Cloud Testing: A Survey on Tools and Open Challenges

Cloud Computing is growing exponentially across organizations and it has a vast impact on the way traditional computation and software testing is conducted. The web based applications these days have different configuration setting, and different deployment requirements. The main focus of Cloud Computing is todeliverreliable, secured, fault-tolerant and elastic infrastructures for hosting Internet-based web applications. Computing the scheduling policies and allocation policy for resources which affect the cloud infrastructure (i.e. hardware, software services) for various web application under fluctuating load and system size is highly challenging problem to deal with. Testing cloud based web applicationsdemands for novel testing methods and tools. This paper is a survey on the growing need of cloud testing, the tools used and the open challenges in the area of cloud testing

MongoDB Performance In The Cloud

Web applications are growing at a staggering rate every day. As web applications keep getting more complex, their data storage requirements tend to grow exponentially. Databases play an important role in the way web applications store their information. Mongodb is a document store database that does not have strict schemas that RDBMs require and can grow horizontally without performance degradation. MongoDB brings possibilities for different storage scenarios and allow the programmers to use the database as a storage that fits their needs, not the other way around. Scaling MongoDB horizontally requires tens to hundreds of servers, making it very difficult to afford this kind of setup on dedicated hardware. By moving the database into the cloud, this opens up a possibility for low cost virtual machine instances at reasonable prices. There are many cloud services to choose from and without testing performance on each one, there is very little information out there. This paper provides benchmarks on the performance of MongoDB in the cloud

Development of Web and Cloud Computing-Based Chatbot Services for Enhancing Academic Services at Panca Budi University

This research aims to develop web and cloud-computing-based chatbot services that can enhance academic services at Panca Budi University. The study highlights the importance of information and communication technology in education and the challenges universities face, such as less interactive academic services and long waiting times. The proposed solution is the development of a web and cloud-computing-based chatbot that can provide quick and accurate responses to student inquiries. Cloud computing in chatbot management also offers additional benefits, such as efficiency and continuous service availability. The research methodology employed a waterfall-based development approach, outlining the stages of chatbot development. Implementing the web-based chatbot utilized Amazon Lex services and integration with other AWS services. Testing results showed that the chatbot improved accessibility to academic information, reduced waiting times, and enhanced the quality of student interactions. The adoption of AWS cloud computing services enabled the chatbot to be accessed online 24/7. The successful development of the chatbot will help meet student needs and enhance academic services at Panca Budi Universit

Usability testing on intelligent mobile web pre-fetching of cloud storage scheme

Mobile device and Cloud Storage (CS) represent the trends of technology usage of the last few years. However, the difficulty in managing the data when there are too many simultaneous uses of cloud storage services at the same time that can cause latency or delayed time. This paper evaluates mobile cloud storage services using usability testing, which is intended to access by multiple of Cloud Storage Services (CSS) with the proposed Intelligent Mobile Web Pre-fetching of Cloud Storage Scheme (MOBICS). The results show most of the respondents with 95.65% agreeing that MOBICS system was very practical and has enhanced the speed in accessing and storing data by Mobile Cloud Storage (MCS). Besides, MOBICS reduces time of interaction up to 19.28% for the local pre-fetching and 18.80% for the intelligent pre-fetching

Model-Based Testing for Composite Web Services in Cloud Brokerage Scenarios

Cloud brokerage is an enabling technology allowing various services to be merged together for providing optimum quality of service for the end-users. Within this collection of composed services, testing is a challenging task which brokers have to take on to ensure quality of service. Most Software-as-a-Service (SaaS) testing has focused on high-level test generation from the functional specification of individual services, with little research into how to achieve sufficient test coverage of composite services. This paper explores the use of model-based testing to achieve testing of composite services, when two individual web services are tested and combined. Two example web services – a login service and a simple shopping service – are combined to give a more realistic shopping cart service. This paper focuses on the test coverage required for testing the component services individually and their composition. The paper highlights the problems of service composition testing, requiring a reworking of the combined specification and regeneration of the tests, rather than a simple composition of the test suites; and concludes by arguing that more work needs to be done in this area

An empirical study on mutation testing of WS-BPEL programs

Nowadays, applications are increasingly deployed as Web services in the globally distributed cloud computing environment. Multiple services are normally composed to fulfill complex functionalities. Business Process Execution Language for Web Services (WS-BPEL) is an XML-based service composition language that is used to define a complex business process by orchestrating multiple services. Compared with traditional applications, WS-BPEL programs pose many new challenges to the quality assurance, especially testing, of service compositions. A number of techniques have been proposed for testing WS-BPEL programs, but only a few studies have been conducted to systematically evaluate the effectiveness of these techniques. Mutation testing has been widely acknowledged as not only a testing method in its own right but also a popular technique for measuring the fault-detection effectiveness of other testing methods. Several previous studies have proposed a family of mutation operators for generating mutants by seeding various faults into WS-BPEL programs. In this study, we conduct a series of empirical studies to evaluate the applicability and effectiveness of various mutation operators for WS-BPEL programs. The experimental results provide insightful and comprehensive guidance for mutation testing of WS-BPEL programs in practice. In particular, our work is the systematic study in the selection of effective mutation operators specifically for WS-BPEL programs

Efficiency Performance Evaluation on Multi-user Web Application Platforms in Cloud Computing

Cloud computing is a well-known paradigm nowadays because it decreases the cost to access the application, for a massive amount of data from anywhere in the world via internet. This paper takes the approach of testing the performance of web application deployment environment. The main objective of this paper was to investigate the performance of web application deployment infrastructure by growing eventually the number of users that visit the web application concurrently. The infrastructure that was used is part of the services provided by cloud computing, more specifically Platform as a Service (PaaS). This service provided a runtime environment in which we easily created, tested and deployed the web application. Tests were designed by using an open source tool. Web application subject for testing purposes was an open source pet shop application which fulfils the criteria of being a multi-user web application. Tests were created by using an open source application called Apache JMeter. One of main goals was to develop a proper test plan by considering user behaviour accessing a web application. We have developed and implemented three scenarios, started with deployment of the platform, installing dependencies and finally installing the web application used for performance testing. We have tested 2 different deployment platforms, in the first environment everything is installed in one machine and in second environment we separate application server from the database server. We have concluded in results where processes like register, login and checkout consumes much more resources of the server. In the future we will try to understand where machine learning stands in this part of web application development and how it can affect deployment infrastructure