Community Detection in Model-based Testing to Address Scalability: Study Design

• Autorzy: Silistre Alper , Kilincceker Onur , Belli Fevzi , Challenger Moharram , Kardaş Geylani

Identyfikatory

DOI

10.15439/2020F163

• Konferencja: Federated Conference on Computer Science and Information Systems (15 ; 06-09.09.2020 ; Sofia, Bulgaria)
• Języki publikacji: EN

Abstrakty

EN

Model-based GUI testing has achieved widespread recognition in academy thanks to its advantages compared to code-based testing due to its potentials to automate testing and the ability to cover bigger parts more efficiently. In this study design paper, we address the scalability part of the model-based GUI testing by using community detection algorithms. A case study is presented as an example of possible improvements to make a model-based testing approach more efficient. We demonstrate layered ESG models as an example of our approach to consider the scalability problem. We present rough calculations with expected results, which show 9 times smaller time and space units for 100 events ESG model when a community detection algorithm is applied.

Słowa kluczowe

EN

graphical user interfaces; program testing; ESG model; scalability

PL

graficzny interfejs użytkownika; testowanie programu; Model ESG; skalowalność

• Wydawca: Polskie Towarzystwo Informatyczne
• Czasopismo: Annals of Computer Science and Information Systems
• Rocznik: 2020
• Tom: Vol. 21
• Strony: 657--660
• Opis fizyczny: Bibliogr. 21 poz., il.

Twórcy

autor

Silistre Alper

• International Computer Institute, Ege University, Izmir, Turkey

autor

Kilincceker Onur

• University of Paderborn, Paderborn, Germany. Mugla Sitki Kocman University, Mugla, Turkey

autor

Belli Fevzi

• University of Paderborn, Paderborn, Germany. Izmir Institute of Technology, Izmir, Turkey

autor

Challenger Moharram

• University of Antwerp and Flanders Make, Belgium

autor

Kardaş Geylani

• International Computer Institute, Ege University, Izmir, Turkey

Bibliografia

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Uwagi

1. Track 5: Software and System Engineering

2. Technical Session: Advances in Software and System Engineering

3. Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).