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He, Zhong Hai, Xiang Zhang, and Xiang Yin Zhu. "Design and Implementation of Automation Testing Framework Based on Keyword Driven." Applied Mechanics and Materials 602-605 (August 2014): 2142–46. http://dx.doi.org/10.4028/www.scientific.net/amm.602-605.2142.
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For the purpose of settling problems in the present automated testing frameworks, the paper presents an automated testing framework based on keyword driven technology. At first, it summarized and analyzed the recent automated testing frameworks; and then it proposed the framework’s system architecture, and also presented the key technology details of the framework. At last, this paper compared this paper’s framework with the recent frameworks by the IP phone, which proved that this framework had superiority in reducing the scale of test scripts, raising the overall efficiency of testing and so on.
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Noonan, Robert E., and Richard H. Prosl. "Unit testing frameworks." ACM SIGCSE Bulletin 34, no. 1 (2002): 232–36. http://dx.doi.org/10.1145/563517.563429.
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Neelapu, Mohnish. "Hybrid Testing Frameworks: Benefits and Challenges in Automation." International Journal of Multidisciplinary Research and Growth Evaluation 6, no. 1 (2025): 2164–69. https://doi.org/10.54660/.ijmrge.2025.6.1.2164-2169.
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The Hybrid Automation Framework is structured around the core principles of test automation, which include test independence, idempotency, and clarity—essential elements for developing a robust testing suite. This document details the development of Hybrid Test Automation Framework also provides an overview of its architecture and design. The framework is user-friendly and integrates a high-level programming language that supports object-oriented design, facilitates low-level access to user interface components, and allows for rapid recovery from alterations to the user interface of the application. The framework's architecture features a multi-layered design that separates browser UI components from test scripts. It incorporates various hybrid methodologies, including Linear Scripting, Module-Based Testing, Keyword-Driven Testing, as well as Data-Driven Testing. Additionally, the paper addresses both the advantages and challenges associated with the implementation of hybrid testing automation frameworks.
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Neelapu, Mohnish. "Hybrid Testing Frameworks: Benefits and Challenges in Automation." International Journal of Multidisciplinary Research and Growth Evaluation. 6, no. 1 (2025): 2164–68. https://doi.org/10.54660/.ijmrge.2025.6.1.2164-2168.
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The Hybrid Automation Framework is structured around the core principles of test automation, which include test independence, idempotency, and clarity—essential elements for developing a robust testing suite. This document details the development of Hybrid Test Automation Framework also provides an overview of its architecture and design. The framework is user-friendly and integrates a high-level programming language that supports object-oriented design, facilitates low-level access to user interface components, and allows for rapid recovery from alterations to the user interface of the application. The framework's architecture features a multi-layered design that separates browser UI components from test scripts. It incorporates various hybrid methodologies, including Linear Scripting, Module-Based Testing, Keyword-Driven Testing, as well as Data-Driven Testing. Additionally, the paper addresses both the advantages and challenges associated with the implementation of hybrid testing automation frameworks.
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Arjun, Mantri. "Enhancing Data Quality in Data Engineering using Data Testing Framework: Types and Tradeoffs." European Journal of Advances in Engineering and Technology 7, no. 10 (2020): 95–100. https://doi.org/10.5281/zenodo.13354036.
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Ensuring high data quality is critical in the era of big data, where reliable data is essential for accurate decision-making and business intelligence. This paper reviews various data testing frameworks designed to enhance data quality, including data validation, data cleansing, data profiling, data lineage, and automated testing frameworks. Each type of framework offers unique functionalities and presents distinct tradeoffs, such as customization versus complexity and real-time versus batch processing. By understanding these frameworks and their tradeoffs, data engineers can make informed decisions to implement the most suitable methods for their specific needs, ultimately ensuring robust data quality management.
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Praveen, Kumar Koppanati. "Hybrid Automation Frameworks Using Java and JavaScript for Cross-Language Applications." Journal of Scientific and Engineering Research 8, no. 6 (2021): 206–10. https://doi.org/10.5281/zenodo.13912358.
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The growing complexity of web and mobile applications has necessitated the adoption of hybrid automation frameworks that can seamlessly integrate with both backend and frontend components. With Java being a dominant language for server-side logic and JavaScript leading on the client side, automation frameworks need to support cross-language testing to ensure comprehensive test coverage. This paper discusses hybrid automation frameworks that combine the strengths of Java and JavaScript for end-to-end testing of web and mobile applications. We analyze popular frameworks such as Selenium, Appium, TestNG, Jasmine, and Protractor and demonstrate how they can be integrated into a cohesive testing environment. The paper also explores techniques for handling asynchronous operations, managing cross-browser compatibility, and synchronizing test data. Best practices for designing and implementing a modular, scalable, and maintainable hybrid automation framework are provided, with case studies that demonstrate its application in real-world projects.
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Praveen, Kumar Koppanati. "Parallelizing Automated UI and API Tests for Java Applications." Journal of Scientific and Engineering Research 10, no. 3 (2023): 155–59. https://doi.org/10.5281/zenodo.13912400.
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The growth and complexity of modern Java applications require newer testing strategies to make it efficient and faster. Automated testing, both for User Interfaces (UI) and Application Programming Interfaces (APIs), is crucial in maintaining the reliability and robustness of these applications. However, traditional approaches to automated testing often involve sequential execution, which can lead to significant delays in feedback and increased time-to-market. This paper discusses the parallelization of automated UI and API tests for Java applications to improve performance and testing efficiency. Leveraging the inherent concurrency of modern hardware and distributed systems, we explore techniques for parallel test execution, examining frameworks such as Selenium, TestNG, and JUnit. By implementing parallelization strategies, organizations can significantly reduce test execution times, enhance resource utilization, and improve the overall quality of software delivery. Additionally, we discuss the potential challenges, including test dependencies, data management, and synchronization issues, and provide solutions to address these concerns.
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Deepti, Sharma, Bharti Pragya, and Kumar Sablaniya Ankit. "AI in Software Testing: Enhancing Testing Frameworks with Artificial Intelligence." Journal of Advanced Research in Artificial Intelligence & It's Applications 2, no. 2 (2025): 15–17. https://doi.org/10.5281/zenodo.14916914.
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<em>Software testing plays a crucial role in ensuring the quality and reliability of software systems. Traditional testing methods, while effective, often require significant time and manual effort, making them prone to human error. The integration of Artificial Intelligence (AI) into software testing presents a ground breaking solution by automating test case generation, execution, and defect detection. This paper explores how AI-driven automated testing frameworks are transforming the software development lifecycle, highlighting key technologies, their benefits, and real-world applications. Additionally, we analyse challenges, limitations, and future trends in AI-powered testing frameworks to provide a comprehensive understanding of the evolving landscape of software testing.</em> <strong><em> </em></strong>
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Sachin, Sharma, Saini Akash, and Sharma Deepti. "Review of Software Testing Models and Performance Optimization Techniques." Journal of Advancement in Software Engineering and Testing 8, no. 1 (2025): 36–38. https://doi.org/10.5281/zenodo.14770935.
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<em>Software testing is still a vital activity to ensure the quality, reliability, and security of software. This review paper discusses current software testing models and performance optimization strategies. The review is based on various frameworks and tools and emphasizes automation and AI advancements. Key models include Waterfall, V-Model, Agile, and Spiral, each of which has specific characteristics and uses. Optimization techniques, such as fault localization and combinatorial testing, are also assessed. Scalability and AI model biases are identified as challenges and future research ideas in intelligent testing frameworks are presented.</em>
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Berihun, Natnael Gonfa, Cyrille Dongmo, and John Andrew Van der Van der Poll. "The Applicability of Automated Testing Frameworks for Mobile Application Testing: A Systematic Literature Review." Computers 12, no. 5 (2023): 97. http://dx.doi.org/10.3390/computers12050097.
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Mobile applications are developed and released to the market every day. Due to the intense usage of mobile applications, their quality matters. End users’ rejection of mobile apps increases from time to time due to their low quality and lack of proper mobile testing. This indicates that the role of mobile application testing is crucial in the acceptance of a given software product. Test engineers use automation frameworks for testing their mobile applications. Automated testing brings several advantages to the development team. For example, automated checks are used for regression testing, fast execution of test scripts, and providing quick feedback for the development team. A systematic literature review has been used to identify and collect evidence on automated testing frameworks for mobile application testing. A total of 56 relevant research papers were identified that were published in prominent journals and conferences until February 2023. The results were summarized and tabulated to provide insights into the suitability of the existing automation testing framework for mobile application testing. We identified the major test concerns and test challenges in performing mobile automation testing. The results showed that the keyword-driven testing framework is the widely used approach, but recently, hybrid approaches have been adopted for mobile test automation. On the other hand, this review indicated that the existing frameworks need to be customized using reusable and domain-specific keywords to make them suitable for mobile application testing. Considering this, this study proposes an architecture, the mobile-based automation testing framework (MATF). In the future, to address the mobile application testing challenges, the authors will work on implementing the proposed framework (MATF).
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Hanna, Milad, Amal Elsayed, and Mostafa-Sami M. "Automated Software Testing Frameworks: A Review." International Journal of Computer Applications 179, no. 46 (2018): 22–28. http://dx.doi.org/10.5120/ijca2018917171.
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Zhou, Hang, Weiren Sun, Yu Jiang, and Yi Zhu. "Polymorphism Testing Frameworks of Sequence Diagrams." Advanced Science Letters 6, no. 1 (2012): 851–54. http://dx.doi.org/10.1166/asl.2012.2303.
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Swamy Prasadarao Velaga. "AUTOMATED TESTING FRAMEWORKS: ENSURING SOFTWARE QUALITY AND REDUCING MANUAL TESTING EFFORTS." International Journal of Innovations in Engineering Research and Technology 5, no. 2 (2018): 78–85. http://dx.doi.org/10.26662/ijiert.v5i2.pp78-85.
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The purpose of this research study is to review and analyze the automated testing frameworks thoroughly with the main areas of focus on the quality assurance of the software and the minimization of testing that is done manually. The research aims and objectives are as follows: This is in relation to the historical development of these frameworks, their types, and their essential characteristics The examination of their effectiveness in enhancing software quality Determine the extent of diminished manual testing efforts The examination of the various ineffectiveness and drawbacks related to the frameworks [1]. Moreover, it presents an aim to reveal best practices, to assess their usage in CI/CD pipelines, and compare the cost and benefits impatient of the practices; to analyze their compliance with the current legislation and industrial standards and to investigate the trends in the further development of the field. Automated testing frameworks (ATFs) are becoming increasingly popular and are practically valuable in custom software development[1]. ATFs are utilized to reduce the manual effort to perform testing and ensure high-quality, robust software. ATFs can be easily implemented for integration and system testing, but there are challenges to implement unit testing automation.Software testers use a number of testing techniques to assess the quality of software, which helps in ensuring that the software meets its requirements and is delivered with minimal defects. Manual testing is performed by a human executing an application to verify different operations of an application and to validate different test conditions. Although manual testing will always have a role in software testing, it does have some limitations. Some of the limitations of manual testing can be overcome by using test automation[1]. Test automation is the use of software to control the execution of tests and to compare the actual results with the expected results. Test automation can be used in repetitive tasks, tasks that are difficult or impossible to do manually, and tasks that are performed under extreme conditions. Test automation can perform testing effectively and efficiently. Automated Testing Frameworks (ATFs), also known as test automation frameworks, are an approach to automate software testing activities to verify different test scenarios and conditions of a software system. The ATF combines automated test scripts and test data and repositories with components that execute pre-test and post-test actions, and reporting to form a structure that supports automated testing[2].With the growing acceptance of agile development and DevOps methodologies, the time allotted for testing has been dramatically reduced. As a result, testers are under pressure to quickly validate the quality of the software and are turning to automated testing. Many test automation frameworks have been developed to assist testers with executing and reporting results of their automated tests. These frameworks can also help reduce the effort involved in test script development.
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Taylor, Greg. "Credibility, Hypothesis Testing and Regression Software." ASTIN Bulletin 37, no. 2 (2007): 517–35. http://dx.doi.org/10.1017/s0515036100014975.
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It has been known since Zehnwirth (1977) that a scalar credibility coefficient is closely related to the F-statistic of an analysis of variance between and within risk clauses. The F-statistic may also be viewed as testing a certain regression structure, associated with credibility framework, against the null hypothesis of a simpler structure.This viewpoint is extended to multi-dimensional credibility frameworks in which the credibility coefficient is a matrix (Sections 3 and 4), and to hierarchical regression credibility frameworks (Section 6). In each case the credibility coefficient is expressed in terms of the F-statistic that tests the significance of a defined regression structure against a simpler one.Section 5 points out how the computation may be implemented in certain cases by means of regression software.
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Shtokal, Alla, and Jakub Smołka. "Comparative analysis of frameworks used in automated testing on example of TestNG and WebdriverIO." Journal of Computer Sciences Institute 19 (June 30, 2021): 100–106. http://dx.doi.org/10.35784/jcsi.2595.
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The article presents a comparative analysis of frameworks supporting the development of automated tests for defined test scenarios. The comparative study concerned the TestNG and WebDriverIO frameworks. The overview of the tool has been analyzed both in terms of the test development process as well as the speed and efficiency of their execution. The website github.com was used for the purposes of the work. This application was used to run test scripts written in both frameworks. The results were compared by five defined criteria: the time of running the test files in different browser operation modes, the average value of memory and CPU usage during the test execution. The summary includes the evaluation of the compared frameworks.
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Taylor, Greg. "Credibility, Hypothesis Testing and Regression Software." ASTIN Bulletin 37, no. 02 (2007): 517–35. http://dx.doi.org/10.2143/ast.37.2.2024078.
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It has been known since Zehnwirth (1977) that a scalar credibility coefficient is closely related to the F-statistic of an analysis of variance between and within risk clauses. The F-statistic may also be viewed as testing a certain regression structure, associated with credibility framework, against the null hypothesis of a simpler structure. This viewpoint is extended to multi-dimensional credibility frameworks in which the credibility coefficient is a matrix (Sections 3 and 4), and to hierarchical regression credibility frameworks (Section 6). In each case the credibility coefficient is expressed in terms of the F-statistic that tests the significance of a defined regression structure against a simpler one. Section 5 points out how the computation may be implemented in certain cases by means of regression software.
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BAHRІI, Ruslan, and Serhii PETROVSKYI. "FEATURES OF MODERN WEB APPLICATION TESTING." Herald of Khmelnytskyi National University. Technical sciences 309, no. 3 (2022): 70–74. http://dx.doi.org/10.31891/2307-5732-2022-309-3-70-74.
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This paper investigates the technology and approaches to testing web applications in modern frameworks. The main techniques of manual testing, which require a large amount of manual work, are considered. The disadvantages of implementing the black-box testing method include the development of a formal specification, and the application of the white-box testing method requires analysis of software code. Particular attention is given to automated testing technologies, which are proposed to be used to develop sites in modern frameworks. The Test pyramid and test levels are described in detail, and the main advantages and disadvantages of each level are analyzed. At the first level, a set of tests consists of unit tests that verify that an individual unit is working correctly according to the requirements of the specification. At the second level of the automation pyramid – integration tests check the interaction of a fragment of code with external components. At the third level – end-to-end tests perform testing of various user scenarios, and UI tests check the correct operation of the web application interface. It is proposed to use behavioral development technology (BDD) for automated testing of web applications. BDD focuses on studying problems formulated based on customer stories and the construction of logic and tests based on these problems. BDD tests are best worked for integration testing, which involves testing different user scenarios. A dependency injection (DI) design template has been used to improve the efficiency of the web application development process, with tools built into modern frameworks. This template applies the transfer of dependencies to an external, specially designed software component. Dependence is injected using a special IoC container.
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Soujanya, Reddy Annapareddy. "Optimizing Android Device Testing with Automation Frameworks." INTERNATIONAL JOURNAL OF INNOVATIVE RESEARCH AND CREATIVE TECHNOLOGY 10, no. 4 (2024): 1–7. https://doi.org/10.5281/zenodo.14540907.
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The exponential growth of mobile applications has introduced new challenges in ensuring quality across the diverse ecosystem of Android devices. The fragmentation of hardware and software configurations demands robust and efficient testing methodologies. This paper investigates the optimization of Android device testing through the use of an advanced automation framework called Appium. By leveraging these frameworks, testing processes can achieve enhanced efficiency, scalability, and reliability. A case study is presented to illustrate the practical application of automation in testing an e-commerce mobile application, focusing on cross-device compatibility, responsiveness, and functionality. The study highlights the methodologies, tools, and metrics used to measure performance improvements, providing actionable insights for testers and developers.
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D., Rajya Lakshmi, and Suguna Mallika S. "A Review on Web Application Testing and its Current Research Directions." International Journal of Electrical and Computer Engineering (IJECE) 7, no. 4 (2017): 2132–41. https://doi.org/10.11591/ijece.v7i4.pp2132-2141.
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Testing is an important part of every software development process on which companies devote considerable time and effort. The burgeoning web applications and their proliferating economic significance in the society made the area of web application testing an area of acute importance. The web applications generally tend to take faster and quicker release cycles making their testing very challenging. The main issues in testing are cost efficiency and bug detection efficiency. Coverage-based testing is the process of ensuring exercise of specific program elements. Coverage measurement helps determine the ―thoroughness‖ of testing achieved. An avalanche of tools, techniques, frameworks came into existence to ascertain the quality of web applications. A comparative study of some of the prominent tools, techniques and models for web application testing is presented. This work highlights the current research directions of some of the web application testing techniques.
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Kurniasari, Dias Tri, and Siti Rochimah. "An evaluation model of website testing framework based on ISO 25010 performance efficiency." Indonesian Journal of Electrical Engineering and Computer Science 37, no. 2 (2025): 1130. http://dx.doi.org/10.11591/ijeecs.v37.i2.pp1130-1139.
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Testing is an important aspect of software development. Automation testing is now widely used to achieve better and more efficient results. Various automation testing frameworks are available in the market. However, one of the major challenges is determining which automation testing framework is suitable for testing. This study proposes an evaluation model for evaluating web automation testing frameworks based on seven performance efficiency factors to address this issue. The model evaluates five types of transactions commonly used on the web; CRUD, Get Massive Data, search, file upload, and file download. In addition, the tested frameworks are categorized as good, medium, and low. To measure the success of the research, expert weighting was also used. Based on the results obtained for all types of transactions, almost all classifications between the experimental results and weighting were in the same class. Although the model was found to be effective with a 100% accuracy rate, it had an accuracy rate of 80% for upload transactions. The outcomes of this study serve as a valuable reference for choosing suitable software for both tested frameworks and other software applications. In future studies focus on narrowing the selection based on not only performance but also functionality and ease of use.
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Dias, Tri Kurniasari Siti Rochimah. "An evaluation model of website testing framework based on ISO 25010 performance efficiency." Indonesian Journal of Electrical Engineering and Computer Science 37, no. 2 (2025): 1130–39. https://doi.org/10.11591/ijeecs.v37.i2.pp1130-1139.
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Testing is an important aspect of software development. Automation testing is now widely used to achieve better and more efficient results. Various automation testing frameworks are available in the market. However, one of the major challenges is determining which automation testing framework is suitable for testing. This study proposes an evaluation model for evaluating web automation testing frameworks based on seven performance efficiency factors to address this issue. The model evaluates five types of transactions commonly used on the web; CRUD, Get Massive Data, search, file upload, and file download. In addition, the tested frameworks are categorized as good, medium, and low. To measure the success of the research, expert weighting was also used. Based on the results obtained for all types of transactions, almost all classifications between the experimental results and weighting were in the same class. Although the model was found to be effective with a 100% accuracy rate, it had an accuracy rate of 80% for upload transactions. The outcomes of this study serve as a valuable reference for choosing suitable software for both tested frameworks and other software applications. In future studies focus on narrowing the selection based on not only performance but also functionality and ease of use.
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Madeja, Matej, Jaroslav Porubän, Sergej Chodarev, Matúš Sulír, and Filip Gurbáľ. "Empirical Study of Test Case and Test Framework Presence in Public Projects on GitHub." Applied Sciences 11, no. 16 (2021): 7250. http://dx.doi.org/10.3390/app11167250.
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Automated tests are often considered an indicator of project quality. In this paper, we performed a large analysis of 6.3 M public GitHub projects using Java as the primary programming language. We created an overview of tests occurrence in publicly available GitHub projects and the use of test frameworks in them. The results showed that 52% of the projects contain at least one test case. However, there is a large number of example tests that do not represent relevant production code testing. It was also found that there is only a poor correlation between the number of the word “test” in different parts of the project (e.g., file paths, file name, file content, etc.) and the number of test cases, creation date, date of the last commit, number of commits, or number of watchers. Testing framework analysis confirmed that JUnit is the most used testing framework with a 48% share. TestNG, considered the second most popular Java unit testing framework, occurred in only 3% of the projects.
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Gimatdinov, Damir Maratovich, Alexander Yurievich Gerasimov, Petr Alekseevich Privalov, Veronika Nikolaevna Butkevich, Natalya Andreevna Chernova, and Anna Antonovna Gorelova. "An Automated Framework for Testing Source Code Static Analysis Tools." Proceedings of the Institute for System Programming of the RAS 33, no. 3 (2021): 41–50. http://dx.doi.org/10.15514/ispras-2021-33(3)-3.
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Automated testing frameworks are widely used for assuring quality of modern software in secure software development lifecycle. Sometimes it is needed to assure quality of specific software and, hence specific approach should be applied. In this paper, we present an approach and implementation details of automated testing framework suitable for acceptance testing of static source code analysis tools. The presented framework is used for continuous testing of static source code analyzers for C, C++ and Python programs.
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Adiatma, Shidqi, and Astie Darmayantie. "Implementation and Comparative Analysis of Test Automation Framework Performance for Functional Testing of Web-Based Applications using the Distance to the Ideal Alternative (DIA) Method." Widya Teknik 22, no. 2 (2023): 36–41. http://dx.doi.org/10.33508/wt.v22i1.5027.
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The importance of functional testing is to ensure the quality of web-based applications so as to improve user experience (user experience) to make it more secure and reliable in ever-increasing market pressure. Can encourage many companies to build high-quality applications and he can release in a short time. Because of this, the testing process must be automated to ensure applications run quickly and effectively. There are several test automation frameworks, specifically for web-based applications that offer effective features and performance to test applications more effectively, such as Katalon Studio, Cypress and WebDriverIO. The purpose of this research is to find the best test automation framework based on performance with certain parameters and sub-parameters. The author runs functional testing on each test automation framework with several test cases and provisions from each framework in a web-based application, and generates reports from each framework with automation testing progress parameters and tool usability parameters using The Distance To The Ideal Alternative method (DIA), and determine the weight for each parameter and sub-parameters. The results of a comparative analysis of test automation frameworks for web-based applications show that WebDriverIO has the best performance compared to other test automation frameworks with a value of 0 in the DIA Method, indicating that WebDriverIO has zero distance from the ideal alternative.
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Saarathy, Sutharsan, Suresh Bathrachalam, and Bharath Rajendran. "Self-Healing Test Automation Framework using AI and ML." International Journal of Strategic Management 3, no. 3 (2024): 45–77. http://dx.doi.org/10.47604/ijsm.2843.
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Purpose: In the lifecycle of Product Development and Management, automated testing has become a cornerstone for ensuring product quality and accelerating release cycles. However, the maintenance of test automation suites often presents significant challenges, particularly due to the frequent changes in application interfaces that lead to broken tests. This paper explores the development and implementation of self-healing test automation frameworks that leverage Artificial Intelligence (AI) and Machine Learning (ML) techniques to automatically detect, diagnose, and repair broken tests. Methodology: By integrating AI/ML models capable of dynamic locator identification, intelligent waiting mechanisms, and anomaly detection, these frameworks can significantly reduce the maintenance burden associated with automated testing. The paper presents a comprehensive architecture of a self-healing test automation framework, detailing the AI/ML techniques employed and the workflow of the self-healing process. A real-world case study is included to demonstrate the practical application and benefits of the proposed framework. Findings: Evaluation results show substantial improvements in test suite reliability and reductions in maintenance time and costs. The AI/ML techniques used in the framework, such as dynamic locator identification and intelligent waiting mechanisms, proved effective in reducing the maintenance burden and improving the robustness of automated testing processes. Unique Contribution to Theory, Practice and Policy: This paper aims to provide insights into the potential of self-healing test automation frameworks to enhance the robustness and efficiency of automated testing processes. By adopting these frameworks, organizations can achieve more resilient and maintainable test automation strategies, ultimately contributing to higher product quality and faster release cycles.
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Pradeepkumar Palanisamy. "Cross-team component mocking frameworks for integration testing." World Journal of Advanced Engineering Technology and Sciences 7, no. 1 (2022): 245–56. https://doi.org/10.30574/wjaets.2022.7.1.0096.
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In the complex and interconnected landscape of modern distributed systems, efficient and reliable integration testing presents a formidable challenge, particularly when external or downstream services are unstable, under development, or costly to access. This comprehensive content explores the critical role and profound benefits of Cross-Team Component Mocking Frameworks. These sophisticated, shared tooling solutions are meticulously designed to simulate the precise responses of downstream services, external APIs, or complex third-party components. By establishing a controlled and consistent mock environment, these frameworks empower development and QA teams to conduct early and isolated validation of their service integrations, significantly mitigating dependencies. The strategic adoption of such frameworks dramatically improves Continuous Integration (CI) pipeline reliability by eliminating external flakiness, facilitates crucial frontend-backend decoupling for parallel development, and fundamentally enables true continuous testing even within highly unstable or unavailable environments. This deep dive outlines their architecture, key capabilities, and best practices for fostering a resilient, efficient, and collaborative integration testing strategy across diverse teams and service boundaries.
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Devyatovskaya, A. D., N. E. Biryuchkov, T. V. Liakh, and K. V. Chaika. "SLAM in Duckietown Simulator Using the OpenVSLAM Framework." Vestnik NSU. Series: Information Technologies 19, no. 4 (2022): 36–49. http://dx.doi.org/10.25205/1818-7900-2021-19-4-36-49.
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The article is devoted to evaluating the applicability of SLAM frameworks for the task of mobile robots of the Duckietown project. The paper provides a comparative analysis of existing SLAM algorithms and frameworks and se-lects frameworks taking into account all the constraints imposed by the project robots. The practical results of testing OpenVSLAM framework on the Duckietown environment and Duckietown simulator data are presented.
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Agrawal, Sachin, and Prabhat Chauhan. "Debugging Error with The Help of Software Testing Methods." International Journal of Ingenious Research, Invention and Development (IJIRID) 1, no. 1 (2023): 26–28. https://doi.org/10.5281/zenodo.7821125.
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Software development is the process of conceiving, specifying, designing, programming, documenting, testing, and bug fixing involved in creating and maintaining applications, frameworks, or other software components software testing is an activity to check whether the actual results match the expected results and to ensure that the software system is Defect free. Testing is a very important step in software development to ensure that the software does properly, what it is supposed to do. While the development of the software there arise certain problems that leads to error, defects, and complications in the software testing to make the software run smoothly. In this report, I tried to over whole software testing, why software testing is required, hoe test cased are made, types of testing, levels of testing, method of testing, why software testing, levels of testing, method of testing & further how important software testing is. In short, we can say that testing is the last step in the software development life cycle.
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Twinkle, Joshi. "Breaking Down Automation Frameworks: Building Blocks for Better Testing." European Journal of Advances in Engineering and Technology 11, no. 11 (2024): 104–16. https://doi.org/10.5281/zenodo.15234713.
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Automation frameworks are the cornerstone of efficient and scalable software testing, providing structured methodologies and reusable components to enhance quality assurance and streamline processes. This article explores the essential building blocks of automation frameworks, highlighting their role in transforming testing practices through advanced tools, design patterns, and innovative approaches. By automating repetitive tasks, frameworks enable QA professionals to focus on high-value activities such as test design and usability evaluations, delivering benefits including improved accuracy, scalability, reduced manual effort, and comprehensive test coverage. Hierarchical strategies, such as the "Test Pyramid," emphasize foundational unit tests complemented by integration and end-to-end tests, optimizing testing efficiency across diverse environments. Structured frameworks—Linear Scripting, Modular, Data-Driven, Keyword-Driven, Hybrid, and Behavior-Driven Development (BDD)—cater to diverse project needs, offering flexibility and adaptability. Design patterns like Page Object Model (POM), Factory, Facade, Singleton, and Fluent POM further enhance modularity, scalability, and maintainability, ensuring robust automation architecture. Emerging methodologies, such as No-Code Test Automation, redefine accessibility through intuitive interfaces, visual workflows, and reusable components, empowering non-technical contributors to engage actively in testing processes. Integration with technologies like Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), and Robotic Process Automation (RPA) optimizes execution, fosters collaboration, and supports advanced reporting and CI/CD pipeline integration. Despite their advantages, automation frameworks face challenges, including high setup costs, maintenance demands, and limited UX and exploratory insights. Addressing these limitations through strategic prioritization and ongoing refinement enables organizations to leverage automation frameworks as vital building blocks for delivering reliable, high-quality software. This article delves into the methodologies, components, and technologies that comprise automation frameworks, showcasing their pivotal role in driving agility, scalability, and innovation in modern software engineering.
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Ichanska, N. "Tools and instruments for developing a web application with student knowledge level testing." Mechanics And Mathematical Methods 6, no. 1 (2024): 95–106. http://dx.doi.org/10.31650/2618-0650-2024-6-1-95-106.
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This work is dedicated to the exploration of modern web application development technologies and their use in assessing knowledge levels. Current and relevant technologies facilitating web application creation were studied, and a comparative analysis of the most popular frameworks for web development was conducted. The research subject of this scientific work revolves around existing contemporary frameworks and tools utilized in developing web applications. The study concentrates on learning about current technologies associated with web application development and their utilization in assessing knowledge levels. A thorough analysis of contemporary methodologies facilitating an effective web-oriented application development process was carried out. The key technologies forming the foundation of web application development were scrutinized and elaborately described, including a comparative analysis of the most widely used frameworks for web development. Tools aiding in development support were examined, and an educational web application for conducting online testing was created. Particular emphasis was given to instruments fostering effective project development and support. The work delved into development support tools and their role in creating web applications. The authors developed an educational web application for online testing, utilizing one of the most popular JavaScript frameworks - Angular. The objective of this work was to select a modern framework for educational web application development. The primary goal was to choose a contemporary framework for crafting an educational web application and develop a fully functional web application ready for use. The outcomes included the creation of a fully functional web application ready for deployment. This web application resulted from a comprehensive study of contemporary frameworks and tools for web application creation. It can be utilized in the educational sphere for conducting tests and assessing knowledge levels, as well as in other fields requiring online testing and the collection of user knowledge information.
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Pelivani, Elis, Adrian Besimi, and Betim Cico. "Customized Software Testing Framework for Web Applications." International Journal of Recent Contributions from Engineering, Science & IT (iJES) 10, no. 01 (2022): 76–85. http://dx.doi.org/10.3991/ijes.v10i01.29473.
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Software testing is gaining more attention and investments in the IT companies. We have both manual and automated approaches, considering the dynamic of the project the appropriate one is chosen. There have been presented and used several frameworks and tools for this purpose. However, the outcome is that a single tool does not cover all the testing needs of IT systems. In this paper, we will present a customized framework based in Selenium that tackle this gap within the IT systems where several modules with many cross function are involved. We will present the architecture overview and a case study
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Abhishek Nimdia. "Optimization of Automated Testing Frameworks for High-Performance Environments." International Journal of Engineering and Computer Science 14, no. 05 (2025): 27199–206. https://doi.org/10.18535/ijecs.v14i05.5122.
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This study explores the optimization of automated testing frameworks for high-performance computing environments, including IoT systems. A comprehensive analysis of existing challenges is conducted, including device heterogeneity, interoperability issues, scalability constraints, and security concerns. The study identifies potential solutions through the integration of modern artificial intelligence (AI) techniques and self-healing mechanisms. The methodology is based on an analysis of publicly available scientific research. Empirical evaluations and implementation examples demonstrate improvements in testing efficiency, reliability, and adaptability, as confirmed by previous research findings. The insights presented in this study will be valuable to researchers and practitioners in high-performance computing, as well as professionals involved in the development and optimization of automated testing frameworks, aiming to ensure reliable and scalable testing of complex distributed environments. Additionally, this study may serve as a valuable resource for project managers and strategists in the IT industry interested in adopting innovative testing methods to enhance the efficiency and resilience of mission-critical applications.
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Latif, Ummi Khaira, and Tien Fabrianti Kusumasari. "COMPARISON BETWEEN YII FRAMEWORKS AND LARAVEL IN 3 DIFFERENT VERSION FOR VIEWING LARGE DATA OF SHIPYARD INDUSTRY IN INDONESIA." International Journal of Innovation in Enterprise System 2, no. 01 (2018): 13–18. http://dx.doi.org/10.25124/ijies.v2i01.12.
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The objective of this paper is to compare two PHP frameworks with execution time, peak memory usage and throughput metrics. This performance comparison was done for Laravel and Yii2 frameworks using MySQL employee database [26] which freely downloaded for testing necessary. The database provided a large amount of data included million entry records. Using a large amount of record, we try to give some view to another developer for considering when choosing the PHP framework for their development. The result in this paper give Laravel has better performance in execution time and throughput measurement but not in memory usage. This result can be affected by many factors including the testing environment in when comparison process implementation.
 
 Keywords—Laravel, Yii2, PHP Framework, Performance Comparison.
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Hemanth Aditya. "Building scalable android testing frameworks: Lessons from google chat UI refresh." International Journal of Science and Research Archive 14, no. 1 (2025): 712–19. https://doi.org/10.30574/ijsra.2025.14.1.0058.
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This article uses the successful implementation of the Google Chat UI Refresh project to provide thorough insights into creating scalable testing frameworks for Android applications. It examines several contemporary Android testing topics, such as multi-layered testing methodologies, optimal test architecture methods, and particular concerns for Jetpack Compose. The article illustrates how appropriate testing frameworks can greatly increase development efficiency, lower errors, and improve overall application quality by analyzing real-world implementation tactics. Considerations for continuous integration and the significance of performance monitoring in mobile testing settings are emphasized. For teams seeking to put into practice reliable testing techniques that may develop with their application, the results provided provide insightful advice.
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Alemayehu, Hayleyesus, and Arman Sargolzaei. "Testing and Verification of Connected and Autonomous Vehicles: A Review." Electronics 14, no. 3 (2025): 600. https://doi.org/10.3390/electronics14030600.
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Connected and Autonomous Vehicles (CAVs) have the potential to revolutionize transportation by addressing critical challenges such as safety, energy efficiency, traffic congestion, and environmental impact. Realizing these benefits, however, requires the development of a rigorous testing and verification framework to enable the safe, efficient, and reliable deployment of CAVs across diverse operational scenarios. Despite the growing body of research, there remains a significant gap in review papers that comprehensively summarize recent studies related to the testing and verification of CAVs while identifying current challenges and highlighting future research directions. This paper seeks to address this gap by presenting a comprehensive review of the existing testing and verification frameworks for CAVs and identifying their associated challenges. Key topics covered include scenario generation, verification cost functions, assertion values, and security considerations. Furthermore, the paper highlights limitations within current frameworks, emphasizing the gaps that hinder systematic and comprehensive evaluations.
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Piggott, Thomas, Lorenzo Moja, Carlos A. Cuello Garcia, et al. "User-experience testing of an evidence-to-decision framework for selecting essential medicines." PLOS Global Public Health 4, no. 1 (2024): e0002723. http://dx.doi.org/10.1371/journal.pgph.0002723.
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Essential medicine lists (EMLs) are important medicine prioritization tools used by the World Health Organization (WHO) EML and over 130 countries. The criteria used by WHO’s Expert Committee on the Selection and Use of Essential Medicines has parallels to the GRADE Evidence-to-Decision (EtD) frameworks. In this study, we explored the EtD frameworks and a visual abstract as adjunctive tools to strengthen the integrate evidence and improve the transparency of decisions of EML applications. We conducted user-experience testing interviews of key EML stakeholders using Morville’s honeycomb model. Interviews explored multifaceted dimensions (e.g., usability) on two EML applications for the 2021 WHO EML–long-acting insulin analogues for diabetes and immune checkpoint inhibitors for lung cancer. Using a pre-determined coding framework and thematic analysis we iteratively improved both the EtD framework and the visual abstract. We coded the transcripts of 17 interviews with 13 respondents in 103 locations of the interview texts across all dimensions of the user-experience honeycomb. Respondents felt the EtD framework and visual abstract presented complementary useful and findable adjuncts to the traditional EML application. They felt this would increase transparency and efficiency in evidence assessed by EML committees. As EtD frameworks are also used in health practice guidelines, including those by the WHO, respondents articulated that the adoption of the EtD by EML applications represents a tangible mechanism to align EMLs and guidelines, decrease duplication of work and improve coordination. Improvements were made to clarify instructions for the EtD and visual abstract, and to refine the design and content included. ‘Availability’ was added as an additional criterion for EML applications to highlight this criterion in alignment with WHO EML criteria. EtD frameworks and visual abstracts present additional important tools to communicate evidence and support decision-criteria in EML applications, which have global health impact. Access to essential medicines is important for achieving universal health coverage, and the development of essential medicine lists should be as evidence-based and trustworthy as possible.
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Veeranna, Kotagi. "Adaptive and Predictive Testing Frameworks Using Chaos Engineering and Deep Learning for Enterprise QA." Recent Trends in Data Knowledge Discovery and Data Mining 1, no. 1 (2025): 16–22. https://doi.org/10.5281/zenodo.15187073.
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<em>As enterprise software systems grow in complexity and scale, traditional quality assurance (QA) methods fall short in predicting failures and ensuring system resilience. This research proposes an innovative QA paradigm that integrates chaos engineering with deep learning to create adaptive and predictive testing frameworks. Chaos engineering introduces controlled disruptions to identify system weaknesses under real-world stress, while deep learning models analyze test outcomes to anticipate failure points and adapt testing strategies dynamically. The proposed framework supports continuous testing across microservices, cloud-native environments, and large-scale enterprise platforms. Experimental validation on simulated and real enterprise workloads demonstrates enhanced fault detection rates, reduced mean time to recovery, and intelligent test case prioritization. The results affirm that integrating chaos experimentation with AI-based learning models leads to more robust, self-improving QA processes capable of coping with the volatility and dynamism of modern software ecosystems.</em>
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Ansari, Mohammed Afzal, and Kiran Bhimrao Ingle. "Software Testing." International Journal for Research in Applied Science and Engineering Technology 10, no. 6 (2022): 979–84. http://dx.doi.org/10.22214/ijraset.2022.43914.
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Abstract— With the developing complexity of today’s software program applications injunction with the increasing competitive pressure has driven the excellent assurance of developed software towards new heights. software program trying out is an inevitable part of the software program development Lifecycle and retaining in keeping with its criticality in the pre and submit development process makes it something that have to be catered with stronger and green methodologies and strategies. This paper objectives to speak about the prevailing in addition to advanced trying out techniques for the betterquality warranty functions. Keywords— Testing Methodologies, Software Testing Life Cycle, Testing Frameworks, Automation Testing, Test Driven Development, Test optimization, Quality Metrics
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Komal, Jasani. "Creating a Scalable VR Testing Environment." International Journal of Leading Research Publication 5, no. 1 (2024): 1–9. https://doi.org/10.5281/zenodo.14982309.
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Virtual Reality (VR) technology has widespread adoption across industries, from gaming and training simulations to healthcare and industrial design. However, creating scalable VR testing environments remains challenging due to hardware limitations, software compatibility, and resource-intensive processes. This paper explores methodologies for designing and implementing scalable VR testing environments that optimize computational efficiency, enhance reproducibility, and support large-scale user testing. We discuss cloud-based VR simulations, distributed rendering techniques, and automation frameworks that facilitate robust testing across diverse VR applications. Additionally, we highlight the role of artificial intelligence (AI) in streamlining test case generation and performance evaluation. By addressing scalability constraints, our proposed approach aims to provide a flexible and cost-effective VR testing framework that accelerates development cycles and ensures high-quality user experiences.
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Tejada, Gabriela, Marina Cracco, Clémence Ranquet Bouleau, Jean-Claude Bolay, and Silvia Hostettler. "Testing Analytical Frameworks in Transdisciplinary Research for Sustainable Development." Sustainability 11, no. 16 (2019): 4343. http://dx.doi.org/10.3390/su11164343.
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This article discusses the concept and the practice of transdisciplinary research, including how it is conceived and implemented through the cooperation of different actors involved. With transdisciplinarity gaining recognition as an approach to addressing sustainable development challenges, the successful integration of various disciplines and actors in the process of knowledge generation becomes essential. Through the Cooperation and Development Center (CODEV), the Ecole Polytechnique Fédérale de Lausanne (EPFL) has promoted transdisciplinary research by proposing a space where North–South partnerships integrating academic and non-academic actors enable the expansion of appropriate technologies and innovations adapted to local societal contexts. This study examines five collaborative research projects conducted at the EPFL. By using an analytical framework consisting of design principles for ideal transdisciplinary research, we conducted semi-structured interviews with academic and non-academic members of the research projects to assess the degree of transdisciplinarity. This framework proved to be a useful tool for exploring transdisciplinary dynamics and assessing the effectiveness of joint knowledge generation. We found that the transdisciplinary cooperation involving different actors is not a linear process, as it depends on the social context in which the project is carried out and on the internal and the external organizational structure established for its implementation. We provide recommendations on how transdisciplinarity could be expanded through institutional support and its results could be effectively transferred into science and practice and discuss the implications for further studies in the conclusions.
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Ghani, M. Ahmad Nawaz ul, M. Shoaib Farooq, and Amjad Hussain Zahid. "Effectiveness of Agile Development Frameworks with Respect to Testing." VAWKUM Transactions on Computer Sciences 15, no. 2 (2018): 84. http://dx.doi.org/10.21015/vtcs.v15i2.518.
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Springer, Lena. "Frameworks of Choice: Predictive and Genetic Testing in Asia." East Asian Science, Technology and Society 10, no. 3 (2016): 333–36. http://dx.doi.org/10.1215/18752160-3624488.
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Marynowski, João Eugenio, Altair Olivo Santin, and Andrey Ricardo Pimentel. "Method for testing the fault tolerance of MapReduce frameworks." Computer Networks 86 (July 2015): 1–13. http://dx.doi.org/10.1016/j.comnet.2015.04.009.
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Researcher. "MACHINE LEARNING-DRIVEN TESTING PROCESS OPTIMIZATION: A SYSTEMATIC REVIEW OF CROSS-INDUSTRY APPLICATIONS AND IMPLEMENTATION FRAMEWORKS." International Journal of Computer Engineering and Technology (IJCET) 15, no. 6 (2024): 1126–38. https://doi.org/10.5281/zenodo.14327675.
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This comprehensive article examines the integration of machine learning technologies in testing process optimization across diverse industries, addressing the growing need for efficient and adaptive testing methodologies. The article analyzes the implementation of predictive analytics and adaptive testing models in streamlining quality control workflows while maintaining rigorous testing standards. Through a systematic examination of current applications, this article explores how artificial intelligence-driven approaches can effectively reduce testing cycles, minimize bottlenecks, and enhance overall testing efficiency. The article synthesizes evidence from multiple sectors, including software development, manufacturing, and healthcare, to present a unified framework for machine learning integration in testing processes. Key considerations regarding infrastructure requirements, data quality, and organizational challenges are discussed, along with strategies for successful implementation. The findings demonstrate that machine learning applications in testing optimization offer significant potential for improving productivity while maintaining quality standards, though careful consideration must be given to implementation strategies and organizational readiness. This article contributes to the growing body of knowledge on intelligent testing systems and provides practical insights for organizations seeking to modernize their testing processes through machine learning integration.
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Drzazga, Krzysztof, Marcin Bobel, and Maria Skublewska-Paszkowska. "Comparative analysis of selected object-relational mapping systems for the .NET platform." Journal of Computer Sciences Institute 16 (September 30, 2020): 285–92. http://dx.doi.org/10.35784/jcsi.2024.
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This article is devoted to the comparison of two object-relational mapping systems supported by .NET platform - Entity Framework Core and NHibernate. The research hypothesis “framework NHibernate is more efficient than Entity Framework Core in the context of DML operations” was put forward. In order to make an efficiency analysis of ORM frameworks, a desktop application was designed and implemented to enable testing and visualization of results. The NHibernate framework turned out to be much more efficient than Entity Framework Core in single tests and slightly faster in bulk tests. The stability of both frameworks was similar.
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Amit, Gupta. "Unveiling the Performance Divide: Appium's Slower Performance Compared to Native Frameworks." European Journal of Advances in Engineering and Technology 5, no. 12 (2018): 1077–81. https://doi.org/10.5281/zenodo.13235624.
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Mobile application testing plays a crucial role in the field of contemporary software development in guaranteeing user satisfaction and product quality. Since smartphones and tablets are part of daily life activities, mobile applications are essential tools for business, work, communication, and leisures. Therefore, the importance of performance in mobile application testing because customers demand faultless experiences that are characterized by effectiveness, dependability, and responsiveness. This research examines the differences between native testing frameworks like XCUITests for iOS and Espresso for Android and Appium, a popular cross-platform automation tool. The observed difficulties with Appium test automation, such as test flakiness and excessive execution response times, served as the impetus for this study. This paper aims to help practitioners and decision-makers choose the best automation tool for their mobile application testing requirements by shedding light on the performance implications of both Appium and native testing frameworks. To help with well-informed decision-making about mobile testing techniques, this study intends to shed light on the variations in test execution time, resource consumption, and dependability between Appium and native frameworks through statistical data and thorough analysis.
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Pandhare, Harshad Vijay. "Evaluating Large Language Models: Frameworks and Methodologies for AI/ML System Testing." International Journal of Scientific Research and Management (IJSRM) 12, no. 09 (2024): 1467–86. https://doi.org/10.18535/ijsrm/v12i09.ec08.
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Abstract As Large Language Models (LLMs) such as GPT-4, Claude, and LLaMA continue to redefine the frontiers of artificial intelligence, the challenge of evaluating these models has become increasingly complex and multifaceted. Traditional machine learning evaluation techniques—centered on metrics like accuracy, perplexity, and F1-score—are no longer sufficient to capture the breadth of capabilities, limitations, and risks associated with these powerful generative systems. This research addresses the growing demand for a robust and scalable evaluation methodology that can comprehensively assess LLMs across multiple dimensions, including performance, robustness, fairness, ethical safety, efficiency, and interpretability. The study begins with a critical examination of existing evaluation frameworks, ranging from benchmark-driven approaches and human-centered testing to adversarial prompt engineering and real-world simulation environments. By identifying the gaps in these current methodologies, the paper proposes a hybrid, multi-layered evaluation framework designed to address the limitations of isolated metrics and offer a more holistic view of LLM behavior in both controlled and dynamic settings. To validate the proposed framework, three widely-used LLMs—GPT-4, Claude 2, and LLaMA 2—were subjected to a series of comparative experiments. Quantitative and qualitative results were obtained across a range of benchmark tasks, ethical risk scenarios, and performance stress tests. The findings are presented using structured tables and visual graphs that demonstrate key trade-offs between accuracy, inference time, toxicity levels, and model robustness. Ultimately, this paper provides a reproducible and scalable blueprint for evaluating LLMs that not only informs model developers and researchers but also aids policymakers, ethicists, and organizations seeking to deploy these models responsibly. The framework's layered architecture offers flexibility for continuous evaluation, ensuring it can adapt to the rapidly evolving landscape of generative AI.
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Niarman, Abdurrahman, Iswandi, and Argi Kartika Candri. "Comparative Analysis of PHP Frameworks for Development of Academic Information System Using Load and Stress Testing." International Journal Software Engineering and Computer Science (IJSECS) 3, no. 3 (2023): 424–36. http://dx.doi.org/10.35870/ijsecs.v3i3.1850.
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There are many programming languages available for the developers to pick when they want to make a web services project such as Java JSP, Python, ASP.Net, PHP and many others. The reason that writer chose PHP as its research topic is that PHP is still being one of the most promising languages especially for developing web services. Several PHP Frameworks are now available on the internet promising that their framework can do better than others. Some popular PHP frameworks are Laravel, Symfony, CakePHP, Yii, and CodeIgniter. Performance is the most aspect to be concerned because of the market’s demands entailing them to do so. The next concern that developer would likely need to decide is whether to go with Pure PHP or to go with PHP Framework. To answer those concerns, this research has been conducted in which a module is taken from an academic information system and will be developed into three similar and equivalent web applications by using Laravel, CodeIgniter, and Pure PHP. The author's aim in conducting this research is to obtain more in-depth information regarding the use of the pure PHP programming language and several frameworks such as CodeIgniter and Laravel. There are many statements stating that using the PHP programming language is no longer feasible, even though in reality using PHP for developing web-based applications is still the choice of many programmers based on statistics from w3tech. The results of research conducted by the author show that the PHP programming language is still very reliable in handling load and stress tests. The pure PHP programming language provides slightly better performance results than the CodeIgniter and Laravel frameworks. Hence, the use of pure PHP or frameworks can be determined from the level of needs of the application development to be created.
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Das, Sanjay Kumar. "Modernizing QA Frameworks for Omni-Based Retirement Systems: A Shift from Manual Mainframe Testing to Intelligent Automation." International Interdisciplinary Business Economics Advancement Journal 06, no. 05 (2025): 68–89. https://doi.org/10.55640/business/volume06issue05-04.
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Quality Assurance (QA) in the retirement services industry is undergoing a paradigm shift as firms modernize legacy Omni-based recordkeeping systems. This paper explores the transition from manual mainframe testing to intelligent automation for Omni-based retirement platforms. We discuss the challenges posed by legacy mainframe environments and the strategies to modernize QA using tools like IBM Personal Communications (PCOMM) for terminal automation, Job Control Language (JCL) for batch processing, and OmniScript for custom business logic. Emphasis is placed on maintaining compliance with stringent retirement regulations and ensuring data accuracy and system performance. We present case studies of organizations that have successfully migrated from labor-intensive, error-prone QA processes to robust automated frameworks. Diagrams and figures illustrate the legacy vs. modern architecture and quantify improvements such as reduced testing cycle time and increased coverage. The results demonstrate that intelligent automation in Omni-based systems not only accelerates testing and enhances quality but also ensures greater reliability and compliance in a highly regulated domain. The findings aim to guide retirement services providers in upgrading their QA practices for better efficiency, accuracy, and risk management.
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Baccolini, Valentina, Giuseppe Migliara, Antonio Sciurti, et al. "PD150 How Is Genetic Testing Evaluated? An Updated Systematic Review Of Assessment Frameworks." International Journal of Technology Assessment in Health Care 40, S1 (2024): S151. https://doi.org/10.1017/s0266462324003830.
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IntroductionAssessment of the risks and benefits of genetic and genomic tests has long been addressed using ad hoc evaluation methods. They are mostly ACCE-based, focus on technical aspects, and often overlook economic and organizational considerations. The few health technology assessment (HTA) based approaches, though more comprehensive, lack validation and implementation. This review’s purpose was to identify evaluation frameworks for genetic and genomic tests and to synthesize their key aspects.MethodsPubMed, Scopus, Web of Science, Google Scholar, and Google Search were used to identify records describing any assessment framework for genetic or genomic tests. As this was an update of a previous systematic review, the search was restricted to records published from 1 October 2020. Inclusion criteria were documents describing evaluation frameworks for genetic or genomic tests that were original, specifically created, and covered at least three evaluation components (analytic validity, clinical validity, clinical utility, economic aspects, or ethical, legal, and social implications). This study was supported by the European Commission and the Ministry for Universities and Research under the National Recovery and Resilience Plan (M4C2-I1.3 Project PE_00000019 “HEAL ITALIA”).ResultsOverall, 22,862 records were retrieved and 12,546 unique records were screened, of which 67 documents were assessed for eligibility. However, none of these met the inclusion criteria and no additional framework was found. In contrast, a total of 37 studies reporting 30 different frameworks were included from the previous systematic review. The analysis of these frameworks revealed that they were published between 2000 and 2019 and were mostly based on the ACCE model (n=13), on the HTA process (n=6), or both (n=3). Others referred to the Wilson and Jungner screening criteria (n=3) or to a mixture of different criteria (n=5).ConclusionsA pressing need exists for a universally accepted evaluation framework for genetic and genomic tests. A shift from ad hoc assessments to a general HTA methodology, potentially based on the EUnetHTA Core Model®, is needed. By integrating solid theoretical and methodological principles, a validated, comprehensive, and widely shared tool for evaluating genetic tests can be realized, promoting consistency across Europe and beyond.