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Mobile Testing Framework Exploiting Machine Learning and NLP

Ayda Tanik

Mobile Testing Framework Exploiting Machine Learning and NLP.

Rel. Luca Ardito, Maurizio Morisio, Riccardo Coppola. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2021

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Android UI testing is an essential task for testing user interaction with the user interface of the android application while developing an android application. Since users interact with the user interface for executing the desired tasks when using an android app, the role of the UI testing is to ensure every function and UI element are working as expected. UI testing guarantees the usability, accessibility, and consistency of apps. However, UI testing can be a costly and time-consuming job with repetitive tasks for developers. The automated android framework can be implemented for solving these issues. When a developer implements an android application, generally the developer follows some design and functional patterns. Based on this information and some features, applications can be categorized, and also similar activity types can be combined together according to some structural behaviors. The main goal is the thesis to create an Android Testing Framework that is providing a user to write simple and adaptive test scripts and can be re-used in apps that have similar characteristics code level without changing test scripts structure. The Android Testing Framework ensures the reuse of existing test scripts for the same type of application and activity category. Thanks to machine learning and NLP, Android application categories and activity were classified by supporting machine learning algorithms and natural language processing. To sum up, The framework can execute UI testing and can be reused at a similar code level of apps by writing simple human-readable test scripts.

Relators: Luca Ardito, Maurizio Morisio, Riccardo Coppola
Academic year: 2020/21
Publication type: Electronic
Number of Pages: 96
Corso di laurea: Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering)
Classe di laurea: New organization > Master science > LM-32 - COMPUTER SYSTEMS ENGINEERING
Aziende collaboratrici: UNSPECIFIED
URI: http://webthesis.biblio.polito.it/id/eprint/19106
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