Quality requirements elicitation based on inquiry of quality-impact relationships

Fotrousi, Farnaz; Fricker, Samuel; Fiedler, Markus

doi:10.1109/re.2014.6912272

Cited by 14 publications

(11 citation statements)

References 30 publications

(48 reference statements)

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“…Existing work on eliciting quality or "just in time" requirements (e.g., [12,13]) may serve as a starting point. A potential hurdle to extending such work is the lack of an easily understood energy metric.…”

Section: Implications For Requirementsmentioning

confidence: 99%

An empirical study of practitioners' perspectives on green software engineering

Manotas

Bird

Zhang

et al. 2016

Proceedings of the 38th International Conference on Software Engineering

125

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The energy consumption of software is an increasing concern as the use of mobile applications, embedded systems, and data center-based services expands. While research in green software engineering is correspondingly increasing, little is known about the current practices and perspectives of software engineers in the field. This paper describes the first empirical study of how practitioners think about energy when they write requirements, design, construct, test, and maintain their software. We report findings from a quantitative, targeted survey of 464 practitioners from ABB, Google, IBM, and Microsoft, which was motivated by and supported with qualitative data from 18 in-depth interviews with Microsoft employees. The major findings and implications from the collected data contextualize existing green software engineering research and suggest directions for researchers aiming to develop strategies and tools to help practitioners improve the energy usage of their applications.

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Section: Implications For Requirementsmentioning

confidence: 99%

An empirical study of practitioners' perspectives on green software engineering

Manotas

Bird

Zhang

et al. 2016

Proceedings of the 38th International Conference on Software Engineering

125

View full text Add to dashboard Cite

show abstract

“…They did not have knowledge of user feedback research, but they had been introduced and extensively trained in software engineering, including in theory and team projects. In a comparable rating and feedback study, Fricker et al (2015) could not identify discernable differences between student ratings and ratings of industry subjects and noted that their positive and negative feedback were congruent. Similarly, Höst et al (2000) could observe only minor differences in the conception, correctness, and judgment abilities of last-year students and professionals.…”

Section: Threats To Validitymentioning

confidence: 94%

“…The short questionnaire may also be triggered (Froehlich et al 2007) regularly or at a particular moment of experiencing a prototype or a released product. The annotating method is another example of written user feedback that users provide comments or rates for snippets of an image (Ames and Naaman 2007) or a video (Fricker et al 2015) when the users have some opinions to share. The interview (Ahtinen et al 2009) is an example of methods gathering verbal user feedback.…”

Section: Background and Related Workmentioning

confidence: 99%

The effect of requests for user feedback on Quality of Experience

2017

Self Cite

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Companies are interested in knowing how users experience and perceive their products. Quality of Experience (QoE) is a measurement that is used to assess the degree of delight or annoyance in experiencing a software product. To assess QoE, we have used a feedback tool integrated into a software product to ask users about their QoE ratings and to obtain information about their rationales for good or bad QoEs. It is known that requests for feedback may disturb users; however, little is known about the subjective reasoning behind this disturbance or about whether this disturbance negatively affects the QoE of the software product for which the feedback is sought. In this paper, we present a mixed qualitativequantitative study with 35 subjects that explore the relationship between feedback requests and QoE. The subjects experienced a requirement-modeling mobile product, which was integrated with a feedback tool. During and at the end of the experience, we collected the users' perceptions of the product and the feedback requests. Based on the users' rational for being disturbed by the feedback requests, such as Bearly feedback,^Binterruptive requests,^Bfrequent requests,^and Bapparently inappropriate content,^we modeled feedback requests. The model defines feedback requests using a set of five-tuple variables: Btask,^Btiming^of the task for issuing the feedback requests, user's Bexpertise-phase^with the product, the Bfrequency^of feedback requests about the task, and the Bcontent^of the feedback request. Configuration of these parameters might drive the participants' perceived disturbances. We also found that the disturbances generated by triggering user feedback requests have negligible impacts on the Software Qual J

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“…[4,24] [ 28,26] S2 The documentation of QRs is not always precise. [4,7,33,25] S3 QRs are often described in too vague terms. [5,25] S4 The documentation of QRs usually becomes desynchronized.…”

Section: Id Research Statement Pro Conmentioning

confidence: 99%

“…[4,35,36] T3 Most QR types are difficult to test properly. [5,7,33,27] T4 Testing QRs is time-consuming. [5] T5 Testing QRs is impossible.…”

Section: Id Research Statement Pro Conmentioning

confidence: 99%

Views on quality requirements in academia and practice: commonalities, differences, and context-dependent grey areas

Vogelsang

Eckhardt

Méndez

et al. 2020

Information and Software Technology

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Context: Quality requirements (QRs) are a topic of constant discussions both in industry and academia. Debates entwine around the definition of quality requirements, the way how to handle them, or their importance for project success. While many academic endeavors contribute to the body of knowledge about QRs, practitioners may have different views. In fact, we still lack a consistent body of knowledge on QRs since much of the discussion around this topic is still dominated by observations that are strongly context-dependent. This holds for both academic and practitioners' views. Our assumption is that, in consequence, those views may differ. Objective: We report on a study to better understand the extent to which available research statements on quality requirements, as found in exemplary peer-reviewed and frequently cited publications, are reflected in the perception of practitioners. Our goal is to analyze differences, commonalities, and contextdependent grey areas in the views of academics and practitioners to allow a discussion on potential misconceptions (on either sides) and opportunities for future research. Method: We conducted a survey with 109 practitioners to assess whether they agree with research statements about QRs reflected in the literature. Based on a statistical model, we evaluate the impact of a set of context factors to the perception of research statements. Results: Our results show that a majority of the statements is well respected by practitioners; however, not all of them. When examining the different groups and backgrounds of respondents, we noticed interesting deviations of perceptions within different groups that may lead to new research questions. Conclusions: Our results help identifying prevalent context-dependent differences about how academics and practitioners view QRs and pinpointing statements where further research might be useful.

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Quality requirements elicitation based on inquiry of quality-impact relationships

Cited by 14 publications

References 30 publications

An empirical study of practitioners' perspectives on green software engineering

An empirical study of practitioners' perspectives on green software engineering

The effect of requests for user feedback on Quality of Experience

Views on quality requirements in academia and practice: commonalities, differences, and context-dependent grey areas

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