22,715 research outputs found
How Developers Use Data Race Detection Tools
Developers need help with multithreaded programming. We investigate how two program analysis tools are used by de-velopers at Google: THREADSAFETY, an annotation-based static data race analysis, and TSAN, a dynamic data race de-tector. The data was collected by interviewing seven veteran industry developers at Google, and provides unique insight into how four different teams use tooling in different ways to help with multithreaded programming. The result is a collec-tion of perceived pros and cons of using THREADSAFETY and TSAN, as well as general issues with multithreading
A Study of Concurrency Bugs and Advanced Development Support for Actor-based Programs
The actor model is an attractive foundation for developing concurrent
applications because actors are isolated concurrent entities that communicate
through asynchronous messages and do not share state. Thereby, they avoid
concurrency bugs such as data races, but are not immune to concurrency bugs in
general. This study taxonomizes concurrency bugs in actor-based programs
reported in literature. Furthermore, it analyzes the bugs to identify the
patterns causing them as well as their observable behavior. Based on this
taxonomy, we further analyze the literature and find that current approaches to
static analysis and testing focus on communication deadlocks and message
protocol violations. However, they do not provide solutions to identify
livelocks and behavioral deadlocks. The insights obtained in this study can be
used to improve debugging support for actor-based programs with new debugging
techniques to identify the root cause of complex concurrency bugs.Comment: - Submitted for review - Removed section 6 "Research Roadmap for
Debuggers", its content was summarized in the Future Work section - Added
references for section 1, section 3, section 4.3 and section 5.1 - Updated
citation
On Modeling the Costs of Censorship
We argue that the evaluation of censorship evasion tools should depend upon
economic models of censorship. We illustrate our position with a simple model
of the costs of censorship. We show how this model makes suggestions for how to
evade censorship. In particular, from it, we develop evaluation criteria. We
examine how our criteria compare to the traditional methods of evaluation
employed in prior works
Understanding Android Obfuscation Techniques: A Large-Scale Investigation in the Wild
In this paper, we seek to better understand Android obfuscation and depict a
holistic view of the usage of obfuscation through a large-scale investigation
in the wild. In particular, we focus on four popular obfuscation approaches:
identifier renaming, string encryption, Java reflection, and packing. To obtain
the meaningful statistical results, we designed efficient and lightweight
detection models for each obfuscation technique and applied them to our massive
APK datasets (collected from Google Play, multiple third-party markets, and
malware databases). We have learned several interesting facts from the result.
For example, malware authors use string encryption more frequently, and more
apps on third-party markets than Google Play are packed. We are also interested
in the explanation of each finding. Therefore we carry out in-depth code
analysis on some Android apps after sampling. We believe our study will help
developers select the most suitable obfuscation approach, and in the meantime
help researchers improve code analysis systems in the right direction
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