Web API Creation for Enterprise Mashup

Data Security is a worldwide concern mostly for small medium enterprise (SMEs) and frameworks, approaches, methods are constantly evolving that has a connection with cloud computing, information systems, artificial intelligence, blockchain. Many developers, administrators or product teams running blind. Those are not knowing of problems with their application or do not have the information to fix the problems. The things which can go wrong with web and mobile applications or services is unlimited like dependency failures, resources, and crashes. Main argument is an evaluation of benefits by using Cloud as infrastructure and application on proactive monitoring called Azure Application Insights (AppInsight) towards target like web application, web API, PKI etc. The findings, demonstration of the study should reveal and support our main hypothesis that there is direct link between the proactive monitoring and the main factors that affects utilizing the cloud services. To address this need, in this paper, we introduce AppInsight, the best practice and a model of proactive approach to monitor different targets using Microsoft technology on Azure Cloud services. AppInsight – a model of proactive monitoring includes several functionalities: (1) identifying availability, (2) failures dependencies, (3) performance and (4) using telemetry data generates ad-hoc solution to fix potential failure of web application, web API etc. AppInsight a feature of Azure Monitor used to monitor live applications. AppInsight will automatically detect performance anomalies, and includes powerful analytics tools to help you diagnose issues. You will get a range of telemetry data of analytics of your target which is monitored by AppInsight. To evaluate this tool, we conduct an empirical evaluation by comparing data from actual live monitoring of Y target. Demo Video: https://www.youtube.com/watch?v=q7R8-c0ge7M

Due to its high portability and simplicity, web application (app) based on HTML/JavaScript/CSS has been widely used for various smart-device platforms. To take advantage of its wide platform pool, a new idea called app migration has been proposed for the web platform. Web app migration is a framework to serialize a web app running on a device and restore it in another device to continue its execution. In JavaScript semantics, one of the language features that does not allow easy app migration is a closure. A JavaScript function can access variables defined in its outer function even if the execution of the outer function is terminated. It is allowed because the inner function is created as a closure such that it contains the outer function's environment. This feature is widely used in web app development because it is the most common way to implement data encapsulation in web programming. Closures are not easy to serialize because environments can be shared by a number of closures and environments can be created in a nested way. In this paper, we propose a novel approach to fully serialize closures. We created mechanisms to extract information from a closure's environment through the JavaScript engine and to serialize the information in a proper order so that the original relationship between closures and environments can be restored properly. We implemented our mechanism on the WebKit browser and successfully migrated Octane benchmarks and seven real web apps which heavily exploit closures. We also show that our mechanism works correctly even for some extreme, closure-heavy cases.

RESTful Web APIs have no description files like WSDL in traditional Web service. Although some REST API definition models have been arising recently, there is still lacking in structured description format for existing large mounts of Web APIs. Almost all Web APIs are documented in semi-structured web pages, and these documentation formats are various for different sites. It's hard for machine to read the semantics of Web APIs. In this paper, we have proposed a novel hierarchical recurrent neural network to convert REST API documentation to structured machine-readable description format -- the Swagger REST API specification. The network extracts the Swagger defined attributes of a REST API from HTML web pages without any feature engineering. With the extracted API specifications, we built an API repository to index, search and compose Web APIs. Experiment showed that the hierarchical RNN model performed well even with only a few training samples.

At present the web applications are used for most of the life activities, these applications are affected by an attack called (Structure Query Language Injection Attack) SQLIA due to the vulnerabilities of the web application. The vulnerabilities of the web application are increased because most of application developers do not care to security in designing.SQL injection is a common attack that infects a web application. The attacker adds (Structured Query Language) SQL code to web page for accessing and changing victim databases.The vital step in securing the database and detecting such an attack in web apps is preparing a tool. Many researchers propose different ways for detection and prevention of such as an attack. In this paper a tool it proposed using a powerful micro-framework web application designer called Flask in Python 3.7 to detect and prevent such attacks. The proposed system is called SQLIAD. SQLIAD analyzed a web application on-line.

Web APIs provide interfaces for interaction among systems based on the existing infrastructure for hosting Web sites and applications. The REST architectural style is the most employed approach for building Web APIs. However, the flexibility provided by REST may result in implementations with low quality design, limited reuse and poor documentation. This paper describes a maturity model for classifying Web APIs, aimed at promoting the adherence to REST architectural principles and the adoption of semantic Web technology in order to improve the design, reuse and documentation of Web APIs.

Effective support to web designers for fast development of web applications starting from third-party components or Web APIs requires to take into account different aspects. Among them, functional and non functional Web API features and suggestions coming from other web designers who faced similar problems and can share the solutions they adopted. In this paper, we propose a new model that brings together all these aspects to support Web API selection for building web mashups. We exploited the model to provide a map of existing Web API recommendation strategies, as well as to design new solutions based on the combined modeling of different Web API descriptive aspects. Since these aspects are extracted from different sources (such as Web API public repositories and social networks of web mashup developers), our model is built by relying on the Linked Data principles.

Automated model-based test generation presents a viable alternative to the costly manual test creation currently employed for regression testing of web apps. However, existing model inference techniques rely on threshold-based whole-page comparison to establish state equivalence, which cannot reliably identify near-duplicate web pages in modern web apps. Consequently, existing techniques produce inadequate models for dynamic web apps, and fragile test oracles, rendering the generated regression test suites ineffective. We propose a model-based test generation technique, FRAGGEN, that eliminates the need for thresholds, by employing a novel state abstraction based on page fragmentation to establish state equivalence. FRAGGEN also uses fine-grained page fragment analysis to diversify state exploration and generate reliable test oracles. Our evaluation shows that FRAGGEN outperforms existing whole-page techniques by detecting more near-duplicates, inferring better web app models and generating test suites that are better suited for regression testing. On a dataset of 86,165 state-pairs, FRAGGEN detected 123% more near-duplicates on average compared to whole-page techniques. The crawl models inferred by FRAGGEN have 62% more precision and 70% more recall on average. FRAGGEN also generates reliable regression test suites with test actions that have nearly 100% success rate on the same version of the web app even if the execution environment is varied. The test oracles generated by FRAGGEN can detect 98.7% of the visible changes in web pages while being highly robust, making them suitable for regression testing.

Asynchronous JAVASCRIPT and XML (AJAX)-based web applications (web apps) are different from traditional applications as they rely on stateful asynchronous communication and runtime manipulation of the DOM (document object model) tree. In this paper, we try to validate a method proposed by Mesbah et al. (2012) for testing AJAX applications automatically using two case studies. We try to identify AJAX-specific errors. Our goal is to replicate their experiment on two different web applications and comment on the performance of their approach. We use ‘Crawljax’ (designed by Mesbah et al.) to create a state-flow graph. First, we check the DOM validity for every state and, second, we check the navigation of the states. Finally, we present the results from our case studies.

Web applications are one of the most useful platforms for the delivery of the information and service over the internet today. Day-to-Day the popularity of web application usage is increasing. Hence the web apps has to be designed for secure transformation of information from web client to web server and to mitigate the vulnerabilities. This paper presents a research survey report on constructing a secure web applications at the client side, server side and even in browsers. This paper initially gives an overview of web application, then followed by techniques or tools along with the attacks at the client side and serverside. It gives a big picture with the aim of promoting future research in this area.

The use of mobile and ubiquitous computing devices is advantageous for collecting and sharing patient data at the bedside or in hospital waiting areas. iPhone web applications - or web apps - combine the power of Internet based solutions with the simplicity of multi-touch and gesture technology, all one portable device. Since many data collection platforms have moved to an online paradigm (or are in the process of doing so), a web app is an ideal solution. In this work, we show the advantages of using a web app for patient data collection, as an imaging engine, and for patient feedback and survey systems. This can be achieved by taking advantage of simple functions available on the iPhone OS when using an online collection platform.

A relevant consequence of the expansion of the web and e-commerce is the growth of the demand of new web sites and web applications. As a result, web sites and applications are usually developed without a formalized process, and web pages are directly coded in an incremental way, where new pages are obtained by duplicating existing ones. Duplicated web pages, having the same structure and just differing for the data they include, can be considered as clones. The identification of clones may reduce the effort devoted to test, maintain and evolve web sites and applications. Moreover, clone detection among different web sites aims to detect cases of possible plagiarism. In this paper we propose an approach. based on similarity metrics, to detect duplicated pages in web sites and applications, implemented with HTML language and ASP technology. The proposed approach has been assessed by analyzing several web sites and Web applications. The obtained results are reported in the paper with respect to some case studies.

The end point of clinical research is often considered to be the publication of peer reviewed data and results. Although an effective method for communication with a technical audience, publications...

Internationally Scalable and Publicly Accessible Tools for Prioritising Investment in Active Travel

The main issues of current web application is easily hacking the user information by unauthorized person. The development of entire web application depends on scripting languages that easily displays the user authentication code to the web browser. All code must be transferred through query string parameter (URL) of the web application. This kind of application security fails when verifying it by penetration testing which is based on XSS languages. This study overcomes the security issues by developing a web application based on cross site scripting technique which the user codes are encrypted using RSA algorithm and cookies, cross domain verification based on encrypted use code. XSS vulnerabilities come in different forms and may be categorized into two varieties: reflected and stored. Reflected is on type of attack which can be performed against applications that employ a dynamic page error message to users. Stored XSS vulnerability appears when data submitted by one user is store in the application or in the back-end database. The user cookies of the web browser store only the encrypted key values. These techniques applied in Enterprise web application it support multiple organization for processing product purchase order, sales order and invoice details.

Acid stimulation treatments are typically designed using a combination of experience, available field/lab testing data and a stimulation design software that ties it all together. The final design, given the large degrees of uncertainty, requires multiple iterations to arrive at the (near) optimum stimulation design. To account for the large number of variables and their uncertainty, a framework and associated tools have been developed for automating and optimizing the design process that allow to significantly reduce the optimization time. The adopted approach leverages modern web applications for overcoming the limitations associated with the legacy stimulation design tools. Python Dash is used for creating an interactive web application, allowing users to load a file containing all necessary inputs for the calculation and specify the ranges for different design parameters. The web app then generates a parameter space and spawns multiple parallel runs of the calculation engine. An optimization module utilizing existing python optimization libraries is developed within the web app framework, which guides the selection of the next sample point in the parameter space after each iteration until the optimum point is reached. After implementing this framework across multiple workflows, considerable improvements have been realized with time savings ranging from hours to days. A detailed case study is presented to demonstrate the application of the framework for designing a Limited Entry Liner (LELs) completion, where the nozzle distribution in different reservoir sections (compartments) is varied to achieve a desired acid placement into the formation and improve stimulation efficiency.