## 2 Related Works
### The Research Gap  
Making service composition easy is still a challenging endeavor [61; 62], requiring further research to understand the obstacles encountered by end-users when composing services. Two recent surveys of service composition by non-programmers revealed insightful motivations for carrying out our research [19; 63]. [PERSON] et al. [63] surveyed more than 165 EUD papers, spanning from 2000 until 2017, and found that approximately 50% of those papers used the component-based technique to build software. In this context, components refer to modular units of software, such as web services and mashups. More importantly, [PERSON] et al. [63] suggested, as a primary research direction, to conduct comparative studies of EUD approaches and highlighted the need for further research to investigate EUD activities so as to guide the design of future tools. The second survey on user studies evaluated tools and approaches of service composition and showed their shortcomings with respect to the evaluation methodologies used, which subjected the findings to scientific scrutiny [19]. The coverage spanned from 2005 until 2018, yet only 47 end-user studies of service composition were reported. Moreover, only 23% of the surveyed EUD studies were confirmatory in nature, necessitating additional confirmatory studies to test the previous research claims. Contrary to the common belief, recent user studies [18; 23] showed that the technical background of users did not improve service composition performance and perception of ease of use. In a bid to eliminate programming difficulty, [PERSON] et al. [23] described a lightweight service mashup platform for creating telecommunication mashup-based compositions easily through a web browser where data and event flows could be defined. The approach was based on various standardised models, such as Service Data Model, Service Creation Model, and Service Execution Model. The evaluation of this composition platform showed no difference in the composition scores between programmers and non-programmers. Additionally, there have been other inconclusive observations about the differences in service composition between technical and non-technical users [12]. Moreover, there are various UI-based approaches aimed at helping end-users to compose services and objects in an easier manner, but the results are still inconclusive. [PERSON] et al. [64], for instance, presented a jigsaw puzzle approach to create transformations and links between services and Internet of Things objects for non-programmers. These transformations form the basis of executable workflows which are generated automatically. Evaluation results showed that non-programmers were able to define the compositions successfully. However, [PERSON] et al. [18] described a WYSIWYG UI-based composition platform to glue multiple services together. In this approach, UI components are used as the building blocks of the mashups. Surprisingly, the non-programmers' performance was not statistically worse than the programmers with respect to a variety of composition tasks. Both groups also showed similar perception of ease of use towards the UI-based approach. Trigger Action programming frameworks, such as IFTTT and Zapier, are gaining rapid popularity [65]. However, striking a balance between expressivity and usability is still an open issue for these types of frameworks. To that end, [PERSON] et al. [15] proposed a recommender system to suggest trigger-action rules to the end-user during their mashups and service composition. Yet the efficiency of creating conditional processes by end-users has still not been investigated. Strikingly, only three service composition studies have attempted to discover the conceptual issues within composition approaches [19]. This calls for further research efforts. This research comes as an attempt to elaborate and conduct a sound study to test and confirm the existing service composition observations. Our user study conforms to the guidelines of the evaluation framework proposed by [PERSON] et al.