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Pathways for statically mining the Model-View-Controller software architecture on mobile applications

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Abstract

In the last few years, we have seen an increase in the number of mobile applications and their usage. The architectural pattern and correctness represent a major factor in the success of a mobile project and its lifecycle. Since architectural patterns can not be imposed on a codebase without an external validation system, we are proposing a novel technique for automatically analysing one of the most commonly used presentational architectural pattern Model-View-Controller (MVC). Our system analyses and detects architectural issues by leveraging information obtain from Software Development Kits (SDKs). For the evaluation of our proposal, we have focused on mobile codebases (private and open source), most specifically on the iOS platform. However, our findings can be extrapolated to other platforms which use SDKs for building their user interfaces (UI).

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Data Availability

Enquiries about data availability should be directed to the authors.

Notes

  1. https://www.jpsim.com/uncovering-sourcekit/.

  2. https://raw.githubusercontent.com/dobreandl/macs/master/apple-object-scanning.txt.

  3. https://github.com/dobreandl/wrong-dependencies-example/tree/master.

  4. The consensus regards the component’s role that could be reflected by the component’s name or component’s functions; the two developers have agreed that the component’s name has the main impact.

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Acknowledgements

We thank the reviewers whose suggestions helped improve and clarify this manuscript. We also thank the two senior developers that constructed the ground truth by manually inspecting each component of the codebases used in the first iteration of our analysis [published in Dobrean and Dioşan (2019)] and of the supplementary codebases used in our extended analysis performed in the current paper.

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The authors have not disclosed any funding.

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Authors and Affiliations

  1. Computer Science Department, Babes Bolyai University, luj-Napoca, Romania

    Dragoş Dobrean

  2. Computer Science Department, Babes Bolyai University, Cluj-Napoca, Romania

    Laura Dioşan

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  1. Dragoş Dobrean
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Correspondence to Dragoş Dobrean.

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Dobrean, D., Dioşan, L. Pathways for statically mining the Model-View-Controller software architecture on mobile applications. Soft Comput 26, 10493–10511 (2022). https://doi.org/10.1007/s00500-022-06908-0

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