Multi-threaded Testing with AOP Is Easy, and It Finds Bugs!

Copty, Shady; Ur, Shmuel

doi:10.1007/11549468_81

Cited by 18 publications

(17 citation statements)

References 10 publications

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“…AspectJ has been shown in earlier work to be well-suited for program-trace generation and infection detection in multithreaded programs [7]. AspectJ introduces additional overhead and execution slowdowns; we observed a typical increase in execution time between 50% and 100% for the programs used in our evaluation (see Section 5).…”

Section: Obtaining the Call Graphsmentioning

confidence: 66%

Localizing Defects in Multithreaded Programs by Mining Dynamic Call Graphs

Eichinger

Pankratius

Große

et al. 2010

Testing – Practice and Research Techniques

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Abstract. Writing multithreaded software for multicore computers confronts many developers with the difficulty of finding parallel programming errors. In the past, most parallel debugging techniques have concentrated on finding race conditions due to wrong usage of synchronization constructs. A widely unexplored issue, however, is that a wrong usage of non-parallel programming constructs may also cause wrong parallel application behavior. This paper presents a novel defect-localization technique for multithreaded shared-memory programs that is based on analyzing execution anomalies. Compared to race detectors that report just on wrong synchronization, this method can detect a wider range of defects affecting parallel execution. It works on a condensed representation of the call graphs of multithreaded applications and employs data-mining techniques to locate a method containing a defect. Our results from controlled application experiments show that we found race conditions, but also other programming errors leading to incorrect parallel program behavior. On average, our approach reduced in our benchmark the amount of code to be inspected to just 7.1% of all methods.

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Section: Obtaining the Call Graphsmentioning

confidence: 66%

Localizing Defects in Multithreaded Programs by Mining Dynamic Call Graphs

Eichinger

Pankratius

Große

et al. 2010

Testing – Practice and Research Techniques

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“…The MAP facilitates both static and dynamic deployment, but does not provide configurable and expressive dynamic scoping concepts. There are also approaches that extend AspectJ by modifying its sources to include more fine-grained join points [9].…”

Section: Related Workmentioning

confidence: 99%

“…A join point shadow is a code snippet placed at join points. It guides advice interaction through the weaving callback (9). Propagation shadows are code snippets that maintain the scope of aspects.…”

Section: The Meta-aspect Protocolmentioning

confidence: 99%

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A Meta-Aspect Protocol for Developing Dynamic Analyses

Achenbach

Ostermann

2010

Lecture Notes in Computer Science

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Abstract. Dynamic aspect-oriented programming has been widely used for the development of dynamic analyses to abstract over low-level program instrumentation. Due to particular feature requirements in different analysis domains like debugging or testing, many different aspect languages were developed from scratch or by extensive compiler or interpreter extensions. We introduce another level of abstraction in form of a meta-aspect protocol to separate the host language from the analysis domain. A language expert can use this protocol to tailor an analysisspecific aspect language, based on which a domain expert can develop a particular analysis. Our design enables a flexible specification of the join point model, configurability of aspect deployment and scoping, and extensibility of pointcut and advice language. We present the application of our design to different dynamic analysis domains.

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“…For example, one may use aspects to insert instrumentation at the beginning of all methods (possibly of a specific type), but cannot limit the instrumentation based on some attribute of the method. However, AOP has more recently also been shown to be useful in testing [52,53].…”

Section: Aspect-oriented Testingmentioning

confidence: 99%

An Extensible Open-Source Compiler Infrastructure for Testing

Quinlan

Vuduc

2006

Lecture Notes in Computer Science

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Testing forms a critical part of the development process for large-scale software, and there is growing need for automated tools that can read, represent, analyze, and transform the application's source code to help carry out testing tasks. However, the support required to compile applications written in common general purpose languages is generally inaccessible to the testing research community. In this paper, we report on an extensible, open-source compiler infrastructure called ROSE, which is currently in development at Lawrence Livermore National Laboratory. ROSE specifically targets developers who wish to build source-based tools that implement customized analyses and optimizations for large-scale C, C++, and Fortran90 scientific computing applications (on the order of a million lines of code or more). However, much of this infrastructure can also be used to address problems in testing, and ROSE is by design broadly accessible to those without a formal compiler background. This paper details the interactions between testing of applications and the ways in which compiler technology can aid in the understanding of those applications. We emphasize the particular aspects of ROSE, such as support for the general analysis of whole programs, that are particularly well-suited to the testing research community and the scale of the problems that community solves.

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Multi-threaded Testing with AOP Is Easy, and It Finds Bugs!

Cited by 18 publications

References 10 publications

Localizing Defects in Multithreaded Programs by Mining Dynamic Call Graphs

Localizing Defects in Multithreaded Programs by Mining Dynamic Call Graphs

A Meta-Aspect Protocol for Developing Dynamic Analyses

An Extensible Open-Source Compiler Infrastructure for Testing

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