Typestate-like analysis of multiple interacting objects

Naeem, Nomair A.; Lhoták, Ondřej

doi:10.1145/1449955.1449792

Cited by 17 publications

(11 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The semantic patches used by Coccinelle are quite different from our typestate analysis with dependency analysis. To perform a typestate-like analysis of multiple interacting objects, Naeem and Lhoták propose an abstract representation for objects [29], which is similar to our access-path clusters domain. While they only allow access paths that represent local variables, our domain allows arbitrary access paths, which is required for analyzing C++ programs.…”

Section: Related Workmentioning

confidence: 99%

ARC++: effective typestate and lifetime dependency analysis

Xiao

Balakrishnan²,

Ivančić

et al. 2014

Proceedings of the 2014 International Symposium on Software Testing and Analysis

View full text Add to dashboard Cite

The ever-increasing reliance of today's society on software requires scalable and precise techniques for checking the correctness, reliability, and robustness of software. Object-oriented languages have been used extensively to build largescale systems, including Java and C++. While many scalable static analysis approaches for C and Java have been proposed, there has been comparatively little work on the static analysis of C++ programs. In this paper, we provide an abstract representation to model C++ objects, containers, references, raw pointers, and smart pointers. Further, we present a new analysis called lifetime dependency analysis, which allows us to precisely track the complex lifetime semantics of temporary objects in C++. Finally, we propose an implementation of our techniques and present promising results on a large variety of open-source software.

show abstract

Section: Related Workmentioning

confidence: 99%

ARC++: effective typestate and lifetime dependency analysis

Xiao

Balakrishnan²,

Ivančić

et al. 2014

Proceedings of the 2014 International Symposium on Software Testing and Analysis

View full text Add to dashboard Cite

show abstract

“…There has been intensive research performed in the past decade to improve the efficiency of runtime monitoring tools, particularly by applying the static analyses to eliminate unnecessary instrumentation [6,7,11,17,19]. Even though these approaches have shown strong potential, it is challenging to develop a static analysis that is precise and yet scalable.…”

Section: Related Workmentioning

confidence: 99%

Optimizing monitoring of finite state properties through monitor compaction

Purandare

Dwyer

Elbaum

2013

Proceedings of the 2013 International Symposium on Software Testing and Analysis

View full text Add to dashboard Cite

Runtime monitoring has proven effective in detecting property violations, but it can incur high overhead when monitoring just a single property -particularly when the property relates multiple objects. In practice developers will likely monitor multiple properties in the same execution which will lead to even higher overhead.This paper presents the first study of overhead arising during the simultaneous monitoring of multiple properties. We present two techniques for mitigating overhead in such cases that exploit reductions in cost that arise from sharing of information between property monitors. This sharing permits a single monitor to function in place of many monitors. We evaluate these techniques on the DaCapo benchmarks and 8 temporal correctness properties and find that they offer significant overhead reductions, as high as 57%, as the number of monitored properties increases.

show abstract

“…Consequently, removing a probe may cause an analysis to become unsound. Recent work addresses this issue by applying various sophisticated static analyses to the path property under analysis to determine monitoring points that are unlikely to expose path violations and remove them offline [Bodden 2010;Bodden et al 2007Bodden et al , 2008aDwyer and Purandare 2007;Naeem and Lhotak 2008], by employing a watchdog thread to periodically trigger simultaneous enabling/disabling of probes [Bodden et al 2008b] (this approach may miss a violation), or by calculating and enabling only the set of probes necessary to observe the transitions to other states ]. These techniques are orthogonal to and can be applied jointly with our approach.…”

Section: Related Workmentioning

confidence: 99%

Lattice-Based Sampling for Path Property Monitoring

Diep

Dwyer

Elbaum

2011

ACM Trans. Softw. Eng. Methodol.

View full text Add to dashboard Cite

Runtime monitoring can provide important insights about a program's behavior and, for simple properties, it can be done efficiently. Monitoring properties describing sequences of program states and events, however, can result in significant runtime overhead. This is particularly critical when monitoring programs deployed at user sites that have low tolerance for overhead. In this paper we present a novel approach to reducing the cost of runtime monitoring of path properties. A set of original properties are composed to form a single integrated property that is then systematically decomposed into a set of properties that encode necessary conditions for property violations. The resulting set of properties forms a lattice whose structure is exploited to select a sample of properties that can lower monitoring cost, while preserving violation detection power relative to the original properties. The lattice is then complemented with a weighting scheme that assigns each property a different priority that can be adjusted continuously to better drive the property sampling process. Our evaluation using the Hibernate API reveals that our approach produces a rich, structured set of properties that enables control of monitoring overhead, while detecting more violations more quickly than alternative techniques.

show abstract

Typestate-like analysis of multiple interacting objects

Cited by 17 publications

References 31 publications

ARC++: effective typestate and lifetime dependency analysis

ARC++: effective typestate and lifetime dependency analysis

Optimizing monitoring of finite state properties through monitor compaction

Lattice-Based Sampling for Path Property Monitoring

Contact Info

Product

Resources

About