Precise Analysis of Java Programs Using JOANA

Giffhorn, Dennis; Hammer, Christian

doi:10.1109/scam.2008.17

Cited by 10 publications

(3 citation statements)

References 8 publications

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“…AddConstraints then computes the set of causal events for any predictable trace constrained by G, which it uses to add LW constraints to G, ensuring that every causal read in a predictable trace can have the same last writer as in the original trace (line 11). Next, AddConstraints adds LS constraints to G, by identifying critical sections on the We evaluated Joana to perform static analysis for detecting whether a branch depends on prior reads or not [Giffhorn and Hammer 2008], following the system dependency graphs used in MCR-S [Huang and Huang 2017]. We found no practical advantages to using Joana.…”

Section: Verifying Wdp-racesmentioning

confidence: 99%

Dependence-aware, unbounded sound predictive race detection

Genç

Roemer

Yu-fan

et al. 2019

Proc. ACM Program. Lang.

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Data races are a real problem for parallel software, yet hard to detect. Sound predictive analysis observes a program execution and detects data races that exist in some other, unobserved execution. However, existing predictive analyses miss races because they do not scale to full program executions or do not precisely incorporate data and control dependence. This paper introduces two novel, sound predictive approaches that incorporate data and control dependence and handle full program executions. An evaluation using real, large Java programs shows that these approaches detect more data races than the closest related approaches, thus advancing the state of the art in sound predictive race detection. CCS Concepts: • Software and its engineering → Dynamic analysis; Software testing and debugging.

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Section: Verifying Wdp-racesmentioning

confidence: 99%

Dependence-aware, unbounded sound predictive race detection

Genç

Roemer

Yu-fan

et al. 2019

Proc. ACM Program. Lang.

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“…Furthermore, for each primitive service, we construct a restricted PDG with nodes corresponding to input and output variables and edges joining the input nodes to the output nodes they depend on. Variable dependence in atomic services can be identified either using classical PDGs [17] or using a description of the service behaviour. In the worst case, we consider that all service outputs depend on all service inputs.…”

Section: Business Processes Abstractionmentioning

confidence: 99%

E2SM: a security tool for adaptive cloud‐based service‐oriented applications

Abdellatif

2019

IET softw.

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The issue of security in the distributed system landscape of a service-oriented architecture (SOA) is a challenging one. No longer is it limited to a local application or an application domain, security must now work across a range of applications and business processes interacting with each other. This is even more true when SOA-based applications are provisioned in the cloud. Firstly, cloud applications components, and the data they might handle, that were once silos, are now being exposed as services by distinct and distrusted tenants. Secondly, such applications are often adaptive when they are provisioned in cloud environments. This study proposes an end-to-end security model (E2SM) that aims to protect data confidentiality in adaptive cloud-based SOA applications. E2SM allows the setting of data-centric security policies that go beyond services boundaries. First, security configuration is automatically calculated starting from a few intuitive business-oriented security settings. Then, the configuration is updated with minimal overhead if security policies are dynamically modified and/or SOA architecture is reconfigured. A security tool is implemented according to the proposed model. As for validation, the tool was used to secure a healthcare business process.

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“…Furthermore, for each primitive service, we construct a restricted PDG with nodes corresponding to input and output variables and edges joining the input nodes to the output nodes they depend on. Variable dependence in atomic services can be identified either using classical program dependence graphs [13] or using a description of the service behavior. In the worst case, we consider that all service outputs depend on all service inputs.…”

Section: System Dependence Graphsmentioning

confidence: 99%

An End-to-End Security Model for Adaptive Service-Oriented Applications

Abdellatif

Bozga

2018

Service-Oriented Computing – ICSOC 2017 Workshops

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In this paper, we present E2SM, an End-to-End Security Model and a set of algorithms to protect data confidentiality in complex adaptive Serviceoriented applications SOA. Starting from initial and intuitive business security constraints' settings, E2SM synthesizes a complete security configuration that is formally verified. E2SM is adapted to dynamic security constraints' modifications and to services' architecture reconfiguration. Thanks to its compositional verification, only impacted services' security is rechecked which makes E2SM suitable to adaptive and scalable SOA.

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Precise Analysis of Java Programs Using JOANA

Cited by 10 publications

References 8 publications

Dependence-aware, unbounded sound predictive race detection

Dependence-aware, unbounded sound predictive race detection

E2SM: a security tool for adaptive cloud‐based service‐oriented applications

An End-to-End Security Model for Adaptive Service-Oriented Applications

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