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The Internet of Things (IoT) promises to deliver improved quality of life for citizens, through pervasive connectivity and quantified monitoring of devices, people, and their environment. As such, the IoT presents a major new opportunity for research in adaptive software engineering. However, there are currently no shared exemplars that can support...
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... Effective strategies to reduce wasteful behavior should require minimum time and cognitive effort from consumers. The Feed me, Feed me exemplar (Bennaceur et al., 2016) describes a system based on the Internet of Things to support the production, distribution, and consumption of food. We use ideas and challenges from the Feed me, Feed me exemplar to focus on how our approach can support individuals in reducing food waste in households. ...
In this chapter, we provide an introduction to the discipline of requirements engineering as part of the software engineering process. We indicate how to elicit, articulate, and organize the goals of complex software systems as an explicit expression of the requirements that the proposed or existing software system is expected to achieve and maintain, including what the system should avoid performing. We advocate that system requirements goals can and should be used to explicitly capture, express, and reason about the diverse digital humanism values which are of concern in socio-technical systems. This is an essential aspect of responsible software engineering.
... Feed me, Feed me is described in [2]. It is an IoT-based ecosystem to support food security, ensure sufficient, safe, and nutrition food to the global population. ...
... A package with the full experimental materials, scripts, and results is available online. 2 Procedure. The empirical study has started with a 20 min training session that included a motivation of the experiment, an introduction into adaptive systems and elicitation of requirements, a presentation of the experiment materials, and an explanation of techniques. ...
... They reported that this approach elicited a wider spectrum of issues and revealed more facets of the perception that people might have of the technology. It has been used to explore future technology in different context Price et al., 2010;Bennaceur et al., 2016, Marinescu, et al., 2021. Most, if not all, reported ContraVision studies have used videos to present positive and negative aspects of future technology. ...
... Ideally, user study should recruit participants from a targeted and relevant population to ensure that they were familiar with the context of scenarios that were presented. While there was no general consensus of number participants required in ContraVision study, studies using ContraVision method have reported between involvement of 11 to 134 participants Price et al., 2010;Bennaceur et al., 2016, Marinescu, et al., 2021. Thus, as his study only involved 10 participants in each group, the number of participants in this study could be considered as rather low. ...
for long papers, 8 pages max) Manufacturing is a domain that is heavily influenced by and relies on future technology which have direct effects on its employees. It is known that user studies are required to ensure that products or systems meet requirement from and are accepted by potential users. However, it is difficult to explore users' responses for future technology that users have no direct experience and knowledge. ContraVison is one of user study methods and is commonly used to study perceptions and acceptance of new future technology. Participants are typically exposed to positive and negative scenarios. This study investigates how different format of scenarios delivery (video, audio and text) in a modified ContraVision affects the richness of information that could be obtained from potential users. Thirty participants were recruited and divided evenly into three groups of user studies. Data was collected through semi-structured interviews and thematic analysis was used. There was no significant effect of the scenarios format delivery on the richness of information that could be obtained from participants in these three groups, although there was a trend that video offers richer information than audio and text. However, further study was required to ascertain this finding as limited characteristics and number of participants in this study might have an impact on the results of current study.
... Feed me [24], DeltaIoT [25], Platform as a service, and Xively [19]. ...
Distributed intelligence is a well-known approach for optimizing interactions among numerous smart devices that interconnect and operate together as Internet of Things (IoT) systems. A modern form of human-machine collective intelligence emerges when humans interact with IoT systems in sociotechnical environments such as smart homes. Fifth-generation (5G) communication networks are designed for high-speed reliable wireless connectivity and expected to boost IoT and (distributed) collective intelligence by revolutionizing human–device–human interactions. In this paper, we contribute a comprehensive review of state-of-the-art sociotechnical environments that exhibit collective intelligence, supported by 5G-enabled IoT. We discuss the latest developments in 5G and their implications for collective intelligence. Further, we explain the key challenges for using 5G to support collective intelligence, e.g., data processing, security, and radio resource management. Finally, we describe four practical applications of collective intelligence to sociotechnical environments—road traffic control, unmanned aerial vehicles, electrical load demand response, and augmented democracy.
... In the recent years, several researchers [1]- [5] introduced vision videos into Requirements Engineering (RE) for soliciting feedback and stimulating discussions. According to Karras et al. [6,p. ...
... These videos are frequently used to solicit feedback and stimulate discussion in RE practices such as workshops and focus groups [13], [21], [22]. Although different researchers [1]- [4] reported on the benefits of vision videos for soliciting feedback and stimulating discussions in group or individual meetings, they seldom provide details about the quantity and content of the feedback. Bennaceur et al. [1] used vision videos in group discussions to solicit as much feedback from the participants as possible. ...
... Although different researchers [1]- [4] reported on the benefits of vision videos for soliciting feedback and stimulating discussions in group or individual meetings, they seldom provide details about the quantity and content of the feedback. Bennaceur et al. [1] used vision videos in group discussions to solicit as much feedback from the participants as possible. Darby et al. [2] produced a vision video to gather feedback on a visionary scenario from a group of stakeholders. ...
... In the recent years, several researchers [1]- [5] introduced vision videos into Requirements Engineering (RE) for soliciting feedback and stimulating discussions. According to Karras et al. [6,p. ...
... These videos are frequently used to solicit feedback and stimulate discussion in RE practices such as workshops and focus groups [13], [21], [22]. Although different researchers [1]- [4] reported on the benefits of vision videos for soliciting feedback and stimulating discussions in group or individual meetings, they seldom provide details about the quantity and content of the feedback. Bennaceur et al. [1] used vision videos in group discussions to solicit as much feedback from the participants as possible. ...
... Although different researchers [1]- [4] reported on the benefits of vision videos for soliciting feedback and stimulating discussions in group or individual meetings, they seldom provide details about the quantity and content of the feedback. Bennaceur et al. [1] used vision videos in group discussions to solicit as much feedback from the participants as possible. Darby et al. [2] produced a vision video to gather feedback on a visionary scenario from a group of stakeholders. ...
Vision videos are established for soliciting feedback and stimulating discussions in requirements engineering (RE) practices, such as focus groups. Different researchers motivated the transfer of these benefits into crowd-based RE (CrowdRE) by using vision videos on social media platforms. So far, however, little research explored the potential of using vision videos for CrowdRE in detail. In this paper, we analyze and assess this potential, in particular, focusing on video comments as a source of feedback. In a case study, we analyzed 4505 comments on a vision video from YouTube. We found that the video solicited 2770 comments from 2660 viewers in four days. This is more than 50% of all comments the video received in four years. Even though only a certain fraction of these comments are relevant to RE, the relevant comments address typical intentions and topics of user feedback, such as feature request or problem report. Besides the typical user feedback categories, we found more than 300 comments that address the topic safety, which has not appeared in previous analyses of user feedback. In an automated analysis, we compared the performance of three machine learning algorithms on classifying the video comments. Despite certain differences, the algorithms classified the video comments well. Based on these findings, we conclude that the use of vision videos for CrowdRE has a large potential. Despite the preliminary nature of the case study, we are optimistic that vision videos can motivate stakeholders to actively participate in a crowd and solicit numerous of video comments as a valuable source of feedback.
... Feed me, Feed me was created by Bennaceur et al. [19]. It is an IoT-based ecosystem to support food security, ensure sufficient, safe, and nutrition food to the global population. ...
Adaptive systems react to changes in their environment by changing their behavior. Identifying these needed adaptations is very difficult, but central to requirements elicitation for adaptive systems. As the necessary or potential adaptations are typically not obvious to the stakeholders, the problem is how to effectively elicit adaptation-relevant information. One approach is to use creativity techniques to support the systematic identification and elicitation of adaptation requirements. In particular, here, we analyze a set of creativity triggers defined for systematic exploration of potential adaptation requirements. We compare these triggers with brainstorming as a baseline in a controlled experiment with 85 master students. The results indicate that the proposed triggers are suitable for the efficient elicitation of adaptive requirements and that the 15 trigger questions produce significantly more requirements fragments than solo brainstorming.
... • We analyze the meta-information of the 11 exemplars of the RoboMAX repository and provide an outlook of potential uses of the robotic mission adaptation exemplars. Similar to the 'Feed Me, Feed Me' IoT exemplar [12], our RoboMAX exemplars provide the high-level requirements and key contextual information associated with the considered systems and their adaptation concerns. In this way, our repository serves a different purpose than, and complements, existing SEAMS exemplars, which provide simulators for simple robotics applications (UNDERSEA [13], Dragonfly [14] and DARTSim [15]) or generic frameworks for developing selfadaptive cyber-physical applications (DEECo [16], Intelligent Ensembles [17]), or datasets (AMELIA [18]). ...
... We consider different stakeholders, including shoppers, the supermarket, and the government. This is motivated by the Feed Me Feed Me exemplar and uses its terminology [38]. A shopping system of a supermarket supports searching items, adding/removing items to/from the shopping basket and later, checking out the basket. ...
... We demonstrated how these models can be built and how they contribute to overcoming challenges in maintaining fairness requirements' satisfaction. We are now extending our previous work [38] on resource-driven requirements adaptation to support the satisfaction of changing fairness requirements, and to suggest possible substitutions for resources that satisfice the stakeholders involved. ...
Software systems are increasingly making decisions on behalf of humans, raising concerns about the fairness of such decisions. Such concerns are usually attributed to flaws in algorithmic design or biased data, but we argue that they are often the result of a lack of explicit specification of fairness requirements. However, such requirements are challenging to elicit, a problem exacerbated by increasingly dynamic environments in which software systems operate, as well as stakeholders' changing needs. Therefore, capturing all fairness requirements during the production of software is challenging, and is insufficient for addressing software changes post deployment. In this paper, we propose adaptive fairness as a means for maintaining the satisfaction of changing fairness requirements. We demonstrate how to combine requirements-driven and resource-driven adaptation in order to address variabilities in both fairness requirements and their associated resources. Using models for fairness requirements, resources, and their relations, we show how the approach can be used to provide systems owners and end-users with capabilities that reflect adaptive fairness behaviours at runtime. We demonstrate our approach using an example drawn from shopping experiences of citizens. We conclude with a discussion of open research challenges in the engineering of adaptive fairness in human-facing software systems.
... The development Scenario-based in IoT is found in the study (S3) by Bennaceur et al. [9], which uses the technique called Con-traVision to obtain a wide spectrum of user reactions to potentially controversial or futuristic technologies. It includes an equal number of positive and negative scenarios and presents them to a group of people in order to help elicit requirements. ...
... The study (S3) by Bennaceur et al. [9], mentioned that, in IoT, the incomplete knowledge of the physical environment, the uncertainty of human behavior, the multitude of stakeholders, and changes in objectives make development challenging. Also, one needs to go beyond connectivity, and must ensure perfect and meaningful collaboration. ...
