From text to visual BPMN process models

Ivanchikj, Ana; Serbout, Souhaila; Pautasso, Cesare

doi:10.1145/3365438.3410990

Cited by 17 publications

(14 citation statements)

References 21 publications

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“…The results presented in detail in [31] already indicated an acceptable level of usability (based on the answers to the stan- dard SUS survey collected from 30 participants). In Fig.…”

Section: System Usability Scalementioning

confidence: 84%

“…In this section, we summarize the main findings of the usability and learnability evaluation presented in [31]. In addition, complementing those quantitative results, Table 4 highlights some of the qualitative feedback about the tool which was spontaneously and anonymously submitted by its users over the past two years.…”

Section: Usability and Learnability Evaluation Summarymentioning

confidence: 98%

“…Fig. 1 BPMN Sketch Miner with the textual and visual BPMN representation of the process modeled during the user study of [31]. To make it easier to read, click here for opening the diagram in the tool -boundary events use their own type annotations, which are related to the corresponding event type.…”

Section: Design Decisionsmentioning

confidence: 99%

“…The approach supported only a very small number of BPMN constructs (start/end event, XOR gateway, task, and sequence flow BPMN constructs) and lacked the modeling annotations necessary to distinguish different types of tasks and events, pools, message flow, etc. The tool presented in [31], as well as in this article, is based on process mining [65], and such provides access to the core constructs of the BPMN without requiring an explicit description of the process control flow, e.g., when the PlantUML textual syntax for activity diagrams. On the other hand, it provides a much more expressive DSL compared to the one we presented in [30] by combining the process mining with textual modeling.…”

Section: From Text To Visual Process Modelsmentioning

confidence: 99%

“…The evaluation of the usability and learnability of the tool was originally published in [31]. 7 We conducted a user study and surveys [33] involving students having no prior knowledge of the BPMN language, as well as industry analysts, with advanced BPMN knowledge, who typically enjoy working with "quick modeling" shortcuts as they need to, as mentioned by one of them, "represent the content of their processes without having to fiddle with the graphical layout."…”

Section: Introductionmentioning

confidence: 99%

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Live process modeling with the BPMN Sketch Miner

2022

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BPMN Sketch Miner is a modeling environment for generating visual business process models starting from constrained natural language textual input. Its purpose is to support business process modelers who need to rapidly sketch visual BPMN models during interviews and design workshops, where participants should not only provide input but also give feedback on whether the sketched visual model represents accurately what has been described during the discussion. In this article, we present a detailed description of the BPMN Sketch Miner design decisions and list the different control flow patterns supported by the current version of its textual DSL. We also summarize the user study and survey results originally published in MODELS 2020 concerning the tool usability and learnability and present a new performance evaluation regarding the visual model generation pipeline under actual usage conditions. The goal is to determine whether it can support a rapid model editing cycle, with live synchronization between the textual description and the visual model. This study is based on a benchmark including a large number of models (1350 models) exported by users of the tool during the year 2020. The main results indicate that the performance is sufficient for a smooth live modeling user experience and that the end-to-end execution time of the text-to-model-to-visual pipeline grows linearly with the model size, up to the largest models (with 195 lines of textual description) found in the benchmark workload.

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“…The results presented in detail in [31] already indicated an acceptable level of usability (based on the answers to the stan- dard SUS survey collected from 30 participants). In Fig.…”

Section: System Usability Scalementioning

confidence: 84%

Section: Usability and Learnability Evaluation Summarymentioning

confidence: 98%

Section: Design Decisionsmentioning

confidence: 99%

Section: From Text To Visual Process Modelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Live process modeling with the BPMN Sketch Miner

2022

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A‐PGRD: Attention‐based automatic business process model generation from RPA process description

Zhu,

Liu,

et al. 2023

Concurrency and Computation

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SummaryRobotic process automation (RPA), a tool driven by business processes as the kernel, continues to heat up in the business community. However, process‐centric RPA modeling lacks an effective means. To address this problem, we propose a method for automatic process acquisition using RPA process descriptions as input. Existing deep learning process generation methods cannot be applied at the phrase level and have low accuracy at the sentence level. The proposed neural network method is based on an attention mechanism for automatic business process model generation from RPA process descriptions (A‐PGRD). The approach analyzes easily accessible and unstructured natural language text documents, constructs a non‐autoregressive neural network with an attention mechanism to retrieve the business process hierarchy, and generates a tree‐like business process graph using unsupervised automation. Through K‐fold cross‐validation, the method achieves an accuracy of 41.7% on the manually collected open‐source RPA business process dataset. Compared with the previous method, the method improves the learning efficiency by 23%–27%. The obtained results can be applied to the RPA tool to better optimize the business process and thus help organizations gain an edge over their competition.

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