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Video as a By-Product of Digital Prototyping: Capturing the Dynamic Aspect of Interaction
Software Engineering · Submitted 1 Aug 2017
abstract compiled · 2026-09-23 · no language-model review
The authors' main claim A first evaluation showed that such a generated video supports a faster understanding of a textual scenario compared to static mockups.
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The paper's own sentences, arranged. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.
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The abstract, sentence by sentence
Requirements engineering provides several practices to analyze how a user wants to interact with a future software. Mockups, prototypes, and scenarios are suitable to understand usability issues and user requirements early. Nevertheless, users are often dissatisfied with the usability of a resulting software. Apparently, previously explored information was lost or no longer accessible during the development phase. Scenarios are one effective practice to describe behavior. However, they are commonly notated in natural language which is often improper to capture and communicate interaction knowledge comprehensible to developers and users. The dynamic aspect of interaction is lost if only static descriptions are used. Digital prototyping enables the creation of interactive prototypes by adding responsive controls to hand- or digitally drawn mockups. We propose to capture the events of these controls to obtain a representation of the interaction. From this data, we generate videos, which demonstrate interaction sequences, as additional support for textual scenarios. Variants of scenarios can be created by modifying the captured event sequences and mockups. Any change is unproblematic since videos only need to be regenerated. Thus, we achieve video as a by-product of digital prototyping. This reduces the effort compared to video recording such as screencasts. A first evaluation showed that such a generated video supports a faster understanding of a textual scenario compared to static mockups.
background contribution method result interpretation main claim
| # | sentence | role | the authors' own work | states the main conclusion | strength |
|---|---|---|---|---|---|
| s0 | Requirements engineering provides several practices to analyze how a user wants to interact with a future software. | background 1.00 | 0.04 | 0.02 | asserted 1.00 |
| s1 | Mockups, prototypes, and scenarios are suitable to understand usability issues and user requirements early. | background 1.00 | 0.06 | 0.02 | asserted 0.86 |
| s2 | Nevertheless, users are often dissatisfied with the usability of a resulting software. | background 0.91 | 0.07 | 0.02 | asserted 0.93 |
| s3 | Apparently, previously explored information was lost or no longer accessible during the development phase. | background 0.50 | 0.08 | 0.02 | asserted 0.42 |
| s4 | Scenarios are one effective practice to describe behavior. | background 1.00 | 0.07 | 0.02 | asserted 0.99 |
| s5 | However, they are commonly notated in natural language which is often improper to capture and communicate interaction knowledge comprehensible to developers and users. | background 0.76 | 0.07 | 0.02 | asserted 0.87 |
| s6 | The dynamic aspect of interaction is lost if only static descriptions are used. | background 0.74 | 0.08 | 0.03 | asserted 0.99 |
| s7 | Digital prototyping enables the creation of interactive prototypes by adding responsive controls to hand- or digitally drawn mockups. | background 0.51 | 0.11 | 0.04 | asserted 1.00 |
| s8 | We propose to capture the events of these controls to obtain a representation of the interaction. | method 0.66 | 0.64 | 0.08 | asserted 0.82 |
| s9 | From this data, we generate videos, which demonstrate interaction sequences, as additional support for textual scenarios. | method 0.78 | 0.92 | 0.18 | asserted 1.00 |
| s10 | Variants of scenarios can be created by modifying the captured event sequences and mockups. | method 0.91 | 0.61 | 0.06 | asserted 0.95 |
| s11 | Any change is unproblematic since videos only need to be regenerated. | method 0.58 | 0.41 | 0.08 | asserted 1.00 |
| s12 | Thus, we achieve video as a by-product of digital prototyping. | contribution 0.84 | 0.83 | 0.39 | asserted 1.00 |
| s13 | This reduces the effort compared to video recording such as screencasts. | interpretation 0.44 | 0.47 | 0.12 | asserted 1.00 |
| s14 | A first evaluation showed that such a generated video supports a faster understanding of a textual scenario compared to static mockups. | result 1.00 | 0.94 | 0.31 | asserted 0.96 |
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The paper
Original abstract
Requirements engineering provides several practices to analyze how a user wants to interact with a future software. Mockups, prototypes, and scenarios are suitable to understand usability issues and user requirements early. Nevertheless, users are often dissatisfied with the usability of a resulting software. Apparently, previously explored information was lost or no longer accessible during the development phase. Scenarios are one effective practice to describe behavior. However, they are commonly notated in natural language which is often improper to capture and communicate interaction knowledge comprehensible to developers and users. The dynamic aspect of interaction is lost if only static descriptions are used. Digital prototyping enables the creation of interactive prototypes by adding responsive controls to hand- or digitally drawn mockups. We propose to capture the events of these controls to obtain a representation of the interaction. From this data, we generate videos, which demonstrate interaction sequences, as additional support for textual scenarios. Variants of scenarios can be created by modifying the captured event sequences and mockups. Any change is unproblematic since videos only need to be regenerated. Thus, we achieve video as a by-product of digital prototyping. This reduces the effort compared to video recording such as screencasts. A first evaluation showed that such a generated video supports a faster understanding of a textual scenario compared to static mockups.
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