A systematic review on cloud testing

A systematic literature review is presented that surveyed the topic of cloud testing over the period (2012-2017). Cloud testing can refer either to testing cloud-based systems (testing of the cloud), or to leveraging the cloud for testing purposes (testing in the cloud): both approaches (and their combination into testing of the cloud in the cloud) have drawn research interest. An extensive paper search was conducted by both automated query of popular digital libraries and snowballing, which resulted into the final selection of 147 primary studies. Along the survey a framework has been incrementally derived that classifies cloud testing research along six main areas and their topics. The paper includes a detailed analysis of the selected primary studies to identify trends and gaps, as well as an extensive report of the state of art as it emerges by answering the identified Research Questions. We find that cloud testing is an active research field, although not all topics have received so far enough attention, and conclude by presenting the most relevant open research challenges for each area of the classification framework.This paper describes research work mostly undertaken in the context of the European Project H2020 731535: ElasTest. This work has also been partially supported by: the Italian MIUR PRIN 2015 Project: GAUSS; the Regional Government of Madrid (CM) under project Cloud4BigData (S2013/ICE-2894) cofunded by FSE & FEDER; and the Spanish Government under project LERNIM (RTC-2016-4674-7) cofunded by the Ministry of Economy and Competitiveness, FEDER & AEI

Automated testing of cloud-based elastic systems with AUToCLES

Abstract—Cloud-based elastic computing systems dynamically change their resources allocation to provide consistent quality of service and minimal usage of resources in the face of workload fluctuations. As elastic systems are increasingly adopted to implement business critical functions in a cost-efficient way, their reliability is becoming a key concern for developers. Without proper testing, cloud-based systems might fail to provide the required functionalities with the expected service level and costs. Using system testing techniques, developers can expose problems that escaped the previous quality assurance activities and have a last chance to fix bugs before releasing the system in production. System testing of cloud-based systems accounts for a series of complex and time demanding activities, from the deployment and configuration of the elastic system, to the execution of synthetic clients, and the collection and persistence of execution data. Furthermore, clouds enable parallel executions of the same elastic system that can reduce the overall test execution time. However, manually managing the concurrent testing of multiple system instances might quickly overwhelm developers ’ capabilities, and automatic support for test generation, system test execution, and management of execution data is needed. In this demo we showcase AUToCLES, our tool for automatic testing of cloud-based elastic systems. Given specifications of the test suite and the system under test, AUToCLES implements testing as a service (TaaS): It automatically instantiates the SUT, configures the testing scaffoldings, and automatically executes test suites. If required, AUToCLES can generate new test inputs. Designers can inspect executions both during and after the tests. I