Bug benchmarks are used in development and evaluation of debugging approaches, eg
fault localization and automated repair. Quantitative performance comparison of different …

Robotics and autonomy systems are becoming increasingly important, moving from
specialised factory domains to increasingly general and consumer-focused applications. As …

Mobile devices are significantly complex, feature-rich, and heavily customized, thus they are
prone to software reliability and performance issues. This paper considers the problem of …

Context: Software aging refers to the phenomenon of performance degradation, increasing
failure rate, or system crash due to resource consumption and error accumulation in …

In long running systems, software tends to encounter performance degradation and
increasing failure rate during execution. This phenomenon has been named software aging …

The impact of software bugs on today's system failures is of primary concern. Many bugs are
detected and removed during testing, while others do not show up easily at development …

Deep learning frameworks play a key rule to bridge the gap between deep learning theory
and practice. With the growing of safety-and security-critical applications built upon deep …

Android has become the most popular mobile OS, as it enables device manufacturers to
introduce customizations to compete with value-added services. However, customizations …

TensorFlow is one of the most popular machine learning frameworks for developing
machine learning algorithms. Because of the popularity and large-scale use of TensorFlow …

Software test flakiness is drawing increasing interest among both academic researchers and
practitioners. In this work we report our findings from a scoping review of white and grey …