A system for specification and verification of interactive, data-driven web applications

Deutsch, Alin; Sui, Liying; Vianu, Victor; Zhou, Dayou

doi:10.1145/1142473.1142584

Cited by 24 publications

(24 citation statements)

References 3 publications

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“…The experimental results are quite exciting: we obtained surprisingly good verification times (on the order of seconds), suggesting that automatic verification is practically feasible for significant classes of properties and Web services. The implementation and experimental results are described in [32], and a demo of the WAVE prototype was presented in [36].…”

Section: The Wave Verifiermentioning

confidence: 99%

Automatic Verification of Database-Centric Systems

Deutsch

Hull²,

Vianu

2014

SIGMOD Rec.

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Section: The Wave Verifiermentioning

confidence: 99%

Automatic Verification of Database-Centric Systems

Deutsch

Hull²,

Vianu

2014

SIGMOD Rec.

Self Cite

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“…Analysis of data-centric processes was also studied in e.g. [9,14,18,1], but no provenance model was proposed there, since the focus was on analyzing a concrete given process, rather than accounting for different weighting and for hypothetical changes as in our work. The process model in some of these works is richer than that of DDPs, mainly due to support of dynamic data updates and parallelism.…”

Section: Related Workmentioning

confidence: 99%

“…While analysis of Data-Centric Processes was studied in e.g., [9,14,18], the focus on provenance and its applications (provisioned temporal analysis and specialization) distinguish the present work from that research.…”

Section: Introductionmentioning

confidence: 99%

A provenance framework for data-dependent process analysis

2014

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A data-dependent process (DDP) models an application whose control flow is guided by a finite state machine, as well as by the state of an underlying database. DDPs are commonly found e.g., in e-commerce. In this paper we develop a framework supporting the use of provenance in static (temporal) analysis of possible DDP executions. Using provenance support, analysts can interactively test and explore the effect of hypothetical modifications to a DDP's state machine and/or to the underlying database. They can also extend the analysis to incorporate the propagation of annotations from meta-domains of interest, e.g., cost or access privileges.Toward this goal we note that the framework of semiringbased provenance was proven highly effective in fulfilling similar needs in the context of database queries. In this paper we consider novel constructions that generalize the semiring approach to the context of DDP analysis. These constructions address two interacting new challenges: (1) to combine provenance annotations for both information that resides in the database and information about external inputs (e.g., user choices), and (2) to finitely capture infinite process executions. We analyze our solution from theoretical and experimental perspectives, proving its effectiveness.

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“…The verification of traditional, non-MVC web applications, has also been investigated in recent years [15,9,10,11]. In this paper, by focusing on MVC style web applications we are able to exploit the modularity in the MVC architecture and extract formal data models from existing applications.…”

Section: Related Workmentioning

confidence: 99%

Bounded verification of Ruby on Rails data models

Nijjar

Bultan

2011

Proceedings of the 2011 International Symposium on Software Testing and Analysis

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The use of scripting languages to build web applications has increased programmer productivity, but at the cost of degrading dependability. In this paper we focus on a class of bugs that appear in web applications that are built based on the Model-View-Controller architecture. Our goal is to automatically discover data model errors in Ruby on Rails applications. To this end, we created an automatic translator that converts data model expressions in Ruby on Rails applications to formal specifications. In particular, our translator takes Active Records specifications (which are used to specify data models in Ruby on Rails applications) as input and generates a data model in Alloy language as output. We then use bounded verification techniques implemented in the Alloy Analyzer to look for errors in these formal data model specifications. We applied our approach to two open source web applications to demonstrate its feasibility.

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A system for specification and verification of interactive, data-driven web applications

Cited by 24 publications

References 3 publications

Automatic Verification of Database-Centric Systems

Automatic Verification of Database-Centric Systems

A provenance framework for data-dependent process analysis

Bounded verification of Ruby on Rails data models

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