PCTF: An Integrated, Extensible Cloud Test Framework for Testing Cloud Platforms and Applications

Iyer, Ganesh Neelakanta; Pasimuthu, Jayakhanna; Loganathan, R.

doi:10.1109/qsic.2013.65

Cited by 10 publications

(6 citation statements)

References 16 publications

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“…Cloud testing is the process of software testing based on CC technology [5]. Cloud testing can be testing the Cloud itself or TaaS over Cloud.…”

Section: Background and Motivationmentioning

confidence: 99%

“…is results in the reduction of delivery time, increased productivity, and capital and operational cost saving. Besides numerous benefits, it also postures several challenges for the quality of service (QoS) assurance including high-availability, multitenancy issues, elasticity, privacy, and security [5]. CC is regarded by many authors as a paradigm shift in computing, in lieu of an important change in the way computing services are offered, developed, attained, and paid for [6].…”

Section: Introductionmentioning

confidence: 99%

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Fuzzy Multicriteria Decision-Making Approach for Measuring the Possibility of Cloud Adoption for Software Testing

Ali

Ullah²,

Abrar

et al. 2020

Scientific Programming

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To reduce costs and improve organizational efficiency, the adoption of innovative services such as Cloud services is the current trend in today’s highly competitive global business venture. The aim of the study is to guide the software development organization (SDO) for Cloud-based testing (CBT) adoption. To achieve the aim, this study first explores the determinants and predictors of Cloud adoption for software testing. Grounded on the collected data, this study designs a technology acceptance model using fuzzy multicriteria decision-making (FMCDM) approach. For the stated model development, this study identifies a list of predictors (main criteria) and factors (subcriteria) using systematic literature review (SLR). In the results of SLR, this study identifies seventy subcriteria also known as influential factors (IFs) from a sample of 136 papers. To provide a concise understanding of the facts, this study classifies the identified factors into ten predictors. To verify the SLR results and to rank the factors and predictors, an empirical survey was conducted with ninety-five experts from twenty different countries. The application value in the industrial field and academic achievement of the present study is the development of a general framework incorporating fuzzy set theory for improving MCDM models. The model can be applied to predict organizational Cloud adoption possibility taking various IFs and predictors as assessment criteria. The developed model can be divided into two main parts, ranking and rating. To measure the success or failure contribution of the individual IFs towards successful CBT adoption, the ranking part of the model will be used, while for a complete organizational assessment in order to identify the weak area for possible improvements, the assessment part of the model will be used. Collectively, it can be used as a decision support system to gauge SDO readiness towards successful CBT.

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“…Cloud testing is the process of software testing based on CC technology [5]. Cloud testing can be testing the Cloud itself or TaaS over Cloud.…”

Section: Background and Motivationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Fuzzy Multicriteria Decision-Making Approach for Measuring the Possibility of Cloud Adoption for Software Testing

Ali

Ullah²,

Abrar

et al. 2020

Scientific Programming

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“…The field of cloud automated testing is nowadays mainly focused on the validation of the external main cloud platform components, as stated with initiatives like Open Cloud Lab [4]. Also to note, structure proposals like Progress Cloud Test Framework tend to integrate the corresponding testing suites in the framework itself [12]. This idea has lately been partially set aside to allow for more heterogeneous test loads, as shown in the FCHTS proposal [13].…”

Section: Related Workmentioning

confidence: 99%

An agile container-based approach to TaaS

Verdugo¹,

Salvachiua

Huecas³

2017

2017 56th FITCE Congress

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Current cloud deployment scenarios imply a need for fast testing of user oriented software in diverse, heterogeneous and often unknown hardware and network environments, making it difficult to ensure optimal or reproducible in-site testing. The current paper proposes the use of container based lightweight virtualization with a ready-to-run, just-intime deployment strategy in order to minimize time and resources needed for streamlined multicomponent prototyping in PaaS systems. To that end, we will study a specific case of use consisting of providing end users with pre-tested custom prepackaged and preconfigured software, guaranteeing the viability of the aforementioned custom software, the syntactical integrity of the provided deployment system, the availability of needed dependencies as well as the sanity check of the already deployed and running software. From an architectural standpoint, by using standard, common use deployment packages as Chef or Puppet hosted in parallellizable workloads over readyto-run Docker images, we can minimize the time required for full-deployment multicomponent systems testing and validation, as well as wrap the commonly provided features via a user-accessible RESTful API. The proposed infrastructure is currently available and freely accessible as part of the FIWARE EU initiative, and is open to third party collaboration and extension from a FOSS perspective.

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“…Some of the important cloud dimensions include elastic scalability, multitenancy, security and performance (Iyer et al, 2013). Some of the important cloud dimensions include elastic scalability, multitenancy, security and performance (Iyer et al, 2013).…”

Section: Cloud Test Dimensionsmentioning

confidence: 99%