@inproceedings{nokey,
title = {An ontology-based meta-modelling approach for software test cases},
author = {Nehemiah Mung’au and Emanuele Laurenzi},
url = {https://ceur-ws.org/Vol-3804/paper6o.pdf},
year  = {2024},
date = {2024-09-11},
booktitle = {BIR-WS 2024: BIR 2024 Workshops and Doctoral Consortium, 23rd International Conference on Perspectives in Business Informatics Research (BIR 2024)},
abstract = {Software testing plays a crucial role in the software development lifecycle, ensuring the reliability and quality of software programs. Despite the advancements in the field, software test cases still suffer of poor specifications, leading to communication issues, inefficiencies, and increased costs. This study investigates the suitability of an ontology-based meta-modelling approach, aiming to support the design of adequate software test cases. The approach promotes the human and machine-interpretability of domain-specific models representing the software test cases. This has the advantage of using automated reasoning services to support the creation of adequate test cases. A new domain-specific modelling language, ontoST, has been developed and implemented in the tool AOAME4STC for the proof of concept.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@inproceedings{nokey,
title = {Semantically annotated learning paths},
author = {Charline Unternährer, Knut Hinkelmann, Sandra Schlick},
url = {https://ceur-ws.org/Vol-3514/short67.pdf},
year  = {2023},
date = {2023-09-13},
urldate = {2023-09-13},
booktitle = {BIR-WS 2023: BIR 2023 Workshops and Doctoral Consortium, 22nd International Conference on Perspectives in Business Informatics Research (BIR 2023)},
address = {Ascoli Piceno, Italy},
abstract = {This paper shows an application of semantic lifting in the education domain. We present a metamodel
for graphical representation of learning paths. This supports lecturers in the design of courses and
learners to navigate through learning object to achieve their learning goals. The graphical models are
semantically annotated with an ontology representing the content of the course and the learning objects.
This enables reasoning for identifying learning objects dealing with specific topics and courses dealing
with prerequisite knowledge. The approach is realized in ADOxx and validated with courses and lectures
at a university of applied sciences in Switzerland.},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
@inbook{Laurenzi2022,
title = {BPMN4MoPla: Mobility Planning Based on Business Decision-Making},
author = {Emanuele Laurenzi and Oliver Ruggli and Alta Merwe},
editor = {Dimitris Karagiannis and Moonkun Lee and Knut Hinkelmann and Wilfrid Utz},
url = {https://doi.org/10.1007/978-3-030-93547-4_27},
doi = {10.1007/978-3-030-93547-4_27},
isbn = {978-3-030-93547-4},
year  = {2022},
date = {2022-01-01},
booktitle = {Domain-Specific Conceptual Modeling: Concepts, Methods and ADOxx Tools},
pages = {617–638},
publisher = {Springer International Publishing},
address = {Cham},
abstract = {This chapter presents a domain-specific modelling language, BPMN4MoPla, which extends the standard BPMN for the purpose of supporting business decision-making in mobility planning. Specifically, requirements for robotic car movements were derived and used for the modelling language extension. To achieve greater support of decision-making in mobility planning, the new modelling method was implemented as a cyber-physical system. Validation of the method was carried out in two complementary ways: (1) with respect to the extended language by modelling a mobility plan use case with BPMN4MoPla and (2) with respect to the expected execution behaviour by transforming and then executing the BPMN4MoPla model in two different modelling environments widely used in research and industry, respectively.},
keywords = {},
pubstate = {published},
tppubtype = {inbook}
}
@inbook{Hinkelmann2016,
title = {Business Process Flexibility and Decision-Aware Modeling—The Knowledge Work Designer},
author = {Knut Hinkelmann},
editor = {Dimitris Karagiannis and Heinrich C. Mayr and John Mylopoulos},
url = {https://doi.org/10.1007/978-3-319-39417-6_18},
doi = {10.1007/978-3-319-39417-6_18},
isbn = {978-3-319-39417-6},
year  = {2016},
date = {2016-01-01},
booktitle = {Domain-Specific Conceptual Modeling: Concepts, Methods and Tools},
pages = {397–414},
publisher = {Springer International Publishing},
address = {Cham},
abstract = {This chapter describes the Knowledge Work Designer, a modeling method for knowledge work. It is based on two principles: (1) the separation of business logic and process logic and (2) the support of both structures and unstructured knowledge. Process logic can be represented in a structured way in BPMN and in a nonstructured way with CMMN. For real processes there is no strict separation between structured processes and cases. Therefore, the Knowledge Work Designer offers a deep integration of BPMN and CMMN. Business logic can be represented in a structured way using decision tables. Unstructured business logic can be represented in documents. The separation of business logic and process logic allows for simpler process model and easier maintenance.},
keywords = {},
pubstate = {published},
tppubtype = {inbook}
}