Improving Software Reliability for Event-Driven Mobile Systems

Mobile platforms commonly support an event-driven model of concurrent programming. In an
event-driven system, the flow of a program is controlled by asynchronous events. Events processed sequentially
in the same thread can be logically concurrent to each other, as they may not be ordered by any programmerspecified
ordering operations. The lack of programmer-defined order between multiple noninterchangeable
concurrent events "” that is, only certain execution orders between these events yields correct results "” leads
to a new class of atomicity violation and order violation bugs in event-driven programs.
Unfortunately, the state of the art for detecting concurrency errors in event-driven systems is significantly
weaker than that in traditional thread-based systems. This thesis aims to fill this important gap by developing
models, algorithms and tools that aid programmers to analyze and diagnose event-driven programs to improve
software reliability. Specifically, this thesis presents the following three techniques to detect concurrency errors
in event-driven programs:
1. A new causality model for event-driven program is defined to infer ordering invariants between events
across different executions.
2. An efficient and scalable single-pass algorithm to identify concurrent asynchronous events that may lead to
concurrency errors.
3. A dynamic event precondition race detector to help programmers to detect and avoid a wide range of atomicity
violations and order violations.
The techniques we have developed are broadly applicable to a majority of event-driven platforms. To translate
our techniques into real-world impact, we develop a set of tools in the context of Android to help build up a
more robust and reliable platform for mobile computing.