How do Practitioners Capture and Utilize User Feedback During Continuous Software Engineering?

Johanßen, Jan Ole; Kleebaum, Anja; Bruegge, Bernd; Paech, Barbara

doi:10.1109/re.2019.00026

Cited by 22 publications

(18 citation statements)

References 46 publications

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“…We describe three use cases in which the use of opinion mining can provide benefits. They are inspired by real-world scenarios, which were analysed in previous research [1,2,14].…”

Section: Motivating Scenariosmentioning

confidence: 99%

“…App reviews is a rich source of user opinions [1,2,14,17]. These opinions can help developers to understand how users perceive their app, what are users' requirements, or what are users' preferences [1,2,14]. Not surprisingly, knowing user opinions is an important information need developers seek to satisfy [2,4].…”

Section: Introductionmentioning

confidence: 99%

“…Not surprisingly, knowing user opinions is an important information need developers seek to satisfy [2,4]. The information can affect different software engineering practices [1,14].…”

Section: Introductionmentioning

confidence: 99%

“…Analysing app reviews to find user opinions, however, is challenging [14,17]; Developers may receive thousands of reviews per day [1,14,17]. Moreover, these reviews contain mostly noise [17,19].…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, these reviews contain mostly noise [17,19]. Consequently, the possibility of using these opinions to support engineering activities is obstructed [1,14].…”

Section: Introductionmentioning

confidence: 99%

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Mining User Opinions to Support Requirement Engineering: An Empirical Study

Dąbrowski

Letier

Perini

et al. 2020

Lecture Notes in Computer Science

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App reviews provide a rich source of user opinions that can support requirement engineering activities. Analysing them manually to find these opinions, however, is challenging due to their large quantity and noisy nature. To overcome the problem, automated approaches have been proposed for so-called opinion mining. These approaches facilitate the analysis by extracting features discussed in app reviews and identifying their associated sentiments. The effectiveness of these approaches has been evaluated using different methods and datasets. Unfortunately, replicating these studies to confirm their results and to provide benchmarks of different approaches is a challenging problem. We address the problem by extending previous evaluations and performing a comparison of these approaches. In this paper, we present an empirical study in which, we evaluated feature extraction and sentiment analysis approaches on the same dataset. The results show these approaches achieve lower effectiveness than reported originally, and raise an important question about their practical use.

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“…We describe three use cases in which the use of opinion mining can provide benefits. They are inspired by real-world scenarios, which were analysed in previous research [1,2,14].…”

Section: Motivating Scenariosmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Not surprisingly, knowing user opinions is an important information need developers seek to satisfy [2,4]. The information can affect different software engineering practices [1,14].…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Moreover, these reviews contain mostly noise [17,19]. Consequently, the possibility of using these opinions to support engineering activities is obstructed [1,14].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Mining User Opinions to Support Requirement Engineering: An Empirical Study

Dąbrowski

Letier

Perini

et al. 2020

Lecture Notes in Computer Science

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Towards Integrating Data-Driven Requirements Engineering into the Software Development Process: A Vision Paper

Franch

Seyff

Oriol

et al. 2020

Requirements Engineering: Foundation for Software Quality

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Modern software engineering processes have shifted from traditional upfront requirements engineering (RE) to a more continuous way of conducting RE, particularly including data-driven approaches. [Question/problem] However, current research on data-driven RE focuses more on leveraging certain techniques such as natural language processing or machine learning than on making the concept fit for facilitating its use in the entire software development process. [Principal ideas/results] In this paper, we propose a research agenda composed of six distinct research directions. These include a data-driven RE infrastructure, embracing data heterogeneity, context-aware adaptation, data analysis and decision support, privacy and confidentiality, and finally process integration. Each of these directions addresses challenges that impede the broader use of data-driven RE. [Contribution] For researchers, our research agenda provides topics relevant to investigate. For practitioners, overcoming the underlying challenges with the help of the proposed research will allow to adopt a data-driven RE approach and facilitate its seamless integration into modern software engineering. For users, the proposed research will enable the transparency, control, and security needed to trust software systems and software providers.

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Towards Super User-Centred Continuous Delivery: A Case Study

Klemets

Storholmen

2020

Lecture Notes in Computer Science

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To develop well designed socio-technical systems for a particular context user involvement is essential. Emerging software development approaches that enable continuous delivery of software functionalities provide new opportunities as to how users can be involved in shaping the design. We present a case study of a software project at a Norwegian engineering and construction company in their effort to move towards a user-centred development approach that leverages on continuous delivery principles. We investigate how users-representatives in form of super users have been involved in the process and their role in forming and implementing the system in practice. We conclude that utilising super users have been instrumental to design a system that meet users' needs. Providing opportunities to test the system in a production environment gave rise to new ideas on how to further refine the design. Involving super users also facilitated system adoption among workers.

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How do Practitioners Capture and Utilize User Feedback During Continuous Software Engineering?

Cited by 22 publications

References 46 publications

Mining User Opinions to Support Requirement Engineering: An Empirical Study

Mining User Opinions to Support Requirement Engineering: An Empirical Study

Towards Integrating Data-Driven Requirements Engineering into the Software Development Process: A Vision Paper

Towards Super User-Centred Continuous Delivery: A Case Study

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