JSXM: A Tool for Automated Test Generation

Dranidis, Dimitris; Bratanis, Konstantinos; Ipate, Florentin

doi:10.1007/978-3-642-33826-7_25

Cited by 19 publications

(16 citation statements)

References 10 publications

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“…For example, a bank account is modelled in [8] as a SXM having Σ = {open(), deposit(a), withdraw(a), close()}, where a represents a positive number. The SXM can have different functions, such as W ithdrawAll, W ithdraw, W ithdrawError (written in upper case, in order to differentiate them from the input symbol withdraw(a)), which can be triggered if the value of a is equal to the account balance b in the first case, 0 < a < b in the second case and b < a for the error case.…”

Section: Stream X-machinesmentioning

confidence: 99%

“…The SXM can have different functions, such as W ithdrawAll, W ithdraw, W ithdrawError (written in upper case, in order to differentiate them from the input symbol withdraw(a)), which can be triggered if the value of a is equal to the account balance b in the first case, 0 < a < b in the second case and b < a for the error case. For example, a bank account is modelled in [8] as a SXM having Σ = {open(), deposit(a), withdraw(a), close()}, where a represents a positive number. Even if a > 0 takes values from an infinite set, thus making Σ also infinite, the theoretical results concerning the X-machine test generation will still be preserved, the only difference being that the search process for appropriate input values will be realized in an infinite set.…”

Section: Stream X-machinesmentioning

confidence: 99%

“…Another tool, called JSXM [8], was developed and used for SXM based testing, using the theoretical foundations from [12]. JSXM supports the animation of SXM models, described in an XML-based language with Java in-line code, and the automatic generation of test suites from the SXM specifications.…”

Section: Related Workmentioning

confidence: 99%

“…has been used in high performance agent based simulators like FLAME [7]; and (2) its associated testing methods [12,11,8]. In essence, an SXM is a class of extended finite state machine (EFSM), having an internal memory and transitions labelled by processing functions, which might have input parameters and can update the machine internal memory.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

X-Machine Based Testing for Cloud Services

Lefticaru

Simons

2015

Communications in Computer and Information Science

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Abstract. In this article we present a tool designed for cloud service testing, able to generate test cases from a formal specification of the service, in form of a deterministic stream X-machine (DSXM) model. The paper summarizes the theoretical foundations of X-machine based testing and illustrates the usage of the developed tool on some examples. It shows in detail how the specification should be written, which are the design for test conditions it should satisfy, in order to assure the generation of high quality test suites for the cloud service.

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Section: Stream X-machinesmentioning

confidence: 99%

Section: Stream X-machinesmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

X-Machine Based Testing for Cloud Services

Lefticaru

Simons

2015

Communications in Computer and Information Science

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“…A tool suite for the specification of SXMs and automated test case generation [8] is available in Java (JSXM). The JSXM language for modeling SXMs is based on XML and Java inline code.…”

Section: Tool Supportmentioning

confidence: 99%

Enabling Proactive Adaptation through Just-in-Time Testing of Conversational Services

Dranidis

Metzger

Kourtesis

2010

Towards a Service-Based Internet

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Abstract. Service-based applications (SBAs) will increasingly be composed of third-party services available over the Internet. Reacting to failures of those third-party services by dynamically adapting the SBAs will become a key enabler for ensuring reliability. Determining when to adapt an SBA is especially challenging in the presence of conversational (aka. stateful) services. A conversational service might fail in the middle of an invocation sequence, in which case adapting the SBA might be costly; e.g., due to the necessary state transfer to an alternative service. In this paper we propose just-in-time testing of conversational services as a novel approach to detect potential problems and to proactively trigger adaptations, thereby preventing costly compensation activities. The approach is based on a framework for online testing and a formal test-generation method which guarantees functional correctness for conversational services. The applicability of the approach is discussed with respect to its underlying assumptions and its performance. The benefits of the approach are demonstrated using a realistic example.

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A verified and optimized Stream X‐Machine testing method, with application to cloud service certification

Simons

Lefticaru

2020

Software Testing Verif & Rel

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Summary The Stream X‐Machine (SXM) testing method provides strong and repeatable guarantees of functional correctness, up to a specification. These qualities make the method attractive for software certification, especially in the domain of brokered cloud services, where arbitrage seeks to substitute functionally equivalent services from alternative providers. However, practical obstacles include the difficulty in providing a correct specification, the translation of abstract paths into feasible concrete tests and the large size of generated test suites. We describe a novel SXM verification and testing method, which automatically checks specifications for completeness and determinism, prior to generating complete test suites with full grounding information. Three optimization steps achieve up to a 10‐fold reduction in the size of the test suite, removing infeasible and redundant tests. The method is backed by a set of tools to validate and verify the SXM specification, generate technology‐agnostic test suites and ground these in SOAP, REST or rich‐client service implementations. The method was initially validated using seven specifications, three cloud platforms and five grounding strategies.

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JSXM: A Tool for Automated Test Generation

Cited by 19 publications

References 10 publications

X-Machine Based Testing for Cloud Services

X-Machine Based Testing for Cloud Services

Enabling Proactive Adaptation through Just-in-Time Testing of Conversational Services

A verified and optimized Stream X‐Machine testing method, with application to cloud service certification

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