ACAT: A novel machine-learning-based tool for automating android application testing

Ariel Rosenfeld, Odaya Kardashov, Orel Zang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations


Mobile applications are being used every day by more than half of the world’s population to perform a great variety of tasks. With the increasingly widespread usage of these applications, the need arises for efficient techniques to test them. Many frameworks allow automating the process of application testing, however existing frameworks mainly rely on the application developer for providing testing scripts for each developed application, thus preventing reuse of these tests for similar applications. In this demonstration, we present a novel tool for the automation of testing Android applications by leveraging machine learning techniques and reusing popular test scenarios. We discuss and demonstrate the potential benefits of our tool in an empirical study where we show it outperforms standard methods in realistic settings.

Original languageEnglish
Title of host publicationHardware and Software
Subtitle of host publicationVerification and Testing - 13th International Haifa Verification Conference, HVC 2017, Proceedings
EditorsRachel Tzoref-Brill, Ofer Strichman
PublisherSpringer Verlag
Number of pages4
ISBN (Print)9783319703886
StatePublished - 2017
Externally publishedYes
Event13th International Haifa Verification Conference, HVC 2017 - Haifa, Israel
Duration: 13 Nov 201715 Nov 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10629 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference13th International Haifa Verification Conference, HVC 2017

Bibliographical note

Publisher Copyright:
© Springer International Publishing AG 2017.


  • Activities classification
  • Android application testing
  • Demonstration
  • Mobile testing automation


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