Ing. Jan Blizničenko

Publikace

Combining Type Inference Techniques for Semi-Automatic UML Generation from Pharo Code

Rok
2024
Publikováno
Journal of Computer Languages. 2024, 82 ISSN 2590-1184.
Typ
Článek
Anotace
This paper explores how to reconstruct UML diagrams from dynamically typed languages such as Smalltalk, which do not use explicit type information. This lack of information makes traditional methods for extracting associations difficult. It addresses the need for automated techniques, particularly in legacy software systems, to facilitate their transformation into modern technologies, focusing on Smalltalk as a case study due to its extensive industrial legacy and modern adaptations like Pharo. We propose a way to create UML diagrams from Smalltalk code, focusing on using type inference to determine UML associations. For optimal outcomes for large-scale software systems, we recommend combining different type inference methods in an automatic or semi-automatic way.

Towards Modularity in Live Visual Modeling: A case-study with OpenPonk and Kendrick

Autoři
Blizničenko, J.; Papoulias, N.; Pergl, R.; Stinckwich, S.
Rok
2017
Publikováno
IWST '17: Proceedings of the 12th edition of the International Workshop on Smalltalk Technologies. New York: ACM, 2017. ISBN 978-1-4503-5554-4.
Typ
Stať ve sborníku
Anotace
Aspects of live-programming that have originated with Lisp and Smalltalk systems have recently seen a renewed research and industrial interest due to their educational and productivity potential (Live workshops at ECOOP, ICSE, and SPLASH, live facilities for the .Net, Java, Python, and Swift platforms). Especially in the case of visual modeling and simulation tools that are used by experts outside Informatics (such as ecologists, biologists, economists, epidemiologists, ...), this constant-feedback loop that live-systems provide can ease the development and comprehension of complex systems, via truly explorable environments. Unfortunately, taking the domain of Epidemiology as a case-study, we observe that the visual component of such systems have no notion of modularity and thus exploration is limited only to small monolithic examples. In order to address this issue we propose a model for modular visual exploration. This model is based on an extension of the OpenPonk platform targeting the Kendrick epidemiological language. Through this model we were able to map the separation of concerns of the Kendrick DSL, in a live visual notation that supports modularity and exploration of part-whole hierarchies.