TU Darmstadt / ULB / TUbiblio

Monkey see, monkey do: effective generation of GUI tests with inferred macro events

Ermuth, Markus ; Pradel, Michael (2016)
Monkey see, monkey do: effective generation of GUI tests with inferred macro events.
Saarbrücken, Germany
doi: 10.1145/2931037.2931053
Conference or Workshop Item, Bibliographie

Abstract

Automated testing is an important part of validating the behavior of software with complex graphical user interfaces, such as web, mobile, and desktop applications. Despite recent advances in UI-level test generation, existing approaches often fail to create complex sequences of events that represent realistic user interactions. As a result, these approaches cannot reach particular parts of the application under test, which then remain untested. This paper presents a UI-level test generation approach that exploits execution traces of human users to automatically create complex sequences of events that go beyond the recorded traces. The key idea is to infer so-called macro events, i.e., sequences of low-level UI events that correspond to a single logical step of interaction, such as choosing an item of a drop-down menu or filling and submitting a form. The approach builds upon and adapts well-known data mining techniques, in particular frequent subsequence mining and inference of finite state machines. We implement the approach for client-side web applications and apply it to four real-world applications. Our results show that macro-based test generation reaches more pages, exercises more usage scenarios, and covers more code within a fixed testing budget than a purely random test generator.

Item Type: Conference or Workshop Item
Erschienen: 2016
Creators: Ermuth, Markus ; Pradel, Michael
Type of entry: Bibliographie
Title: Monkey see, monkey do: effective generation of GUI tests with inferred macro events
Language: German
Date: July 2016
Publisher: ACM
Issue Number: 25
Book Title: ISSTA 2016 Proceedings of the 25th International Symposium on Software Testing and Analysis
Event Location: Saarbrücken, Germany
DOI: 10.1145/2931037.2931053
Abstract:

Automated testing is an important part of validating the behavior of software with complex graphical user interfaces, such as web, mobile, and desktop applications. Despite recent advances in UI-level test generation, existing approaches often fail to create complex sequences of events that represent realistic user interactions. As a result, these approaches cannot reach particular parts of the application under test, which then remain untested. This paper presents a UI-level test generation approach that exploits execution traces of human users to automatically create complex sequences of events that go beyond the recorded traces. The key idea is to infer so-called macro events, i.e., sequences of low-level UI events that correspond to a single logical step of interaction, such as choosing an item of a drop-down menu or filling and submitting a form. The approach builds upon and adapts well-known data mining techniques, in particular frequent subsequence mining and inference of finite state machines. We implement the approach for client-side web applications and apply it to four real-world applications. Our results show that macro-based test generation reaches more pages, exercises more usage scenarios, and covers more code within a fixed testing budget than a purely random test generator.

Uncontrolled Keywords: GUI testing, test generation, JavaScript, web applications
Identification Number: TUD-CS-2016-14767
Divisions: Profile Areas
Profile Areas > Cybersecurity (CYSEC)
Date Deposited: 14 Aug 2017 11:28
Last Modified: 12 Jan 2019 21:20
PPN:
Export:
Suche nach Titel in: TUfind oder in Google
Send an inquiry Send an inquiry

Options (only for editors)
Show editorial Details Show editorial Details