Web Application Testing Research Articles

Foodies Full Stack Web Application: Connecting You to Your College Canteens

The "Foodies Full Stack Web Application" is designed to revolutionize the way college students interact with their campus canteen services by providing real-time access to menus, nutritional information, and personalized food recommendations. This project aims to bridge the gap between canteen owners and students, offering seamless communication and better decision-making for daily meals. By leveraging the power of the Spoonacular API, the platform can not only display available menu items but also offer detailed nutritional data, which is crucial for students with dietary preferences or restrictions. Additionally, the application uses machine learning to suggest dishes based on individual preferences, ensuring a tailored dining experience for each user. This project has been developed using modern web development technologies, integrating both front-end and back-end functionalities to create a responsive, user-friendly platform. The application has the potential to enhance user satisfaction, improve the efficiency of canteen operations, and promote healthier eating habits among students. This paper outlines the design, implementation, and testing of the Foodies Web Application, while also discussing future improvements and scalability.

E2E test execution optimization for web application based on state reuse

AbstractEnd‐to‐end (E2E) testing is a commonly used technique for web application testing. Unlike traditional unit tests, E2E tests focus on test scenarios that target the entire business, which integrate and collaborate of various components and services to make the whole application work. As a result, one drawback of E2E tests is their longer execution time, seriously affecting testing efficiency of web applications. In order to speed up the execution of E2E tests for web applications, this paper proposes a test execution optimization approach based page state reuse. Through analyzing the common operations of E2E tests, a common prefix trees is constructed to organize the same operations among test scripts in a test suite of web applications. Under the guidance of the prefix tree, the optimal reusable state is identified and duplicated to maximize the utilization of page states triggered by the same operations, thereby reducing the overall execution time of the test suite. Besides, to realize page state reuse automatically, we design a browser process replication strategy, which implement querying the active page and duplicating the web page. To verify the effectiveness of our method, experiments and evaluations were conducted on 347 E2E tests from eight open‐source web applications, and the results showed that our approach reduced the E2E testing execution time for web applications by 52%–68%.

Developing an Open-Source, User-Friendly, OWASP-Compliant Architecture for Healthcare Web Application Testing.

Nowadays, web applications are fundamental in the healthcare sector. However, with the widespread use of this technology, risks related to cybersecurity attacks also increase. To mitigate this phenomenon, every 3-4 years, the nonprofit foundation Open Worldwide Application Security Project (OWASP) compiles a top 10 ranking of the most critical web application security risks. Along with the top 10 Web Application Security Risks, OWASP also provides the Web Security Testing Guide, which offers comprehensive guidelines for conducting security tests. This guide includes suggestions for specific tools to use when performing different tests, among other valuable insights. However, the use of these recommended tools can be costly and can require advanced technical skills and a deep understanding of security best practices and web technologies. In addition, since the OWASP work on web security is generic, it would be useful to restrict and adapt it to the healthcare area. This would help in reducing the overhead when dealing with the needed tools. The goal of this study is to make web application security assessment in healthcare more accessible by developing tools that simplify the process and makes it user- friendly. Before developing such tools, an in-depth feasibility study must be conducted to verify the existence of open-source libraries to carry out the necessary testing procedures. It will be also necessary to identify how tools could be simplified and enhanced when focusing on healthcare.

Comparison of selected tools for automation testing of Web applications

The article is as an introduction to software testing, considering its definition and reasons for errors appearing in code. Three selected libraries available in Python, used for automating tests of web applications, are presented: Selenium, Playwright, and Splinter. Subsequently, a detailed comparison of these tools is made based on specific comparative criteria.

DETECTA – MULTIPLE DISEASE DETECTION

Machine Learning Techniques for Predictive Analytics in Healthcare There are multiple techniques in machine learning that can in a variety of industries, do predictive analytics on large amounts of data. Predictive analytics in healthcare is a difficult endeavor, but it can eventually assist practitioners in making timely decisions regarding patients' health and treatment based on massive data. Diseases like Breast cancer, diabetes, and heart-related diseases are causing many deaths globally but most of these deaths are due to the lack of timely check-ups of the diseases. The above problem occurs due to a lack of medical infrastructure and a low ratio of doctors to the population. The statistics clearly show the same, WHO recommended, the ratio of doctors to patients is 1:1000 whereas India's doctor-to- population ratio is 1:1456, this indicates the shortage of doctors. The diseases related to heart, cancer, and diabetes can cause a potential threat to mankind, if not found early. Therefore, early recognition and diagnosis of these diseases can save a lot of lives. This work is all about predicting diseases that are harmful using machine learning classification algorithms. In this work, breast cancer, heart, and diabetes are included. To make this work seamless and usable by the mass public, our team made a medical test web application that makes predictions about various diseases using the concept of machine learning. In this work, our aim to develop a disease-predicting web app that uses the concept of machine learning-based predictions about various diseases like Breast cancer, Diabetes, Heart diseases, Covid, Pneumonia, Alzheimer.

Leveraging Selenium and Cypress for Comprehensive Web Application Testing

Leveraging Selenium and Cypress for Comprehensive Web Application Testing

Enhanced Cloud Computing Security Using Application-Based Multi-Factor Authentication (MFA) for Communication Systems

The objective of this study is to create an advanced cloud computing security system that addresses the security vulnerabilities inherent in existing authentication processes in communication systems. Specifically, the study developed an application-based multi-layer and multi-factor authentication (MFA) program that enhances cloud security measures. The system presented an improved approach to cloud computing security through the implementation of application-based multi-factor authentication (MFA). By leveraging encryption techniques, the system guarantees secure access based on user profiles. These profiles consist of valid usernames, passwords, and token numbers generated by the application. In addition, the system enhances security by integrating the Time-based One-Time Password (TOTP) algorithm (IETF RFC 6238) with location checks, augmenting the overall protection measures. A thorough testing procedure was carried out on the system, with a specific focus on a test web application hosted on the cloud server. The result validated the efficacy of all three authentication factors integrated within the application.

Multiple Disease Prediction System

The field of machine learning, a subset of artificial intelligence, has revolutionized numerous industries by enabling predictive analytics on vast datasets. In healthcare, predictive analytics holds great promise for enhancing patient care by providing insights for informed decision-making. Diseases like Parkinson's, diabetes, and heart conditions pose significant global challenges due to delayed detection, often caused by limited medical resources. Early recognition of these ailments is crucial, as late-stage diagnoses can be challenging to treat effectively. To address this gap, this project utilizes machine learning classification algorithms to predict these diseases. A user-friendly medical test web application has been developed to make these predictions accessible to a broad audience, aiming to facilitate early assessments and improve public health outcomes. Keywords— Disease Prediction, Artificial Intelligence, Machine Learning, Classification Algorithms.

LIGHTWEIGHT ENVIRONMENTS FOR TESTING SPEED AND RELIABILITY OF SOFTWARE BASED ON OPERATING SYSTEM LEVEL VIRTUALIZATION

An environment for performance software testing has been described, based on the use of containerization technology through the use of appropriate software (Docker or others) on the one hand, and a tool for measuring performance and carrying out load testing such as ApacheBench or similar. The advantage of containerization technology for achieving the goal was evaluated. It is shown that in this case, the test environment can be deployed on different computers separately, rather than being deployed centrally. This provides following advantages: less cost in terms of computing resources compared to other ways of deploying environments on local computers. Certain types of environment configurations can be easily distributed and replicated between individual computers and workstations through the distribution and application of prepared configuration files. Compared to cloud environments, this approach does not require additional material costs for support. The scheme of operation of such an environment for non-functional testing has been analyzed.. The environment also allows you to simulate more complex configurations, for example, to study the operation of various load balancing algorithms/systems. The created testing environment was tested on the example of performance of testing web applications. It showed that the created environment allows you to calculate the approximate response time of the application and the presence of failures depending on the number of users who use the application at the same time. Also, load testing allows you to calculate the normal and critical number of application users and predict and prevent potential failures. The mechanism for creating test environments considered in this work can be used to build models that are necessary for studying and/or modeling certain types of software testing based on loads, load balancing algorithms between workstations, and others. Since such an approach can be used on almost any personal workstation with relatively small requirements for computing resources and the deployment and distribution of environments is quite simple, such an approach can be implemented not only in business, but also in universities for courses that involve the use similar environments.

A Reinforcement Learning Approach to Guide Web Crawler to Explore Web Applications for Improving Code Coverage

Web crawlers are widely used to automatically explore and test web applications. However, navigating the pages of a web application can be difficult due to dynamic page generation. In particular, the inputs for the web form fields can affect the resulting pages and subsequent navigation. Therefore, choosing the inputs and the order of clicks on a web page is essential for an effective web crawler to achieve high code coverage. This paper proposes a set of actions to quickly fill in web form fields and uses reinforcement learning algorithms to train a convolutional neural network (CNN). The trained agent, named iRobot, can autonomously select actions to guide the web crawler to maximize code coverage. We experimentally compared different reinforcement learning algorithms, neural networks, and actions. The results show that our CNN network with the proposed actions performs better than other neural networks in terms of branch coverage using the Deep Q-learning (DQN) or proximal policy optimization (PPO) algorithm. Furthermore, compared to previous studies, iRobot can increase branch coverage by about 1.7% while reducing training time to 12.54%.

Bridging the GAP: Selenium and RPA for Unparalleled Automation

In the ever-changing technological landscape of today, the incorporation of test automation has become an essential element in the realm of software development and quality assurance. Selenium, known for its robust capabilities in web application testing, has long served as a fundamental pillar in the field of test automation. Simultaneously, Robotic Process Automation (RPA) has experienced increased utilization in order to streamline repetitive business processes across various industries. However, the true potential of these two automation approaches lies in their integration, which provides an opportunity for unparalleled efficiency, productivity, and comprehensive test coverage. This article delves into the synergistic relationship between Selenium and RPA, examining how their combination ushers in a new era of test automation. We explore the seamless integration of Selenium within RPA frameworks and demonstrate how it expands automation beyond web applications, encompassing desktop applications and diverse systems. Our research outlines practical use cases, technical implementation, and the benefits of this amalgamation. Furthermore, we discuss its potential to revolutionize not only software testing but also broader business processes.The fusion of Selenium and RPA signifies a transformative shift in test automation, enabling organizations to bridge the gap between isolated testing efforts and comprehensive automation, ultimately resulting in unparalleled efficiency and reliability.

Generative Pre-Trained Transformer-Based Reinforcement Learning for Testing Web Application Firewalls

Web Application Firewalls (WAFs) are widely deployed to protect key web applications against multiple security threats, so it is important to test WAFs regularly to prevent attackers from bypassing them easily. Machine-learning-based black-box WAF testing is gaining more attention, though existing learning-based approaches have strict requirements on the source and scale of payload data and suffer from the local optimum problem, limiting their effectiveness and practical application. We propose GPTFuzzer, a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">practical</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">effective</i> generation-based approach to test WAFs by generating attack payloads token-by-token. Specifically, we fine-tune a Generative Pre-trained Transformer language model with reinforcement learning to make GPTFuzzer have the least restrictions on payload data and thus more applicable in practice, and we use reward modeling and KL-divergence penalty to improve the effectiveness of our approach and mitigate the local optimum issue. We implement GPTFuzzer and evaluate it on two well-known open-source WAFs against three kinds of common attacks. Experimental results show that GPTFuzzer significantly outperforms state-of-the-art approaches, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i.e.</i> ML-Driven and RAT, finding up to 7.8× (3.2× on average) more bypassing payloads within 1,250,000 requests, or finding out all bypassing payloads using up to 8.1× (3.3× on average) fewer requests.

EFFECTIVENESS OF SECURITY THROUGH OBSCURITY METHODS TO AVOID WEB APPLICATION VULNERABILITY SCANNERS

The concept of security through obscurity is not recommended by the National Institute of Standards and Technology (NIST) as a form of system security. Basically this concept hides assets as difficult as possible so that it is not easy for attackers to find them, so that it can be used to avoid vulnerability scanner applications that are widely used by attackers to find out web system weaknesses. This research was conducted by modifying the web application firewall (WAF) and testing using the SQLMap and OWASP Zed Attack Proxy (ZAP) vulnerability scanner applications. The results of the study show that SQLMap takes up to 1238 times longer to complete a scan on a modified web application firewall than without modification, while OWASP ZAP cannot complete a scan on the same treatment. Thus the concept of security through obscurity can be applied to web security to extend vulnerability scanning time.

Enhancing Performance of Software Testing Automation using Selenium Web Grid

Web application testing is crucial to ensuring software quality and dependability. Selenium, a popular open-source testing framework, is widely used for automating web browsers to perform various testing tasks. One of the key components of Selenium is Selenium WebGrid, a distributed testing infrastructure that allows running tests in parallel across multiple nodes. This paper presents a comprehensive study on measuring the performance of Selenium WebGrid. The objective is to evaluate its efficiency, scalability, and reliability in executing test scripts across different browsers and operating systems. The study compares the performance of Selenium WebGrid with other testing approaches, such as traditional Selenium Grid and single-node Selenium execution. The methodology employed in this study involves designing a set of representative test cases that simulate real-world scenarios. These test cases cover a range of typical web application functionalities, including form submissions, page navigation, and data validation. The performance metrics considered for evaluation include execution time, resource utilization, and test throughput. To measure the performance of Selenium WebGrid, a testbed environment is set up consisting of multiple nodes with different configurations. The test scenarios are executed on the WebGrid infrastructure, and the performance metrics are collected and analyzed. The results are then compared with those obtained from traditional Selenium Grid and single-node Selenium execution to identify the performance advantages and limitations of Selenium WebGrid. It demonstrates the improved scalability and efficiency of WebGrid in executing tests across multiple nodes simultaneously. The results also provide insights into the resource requirements and trade-offs associated with using Selenium WebGrid compared to other testing approaches. This work adds to the body of knowledge by presenting empirical data on Selenium WebGrid's performance characteristics. It serves as a valuable resource for software testing professionals and researchers interested in leveraging Selenium WebGrid for distributed web application testing.

Enhancing Performance of Software Testing Automation using Selenium web grid

Web application testing is crucial to ensuring software quality and dependability. Selenium, a popular open-source testing framework, is widely used for automating web browsers to perform various testing tasks. One of the key components of Selenium is Selenium WebGrid, a distributed testing infrastructure that allows running tests in parallel across multiple nodes. This paper presents a comprehensive study on measuring the performance of Selenium WebGrid. The objective is to evaluate its efficiency, scalability, and reliability in executing test scripts across different browsers and operating systems. The study compares the performance of Selenium WebGrid with other testing approaches, such as traditional Selenium Grid and single-node Selenium execution. The methodology employed in this study involves designing a set of representative test cases that simulate real-world scenarios. These test cases cover a range of typical web application functionalities, including form submissions, page navigation, and data validation. The performance metrics considered for evaluation include execution time, resource utilization, and test throughput. To measure the performance of Selenium WebGrid, a testbed environment is set up consisting of multiple nodes with different configurations. The test scenarios are executed on the WebGrid infrastructure, and the performance metrics are collected and analyzed. The results are then compared with those obtained from traditional Selenium Grid and single-node Selenium execution to identify the performance advantages and limitations of Selenium WebGrid. It demonstrates the improved scalability and efficiency of WebGrid in executing tests across multiple nodes simultaneously. The results also provide insights into the resource requirements and trade-offs associated with using Selenium WebGrid compared to other testing approaches. This work adds to the body of knowledge by presenting empirical data on Selenium WebGrid's performance characteristics. It serves as a valuable resource for software testing professionals and researchers interested in leveraging Selenium WebGrid for distributed web application testing.

Investigating the robustness of locators in template-based Web application testing using a GUI change classification model

GUI-based test-cases generated by Capture and Replay tools suffer from the well-known fragility problem: they may break even if small layout changes are operated in a Web application, without modifying the app functionality. An approach based on the automatic injection of HTML tag attributes named hooks in the source code of Web templates has been recently proposed to solve this problem. Such hooks allow the unique identification of GUI items to be located during test case execution. This technique showed its effectiveness in a preliminary validation study, where it allowed to significantly reduce the number of test case locator breakages in regression testing of student-made Web applications. This paper presents a further validation study where we compared the robustness of hook-based test cases against state-of-the-art and state-of-the-practice techniques for locating GUI objects. We proposed a three dimensional model for classifying different types of layout changes and used it to define a benchmark of realistic changes. Thanks to the model, we systematically compared the robustness of test cases generated by different techniques with respect to specific types of changes and studied the relationship between fragility issues and types of changes in different test case generation techniques.

Analysis of web application testing methods

An important practical task for developers is the rapid creation and maintenance of high-quality multi-level software. It is assumed that the developed product will meet the qual-ity characteristics. And, if we talk about testing applications of different types, then you should pay attention to their features. For example, web applications have critical areas that must be checked. Thus, the purpose of this article is to analyse various methods and technics for testing web applications. The article provides a detailed analysis of the latest publications related to testing web applications. It turned out that most of the articles are aimed at describing terms or general information about testing. Several articles describe automated testing with Selenium, IBM Rational, SilkPerformer, TestComplete, HP QuickTest Professional, JUnit and compare them in terms of efficiency in various applications. However, most of the articles are devoted to various aspects of manual testing. In order to identify the factors that distinguish web application testing from desktop ap-plication testing, a table has been compiled comparing them according to the following crite-ria: environment, platform, deployment and updating, architecture, connectivity, availability. This comparison shows that web applications have several features that need to be consid-ered when testing them. In our opinion, the main critical areas of web applications that require additional de-scription and instructions are unity of design, navigation and "friendliness" to the user, func-tionality, security, compatibility with browsers and operating systems, and productivity. The article describes the specifics of testing critical zones and gives an estimate of the resource consumption of their testing. Tests are also recommended, which are useful for testing web and desktop applications.

Automated web testing over the last decade: A systematic literature review

Web applications play a vital role in every section ranging from business to administration, making operations efficient. Reliability must be ensured to avoid loss of credibility and revenue. Testing modern web applications is very tedious due to their dynamic and asynchronous nature. Web applications evolve rapidly to serve the growing needs of the customers and manual testing is often infeasible to maintain the reliability and validity of the system due to time and resource constraints. Automated web application testing is an ongoing popular research domain due to the complexity imposed by web applications. This paper conducts a systematic literature review on the practices of automated web testing over the past decade. PRISMA framework is used to screen the most relevant research papers using Scopus and Web of Science as the database. A total of 26 papers were selected based on the inclusion criteria and quality assessment. The articles were fetched and their contributions are documented to know about current practices and the effectiveness of such approaches in minimizing human effort. Results indicate broadly two categories of automated testing, one depending on the tester’s expertise to generate test cases, and the other relying on crawlers to exploit the system dynamically.

GUI-Based Automated Testing Tool with Exploratory Behavioral Analysis for Enhanced Software Quality Assurance

Testing web-based apps is difficult because of the intricate nature of these programmes. Automated methods used in computerised testing make ensuring that tasks are distributed fairly and reduce the influence of human mistake. This article’s goal is to provide our system for automating the testing of web applications. It was possible to effectively construct this state-of-the-art automated testing framework thanks to the Selenium WebDriver tool. As a result of this setup, PyAutoGUI may be used to automatically traverse through websites and match widgets to a pre-trained dataset. With the framework’s screenshot feature, designers may examine their previous work with more ease. Our team has come up with a novel approach to finding, categorising, and rating widgets by using machine learning and image processing techniques. Using this method, you may quickly get the images needed for the GUI widgets from the server by inputting the URL for the training data. Datasets are checked for the presence of GUI widgets using BLOB text detection. After locating all widgets, they are classified according to their various uses. Widgets may take several forms, including labels, buttons, input fields, checkboxes, and links. Finally, we make sure the overall GUI component categorization is as precise as possible by performing a series of checks. In order to identify the different kinds of widgets, our project used image processing rather than graphical user interfaces coded in languages like Java, Python, or Visual Basic. Test coverage was increased to 98.4 percent after we successfully implemented automated testing for online apps.

Comparative analysis of methods for testing web applications

The aim of the study was to conduct a comparative analysis of testing approaches for web applications in the two most popular architectures: monolithic and microservices. For the purpose of the study, the server-side of the application (backend) was implemented twice with identical functionalities for each of these architectures, allowing for a precise comparison of testing differences for the same program capabilities. The results revealed that the monolithic application was easier and faster to test. However, the microservices architecture requires more energy spent on testing, but allows better scalability and elasticity for independent teams to develop applications. Each of the examined architectures certainly has its own advantages and drawbacks. Furthermore, the conducted research indicates that unit tests require significantly less time to execute. However, when it comes to comprehensive code analysis, integration tests outperform unit tests by covering a substantial portion of the application's code with a single test. Nonetheless, the best comprehensive code analysis and protection against unwanted functional changes can be achieved by employing all known types of tests.