Cloud based testing of business applications and web services

This paper deals with testing of applications based on the principles of cloud computing. It is aimed to describe options of testing business software in clouds (cloud testing). It identifies the needs for cloud testing tools including multi-layer testing; service level agreement (SLA) based testing, large scale simulation, and on-demand test environment. In a cloud-based model, ICT services are distributed and accessed over networks such as intranet or internet, which offer large data centers deliver on demand, resources as a service, eliminating the need for investments in specific hardware, software, or on data center infrastructure. Businesses can apply those new technologies in the contest of intellectual capital management to lower the cost and increase competitiveness and also earnings. Based on comparison of the testing tools and techniques, the paper further investigates future trend of cloud based testing tools research and development. It is also important to say that this comparison and classification of testing tools describes a new area and it has not yet been done

A Systematic Mapping Study of Empirical Studies on Software Cloud Testing Methods

Context: Software has become more complicated, dynamic, and asynchronous than ever, making testing more challenging. With the increasing interest in the development of cloud computing, and increasing demand for cloud-based services, it has become essential to systematically review the research in the area of software testing in the context of cloud environments. Objective: The purpose of this systematic mapping study is to provide an overview of the empirical research in the area of software cloud-based testing, in order to build a classification scheme. We investigate functional and non-functional testing methods, the application of these methods, and the purpose of testing using these methods. Method: We searched for electronically available papers in order to find relevant literature and to extract and analyze data about the methods used. Result: We identified 69 primary studies reported in 75 research papers published in academic journals, conferences, and edited books. Conclusion: We found that only a minority of the studies combine rigorous statistical analysis with quantitative results. The majority of the considered studies present early results, using a single experiment to evaluate their proposed solution

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

An agile container-based approach to TaaS

Current cloud deployment scenarios imply a need for fast testing of user oriented software in diverse, hetero-geneous and often unknown hardware and network environ-ments, 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-in-time 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 stand-point, by using standard, common use deployment packages as Chef or Puppet hosted in parallellizable workloads over ready-to-run Docker images, we can minimize the time required for full-deployment multicomponent systems testing and valida-tion, 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

Finding a suitable performance testing tool

Abstract. The pursuit of finding the most suitable testing software for each project is a difficult task as there are a lot of software effective finding certain kind of problems but completely missing others in the field of stress and load testing. A silver bullet solving all problems in a cost effective and reliable way has not yet been found. This project was done as a systematic literature review to find whether there are solutions documented capable of testing everything in a cost-effective way. The document starts with an introduction of the task, originating from a real software testing company’s suggestion of finding suitable test software that can, cost effectively and reliably, fulfil the needs of the company. A history section is describing the reason of testing importance, basics of testing and what others have found in their studies of the area. The research method is described in detail followed by results describing tools found during the research divided in sections by license type. The sectioning by license type was selected for the benefit of testing companies that are interested in further developing tools found to their own interest. Findings and answered research questions were presented and discussed followed by possible implications and further research suggestions to future scholars interested in the matter. The systematic literature review found a total of 40 different tools identified during the data extraction process. One complete software system was available commercially including heavy support and help functions for the customer. A different approach linking open source and relatively inexpensive pieces of software together to achieve a composite solution was also identified. The solution included the most common and most popular individual piece of software identified by the study. All found pieces of software were listed and commented briefly mainly with information originating from the authors’ home pages

A Framework for Evaluating Model-Driven Self-adaptive Software Systems

In the last few years, Model Driven Development (MDD), Component-based Software Development (CBSD), and context-oriented software have become interesting alternatives for the design and construction of self-adaptive software systems. In general, the ultimate goal of these technologies is to be able to reduce development costs and effort, while improving the modularity, flexibility, adaptability, and reliability of software systems. An analysis of these technologies shows them all to include the principle of the separation of concerns, and their further integration is a key factor to obtaining high-quality and self-adaptable software systems. Each technology identifies different concerns and deals with them separately in order to specify the design of the self-adaptive applications, and, at the same time, support software with adaptability and context-awareness. This research studies the development methodologies that employ the principles of model-driven development in building self-adaptive software systems. To this aim, this article proposes an evaluation framework for analysing and evaluating the features of model-driven approaches and their ability to support software with self-adaptability and dependability in highly dynamic contextual environment. Such evaluation framework can facilitate the software developers on selecting a development methodology that suits their software requirements and reduces the development effort of building self-adaptive software systems. This study highlights the major drawbacks of the propped model-driven approaches in the related works, and emphasise on considering the volatile aspects of self-adaptive software in the analysis, design and implementation phases of the development methodologies. In addition, we argue that the development methodologies should leave the selection of modelling languages and modelling tools to the software developers.Comment: model-driven architecture, COP, AOP, component composition, self-adaptive application, context oriented software developmen