Software fault localization, the act of identifying the locations of faults in a program, is widely
recognized to be one of the most tedious, time consuming, and expensive-yet equally critical …

Despite the numerous static and dynamic program analysis techniques in the literature, data
races remain one of the most common bugs in modern concurrent software. Further, the …

This chapter describes traditional and intuitive fault localization techniques, including
program logging, assertions, breakpoints, and profiling. Many advanced fault localization …

Data races are among the most reliable indicators of programming errors in concurrent
software. For at least two decades, Lamport's happens-before (HB) relation has served as …

Testing multithreaded programs is a hard problem, because it is challenging to expose
those rare interleavings that can trigger a concurrency bug. We propose a new thread …

Concurrency bugs are extremely difficult to detect. Recently, several dynamic techniques
achieve sound analysis. M2 is even complete for two threads. It is designed to decide …

While current bug detection techniques for concurrent software focus on unearthing low-
level issues such as data races or deadlocks, they often fall short of discovering more …

Concurrent programs are notoriously hard to write correctly, as scheduling nondeterminism
introduces subtle errors that are both hard to detect and to reproduce. The most common …

Causality inference, such as dynamic taint anslysis, has many applications (eg, information
leak detection). It determines whether an event e is causally dependent on a preceding …

Writing concurrent programs is highly error-prone due to the nondeterminism in interprocess
communication. The most reliable indicators of errors in concurrency are data races, which …