MIDAS: a cloud platform for SOA testing as a service

Francesco, Alberto De; Napoli, Claudia Di; Giordano, Maurizio; Ottaviano, Giuseppe; Perego, Raffaele; Tonellotto, Nicola

doi:10.1504/ijhpcn.2015.071254

Cited by 6 publications

(3 citation statements)

References 6 publications

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“…Indeed, each service receives a MIDAS DSL model as input and generates test cases for the input model, based on its own test scenario. There are also other services for test case prioritization, scheduling, transformation to the TTCN-3 test code, execution, and arbitration [4,[9][10][11][12]14].…”

Section: Previous Attemptsmentioning

confidence: 99%

Challenges & opportunities in low-code testing

Khorram

Mottu

Sunyé

2020

Proceedings of the 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems: Companion Proceedi

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Low-code is a growing development approach supported by many platforms. It fills the gap between business and IT by supporting the active involvement of non-technical domain experts, named Citizen Developer, in the application development lifecycle.Low-code introduces new concepts and characteristics. However, it is not investigated yet in academic research to point out the existing challenges and opportunities when testing low-code software. This shortage of resources motivates this research to provide an explicit definition to this area that we call it Low-Code Testing.In this paper, we initially conduct an analysis of the testing components of five commercial Low-Code Development Platforms (LCDP) to present low-code testing advancements from a business point of view. Based on the low-code principles as well as the result of our analysis, we propose a feature list for low-code testing along with possible values for them. This feature list can be used as a baseline for comparing low-code testing components and as a guideline for building new ones. Accordingly, we specify the status of the testing components of investigated LCDPs based on the proposed features. Finally, the challenges of low-code testing are introduced considering three concerns: the role of citizen developer in testing, the need for high-level test automation, and cloud testing. We provide references to the state-of-the-art to specify the difficulties and opportunities from an academic perspective. The results of this research can be used as a starting point for future research in low-code testing area. CCS CONCEPTS• Software and its engineering → Software testing and debugging.

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Section: Previous Attemptsmentioning

confidence: 99%

Challenges & opportunities in low-code testing

Khorram

Mottu

Sunyé

2020

Proceedings of the 23rd ACM/IEEE International Conference on Model Driven Engineering Languages and Systems: Companion Proceedi

View full text Add to dashboard Cite

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“…By monitoring which licenses are used for which amount of time, a payment structure between the tool provider and the cloud platform provider can be defined. More details on this problem, as well as other technical prob- lems which were solved within the MIDAS project, can be found in the literature [7,8].…”

Section: Setting Up the Infrastructurementioning

confidence: 99%

Model-based testing as a service

Herbold

Hoffmann

2017

Int J Softw Tools Technol Transfer

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The quality of Web services is an important factor for businesses that advertise or sell their services in the Internet. Failures can directly lead to fewer costumers or security problems. However, the testing of complex Web services that are organized in service-oriented architectures is a difficult and complex problem. Model-based testing (MBT) is one solution to deal with the complexity of the testing. With MBT, testers do not define the tests directly, but rather specify the structure and behavior of the System Under Test using models. Then, a test strategy is used to derive test cases automatically from the models. However, MBT yields a large amount of tests for complex systems which require lots of resources for their execution, thereby limiting its potential. Within this article, we discuss how cloud computing can be used to provide the required resources for scaling up test campaigns with large amounts of test cases derived using MBT.

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“…Examples of QoS-based Service-Based Applications are Cloud applications. In these cases, component services have to be executed on computing resources belonging to different Cloud providers at a price depending both on the required computational power, and on the adopted market strategies (De Francesco et al 2015). The response time, availability, pay-per-use, cost, and reputation are critical QoS attributes in cloud computing (Feng et al 2016).…”

Section: Introductionmentioning

confidence: 99%

A Trade-Off Negotiation Strategy for Pareto-Optimal Service Composition with Additive QoS-constraints

Napoli

Rossi

2020

Group Decis Negot

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QoS-based service composition enables the development of complex business applications. They are composed of distributed services characterized by QoS attributes representing non-functional characteristics, such as cost, execution time, and reliability. With the proliferation of services on the Internet, more candidates for each component service may be available with different QoS values. Hence, the ones satisfying QoS global constraints required for the application have to be selected. Automated negotiation is adopted to select component services in a dynamic market of services where provided QoS values may vary according to different market strategies. Nevertheless, when dealing with multiple QoS attributes, multiple service providers, and not shared information, it is difficult to guarantee the formal properties of the negotiation outcomes. In the present work, we propose a trade-off negotiation strategy that allows reaching a Pareto-optimal agreement, if it exists. The agreement consists of the QoS values of component services that are the ones selected to provide the complete application. The strategy exploits both the competition, that is due to multiple services providing the same functionality with different QoS values, and the cooperation among the providers of the different component services, that are necessary to meet the required end-to-end QoS constraints.

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MIDAS: a cloud platform for SOA testing as a service

Cited by 6 publications

References 6 publications

Challenges & opportunities in low-code testing

Challenges & opportunities in low-code testing

Model-based testing as a service

A Trade-Off Negotiation Strategy for Pareto-Optimal Service Composition with Additive QoS-constraints

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