. The 15 initial categories obtained by open coding are analyzed and summarized here before according to the definition of user needs in software engineering (Wang et al, 2019 ): (1) The conditions or capabilities required by the user to solve problems or achieve goals; (2) The capabilities of system and its component to meet the requirement from contracts, standards, specifications or other formal documents; (3) A document description that reflects the conditions or capabilities described in the above two scenarios, which mainly includes functional requirements and non-functional requirements. According to various needs of WeChat in different operating systems, we get a theoretical system composed of 6 main categories, namely 6 user needs of WeChat APP users obtained by Grounded Theory, which are: performance, reliability, usability, functional deficiency, functional insufficiency and system adaptability.…”

Section: Data Preparationmentioning

confidence: 99%

Grounded Theory-Based User Needs Mining and Its Impact on APP Downloads: Exampled With WeChat APP

Chen

Zhang²,

Yang³

et al. 2022

Front. Psychol.

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Software development is an iterative process from designing to implementation, and to testing, in which product development staff should be closely integrated with users. Satisfying user needs effectively is often the pain point for developers. In order to alleviate this, this paper manages to establish the quantitative connection between users' online reviews and APP (Application Program) downloads. By analyzing user online comments, companies can dig out user needs and preferences. This could benefit them by making accurate market positioning of their APP products, and therefore iteratively innovating products based on user needs, which hopefully will increase the volume of APP downloads. This paper regards WeChat APP during 47 updates periods as the research object. Based on Grounded Theory, user needs are extracted after data cleaning. Next, by using semantic analysis and word frequency analysis, we are able to obtain the implicit feedbacks such as emotion tendency, satisfaction and requirements lie under online reviews. Then, we construct a quantile regression model to study the impact of users' online reviews on downloads based on the influencing factors we extracted so as to provide a decision basis for enterprises to iteratively update their products. Results show that: (1) Generally speaking, needs of WeChat users mainly focus on performance, reliability, usability, functional deficiency, functional insufficiency, and system adaptability; (2) For those APP versions with relatively fewer downloads, user needs are mostly about functional deficiency, followed by functional insufficiency, performance, usability, and system adaptability. At this stage, it is found out that users' emotion tendency and user satisfaction significantly affect the volume of downloads; (3) When the volume of APP downloads is moderate, the user needs are functional deficiency, functional insufficiency, and system adaptability. While under this circumstances, users' star ratings have a significant impact on downloads; (4) In addition, when the volume of App downloads is high, user needs are performance, usability, and system adaptability. Our methods effectively extract users' requirements from online reviews and then successfully build up the quantitative connection between the implicit feedbacks from those requirements and APP downloads.

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“…Wang et al 16 conducted an SLR on crowdsourced user feedback used for RE purpose. The authors considered 44 studies as their primary study set to know how user feedback empowered RE activities.…”

Section: Related Workmentioning

confidence: 99%

“…Bakar et al 15 have surveyed 13 studies that mainly focus on how product descriptions and software requirements specification (SRS) document are used to elicit user requirements for software product line organizations. Wang et al, 16 Groen et al, 17 and Mao et al 18 have surveyed literature that emphasizes on crowdsourcing (e.g., from App Store and Google Play Store) and RE. The authors have concluded that user feedback can be a major source to support RE activities.…”

Section: Introductionmentioning

confidence: 99%

Social network sites and requirements engineering: A systematic literature review

Ali

Hong

Chung

2020

J Software Evolu Process

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A large volume of highly diverse and real‐time data provided by social network sites has revolutionized several data analytical sciences such as stock exchange fluctuation prediction, sentiment analysis, and political affiliations prediction. From a software engineering viewpoint, social network sites have produced an unprecedented opportunity for software development organizations to monitor the opinion of the large population of users of their systems. The extracted data from social network sites can be used to extract information about newly launched systems, and it enable software development organizations to obtain rapid technical and social feedback about their systems. This paper presents on a systematic literature review of the published research articles on how requirements engineering (RE) activities are conducted using social network sites, elaborated in studies published between 2011 and 2019. From the resulting studies, we extracted data to answer our four questions related to social network site (SNS)‐based RE approaches focusing on requirements elicitation, prioritization, and negotiation activities. Thirty‐one relevant studies were identified and analyzed to answer our research questions. Among 31 studies, 62% of the studies reportedly support requirements elicitation activity, and 14% of the studies reportedly support requirements elicitation, prioritization, and negotiation activities. Ten percent studies were about requirements elicitation and prioritization activities, 7% of the studies support both requirements elicitation and negotiation activities, and prioritization activity was supported by 7% of the studies. It was also observed that 58% of the selected studies adopted semi‐automatic approaches to conduct RE activities while 21% of the selected studies proposed automatic tools, and 21% of the selected studies adopted manual approaches to conduct RE activities. The outcomes of this systematic literature review indicate that social network sites can be a major source that can be used successfully to extract and identify user requirements. Moreover, this systematic literature review also presents implications of this study for practitioners and researchers including challenges, unresolved issues, and future research directions.

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A systematic mapping study on crowdsourced requirements engineering using user feedback

Cited by 21 publications

References 27 publications

CREeLS: Crowdsourcing based Requirements Elicitation for eLearning Systems

CREeLS: Crowdsourcing based Requirements Elicitation for eLearning Systems

Grounded Theory-Based User Needs Mining and Its Impact on APP Downloads: Exampled With WeChat APP

Social network sites and requirements engineering: A systematic literature review

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