Android apps are GUI-based event-driven software and have become
ubiquitous in recent years. Obviously, functional correctness is critical for an app's success.
However, in addition to crash bugs, \emph{non-crashing functional bugs} (in short as ``non-crashing bugs'' in this work) like inadvertent function failures, silent user data lost and incorrect display information are prevalent, even in popular, well-tested apps.
These non-crashing functional bugs are usually caused by program logic errors and manifest themselves on the graphic user interfaces (GUIs).
In practice, such bugs pose significant challenges in
effectively detecting them because (1) current practices heavily rely on
expensive, small-scale manual validation (\emph{the lack of
automation}); and (2) modern \emph{fully automated} testing has been limited to
crash bugs (\emph{the lack of test oracles}).

This paper fills this gap by introducing \emph{independent view fuzzing},
\emph{a novel, fully automated approach} for detecting non-crashing functional bugs in Android apps.
Inspired by metamorphic testing, our key insight is to leverage the commonly-held \emph{independent view
property} of Android apps to manufacture property-preserving mutant
tests from a set of seed tests that validate certain app properties.
The mutated tests help exercise the tested apps under additional, adverse
conditions. Any property violations indicate likely functional bugs for further manual confirmation.
We have realized our approach as an automated, end-to-end functional
fuzzing tool, Genie. Given an app, (1) Genie automatically
detects non-crashing bugs without
requiring human-provided tests and oracles (thus
\emph{fully automated}); and (2) the detected non-crashing bugs are
diverse (thus \emph{general and not limited to specific functional
properties}), which set Genie apart from prior work.

We have evaluated Genie on 12 real-world Android
apps and successfully uncovered 34 previously unknown non-crashing bugs
in their latest releases — all have been confirmed, and 22 have
already been fixed. Most of the detected bugs are nontrivial and have
escaped developer (and user) testing for at least one year and
affected many app releases, thus clearly demonstrating Genie's effectiveness.
According to our analysis, Genie achieves a reasonable true positive rate of 40.9%, while these 34 non-crashing bugs could not be detected by prior fully automated GUI testing tools (as our evaluation confirms).
Thus, our work complements and enhances
existing manual testing and fully automated testing for crash bugs.