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Journal articles on the topic 'Testing'

Author: Grafiati

Published: 4 June 2021

Last updated: 9 June 2025

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1

Praveen, Kumar Koppanati. "Parallelizing Automated UI and API Tests for Java Applications." Journal of Scientific and Engineering Research 10, no. 3 (March 31, 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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Seth, Jyotsna, Mukul Varshney, and Shivani Garg Abha Kiran Rajpoot. "Automated Testing: An Edge Over Manual Software Testing." International Journal of Trend in Scientific Research and Development Volume-1, Issue-4 (June 30, 2017): 710–13. http://dx.doi.org/10.31142/ijtsrd2232.

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Brower, Vicki. "Testing, testing … testing?" Nature Medicine 3, no. 2 (February 1997): 131–32. http://dx.doi.org/10.1038/nm0297-131.

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4

Putterman, Chaim, and Eldad Ben-Chetrit. "Testing, Testing, Testing . . ." New England Journal of Medicine 333, no. 18 (November 2, 1995): 1208–11. http://dx.doi.org/10.1056/nejm199511023331809.

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5

Petro, Jane A. "Testing, Testing, Testing." American Journal of Cosmetic Surgery 32, no. 2 (June 2015): 43–46. http://dx.doi.org/10.1177/074880681503200201.

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Petro, Jane A. "Testing, Testing, Testing." American Journal of Cosmetic Surgery 32, no. 2 (June 2015): 43–46. http://dx.doi.org/10.5992/0748-8068-32.2.43.

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7

Rogers, Tim B. "Testing Testing Testing..." Theory & Psychology 4, no. 2 (May 1994): 300–302. http://dx.doi.org/10.1177/0959354394042016.

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8

Chandrasekhar, K. "Testing Web Application using Selenium Testing Tool with Respect to Test’ng." International Journal for Research in Applied Science and Engineering Technology 6, no. 4 (April 30, 2018): 4766–70. http://dx.doi.org/10.22214/ijraset.2018.4781.

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9

Bashir, Josefeena. "Hypothesis Testing." Scientific Journal of India 3, no. 1 (December 31, 2018): 62–63. http://dx.doi.org/10.21276/24565644/2018.v3.i1.21.

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10

Gallagher, C. "'Testing, testing' [product testing]." Manufacturing Engineer 81, no. 6 (December 1, 2002): 249–52. http://dx.doi.org/10.1049/me:20020601.

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11

Nejad, Ali Mansouri, Farhad Pakdel, and Ali Akbar Khansir. "Interaction between Language Testing Research and Classroom Testing Practice." Educational Process: International Journal 8, no. 1 (January 15, 2019): 59–71. http://dx.doi.org/10.22521/edupij.2019.81.4.

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12

SARI, Halil İbrahim. "Testing Multistage Testing Configurations: Post-Hoc vs. Hybrid Simulations." International Journal of Psychology and Educational Studies 7, no. 1 (January 30, 2020): 27–37. http://dx.doi.org/10.17220/ijpes.2020.01.003.

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esl, vil. "Test environment test two." Journal of Test Deposits 42, no. 119 (May 8, 2011): 126. http://dx.doi.org/10.5555/testing-test-environment.

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14

Advaith, Aditya Chevuturu, Pratap Mathur Divyendra, Joseph Prasanth Kumar Reddy Byreddy, and Charanya R. Dr. "A Comparative Survey on Software Testing Tools." International Journal of Engineering and Advanced Technology (IJEAT) 11, no. 6 (August 30, 2022): 32–40. https://doi.org/10.35940/ijeat.F3664.0811622.

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<strong>Abstract: </strong>Testing the software is an important part of the Software Development Life Cycle. In present day, the software industry’s focus is on developing quality applications. In order to save time and costs when evaluating a program, most testers have moved from manual testing to automated testing. A large variety of software testing tools, open-source as well as commercial, are available in the market. It is quite a challenging task to select a testing tool that fits best to their software, as the choices keep getting wider. With more choices comes also the increased spectrum of software testing tool features with cost variations. Web application tools help the developers to test their software quite comfortably and are widely used today. With the integration of testing tools and web browsers, testing has become modular. When choosing an appropriate software testing tool, there are many factors which come into play to make this decision apt for a particular software to be tested. Testing tools are either automated or manual. The tool selection is done on parameters which best suit the tester. The purpose of this study is to identify and compare the popular testing tools and provide a review based on parameters which are suitable. This paper provides a comparative review of features of open source and commercial testing tools in a tabular format, based on these different parameters. It also lists down descriptions and features of various testing tools so that users and developers can opt for the appropriate tools based on their demands and requirements.

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15

Kaur, Kamaldeep, Sunil Khatri, Alok Mishra, and Rattan Datta. "Statistical Usage Testing at Different Levels of Testing." JUCS - Journal of Universal Computer Science 24, no. (12) (December 28, 2018): 1800–1820. https://doi.org/10.3217/jucs-024-12-1800.

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Statistical Usage Testing (SUT) is the testing technique defined in Cleanroom Software Engineering model [Runeson, 93]. Cleanroom Software Engineering model is a theory based and team oriented model that is based on development and certification of software in increments using statistical quality control [Linger 96]. SUT is a black box testing technique and concentrates on how the software completes its required function from the user's perspective [Runeson, 93]. SUT is carried out by developing usage models and assigning usage probabilities. Testing is carried out on usage models by performing statistical tests which are random sequences [Trammel 95]. Statistical testing can be viewed as a statistical experiment where random test cases are selected from all the usage models [Trammel 95]. This paper demonstrates the process and benefits of applying SUT at different levels of testing. Levels of testing include Unit level, Integration level, System level and Acceptance level. SUT is generally performed at System level and Unit testing is not the part of SUT. Unit testing makes it easier to access code and debug human errors. Detecting errors at an early stage helps reducing cost and effort. The paper proposes to allow Unit testing in Cleanroom Software Engineering Model, thus making it more flexible and suitable for varied applications. Unit testing is essentially performed to ensure that the code is working correctly and meets the user specifications [istqb, 15]. Errors may also exist when modules are integrated because of interchange of data and control information between various modules. Integration testing is performed when the modules are combined together to check their behaviour and functionality after integration. Once the Integration testing phase gets successfully completed, System testing is performed on the whole system [test-institute, 15]. The paper makes use of Student record software to demonstrate the process of performing SUT at different levels. In addition to performing SUT at System level, this paper helps in understanding the advantages of applying SUT at Unit level and Integration level.

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16

Beardsley, Tim. "Testing, Testing." Scientific American 274, no. 6 (June 1996): 38–39. http://dx.doi.org/10.1038/scientificamerican0696-38.

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17

Pitts, Stephanie E. "‘Testing, testing...’." Active Learning in Higher Education 6, no. 3 (November 2005): 218–29. http://dx.doi.org/10.1177/1469787405057663.

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18

Hindmarch, Sonali. "Testing, testing." 5 to 7 Educator 2008, no. 46 (October 2008): 5. http://dx.doi.org/10.12968/ftse.2008.7.10.30982.

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19

Brey, Robin L. "Testing, Testing." Neurology Now 4, no. 6 (November 2008): 7. http://dx.doi.org/10.1097/01.nnn.0000343170.45828.28.

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20

Moore, John W. "Testing, Testing." Journal of Chemical Education 78, no. 7 (July 2001): 855. http://dx.doi.org/10.1021/ed078p855.

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21

Emmanuel, Anton V. "Testing, testing." Frontline Gastroenterology 9, no. 2 (March 8, 2018): 85. http://dx.doi.org/10.1136/flgastro-2018-100978.

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22

Buchanan, Mark. "Testing, testing." Nature Physics 8, no. 5 (May 2012): 355. http://dx.doi.org/10.1038/nphys2305.

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23

Yngve, Agneta. "Testing, testing." Public Health Nutrition 10, no. 9 (September 2007): 864. http://dx.doi.org/10.1017/s1368980007797215.

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24

Stevenson, Douglas K. "Testing, testing." System 14, no. 1 (January 1986): 85–93. http://dx.doi.org/10.1016/0346-251x(86)90053-9.

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25

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 (August 1, 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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26

Paul Singh Sahni, Bhupinder. "Software Testing Techniques." International Journal of Science and Research (IJSR) 9, no. 7 (July 5, 2020): 2014–17. http://dx.doi.org/10.21275/sr24628184637.

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27

Hu, Shueh-Cheng, and I.-Ching Chen. "A Software Testing Service Supporting Long-Lived and Asynchronous Testing Jobs." Lecture Notes on Software Engineering 2, no. 4 (2014): 314–19. http://dx.doi.org/10.7763/lnse.2014.v2.142.

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28

Helexa, Milan, Ján Kováč, and Jozef Krilek. "Testing tyres of mobile forest machines in the soil testing canal." Research in Agricultural Engineering 67, No. 4 (December 17, 2021): 190–98. http://dx.doi.org/10.17221/76/2020-rae.

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The article focuses on the research of tyre rolling resistances in the soil test channel environment. The specific monitored tyre was a Mitas TS05 10.0/75-15.3 10PR diagonal tyre with an arrow tread. The measurement itself was divided into two stages. In the first stage, measurements of rolling resistance were performed on a solid concrete base of the laboratory in order to determine the internal component of rolling resistance of the tyre. In the second stage, rolling resistances were monitored on forest soil deposited in the main body of the soil channel. The mentioned measurements of rolling resistance can be considered key for further evaluation of traction and energy properties of tyres. Despite some complications which occurred during the measurement, the results obtained indicate the conclusions reached by other researchers in the field. The main conclusion of this research is to confirm the justification of using the correct or optimal level of inflation pressures of tyres of mobile energy means depending on the properties of the surfaces on which they move in order to reduce not only their energy intensity but also greater environmental acceptability.

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29

Afrin, Arashiya, and Kamar Mohsin. "Testing approach: Manual testing vs automation testing." Global Sci-Tech 9, no. 1 (2017): 55. http://dx.doi.org/10.5958/2455-7110.2017.00008.8.

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30

Doddington, Christine, Eve Bearne, Helen Demetriou, and Julia Flutter. "‘Testing, testing, testing… can you hear me?’." Education 3-13 29, no. 3 (October 2001): 43–46. http://dx.doi.org/10.1080/03004270185200361.

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31

Yakoob, Rahila, and Gopalkrishna Bhat K. "Comparision of Direct Antibiotic Susceptibility Testing with Standard Testing in Blood Culture." Journal of Pure and Applied Microbiology 12, no. 4 (December 30, 2018): 2289–96. http://dx.doi.org/10.22207/jpam.12.4.70.

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32

Mensah, Yaw Agyei, Abigail Ajoke Ogunlolu, and Yaw Asa Mensah. "Hybrid software testing model to improve software quality assurance." Global Journal of Engineering and Technology Advances 17, no. 1 (October 30, 2023): 104–16. https://doi.org/10.5281/zenodo.10674893.

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Software testing is a very critical factor in determining the quality, robustness and reliability of applications. Testing methods have advanced to accommodate the various software development practices that are being churned out at frequent rates and representing complex systems. One such method is the hybrid software testing model, which combines the strengths of different testing techniques to achieve comprehensive testing coverage. This study provides an in-depth analysis of the hybrid software testing model, exploring its definition, benefits, challenges, and best practices. Furthermore, it discusses various testing techniques commonly used in hybrid testing and presents case studies showcasing the successful implementation of the hybrid model in real-world scenarios.

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33

Falah, Bouchaib, and Souhail Marghabi. "Towards Regression Testing Constraints." International Journal of Modeling and Optimization 4, no. 6 (December 2014): 504–9. http://dx.doi.org/10.7763/ijmo.2014.v4.425.

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34

Tiwari, Vijay Kumar. "Oracle Database Backup Testing." International Journal of Trend in Scientific Research and Development Volume-2, Issue-3 (April 30, 2018): 2043–44. http://dx.doi.org/10.31142/ijtsrd11572.

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35

U Kerkar, Sairaj, Jyothi Warrier, and U. R Bagal. "Swab Testing Robotic Arm." International Journal of Science and Research (IJSR) 11, no. 7 (July 5, 2022): 1297–301. http://dx.doi.org/10.21275/sr22718163040.

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36

Genov, Borislav. "Justification of nondestructive testing." Journal scientific and applied research 1, no. 1 (April 4, 2012): 76–86. http://dx.doi.org/10.46687/jsar.v1i1.22.

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Progress in technology has enabled improvement in performance of materials and processes. These advancements lead to reduction in size and weight of engineering structures. But these structures become more sophisticated and expensive,and these lead to introduce quantitative nondestructive measures to ensure quality throughout all production process. This is particularly true for these applications, where the cost of the failure of a component can be unavoidable high compared to the cost of preventive measures, or the failure may cause catastrophic consequences. The following paper reviews present philosophy and justification of use of nondestructive testing (NDT).

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37

Schneider, Carl E. "At Law: Testing Testing." Hastings Center Report 27, no. 4 (July 1997): 22. http://dx.doi.org/10.2307/3528775.

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38

Pray, Toni. "Testing... Testing... for Fran." English Journal 77, no. 4 (April 1988): 86. http://dx.doi.org/10.2307/819317.

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39

Thomas, Alex. "Testing, Testing, 1, 2." Contemporary Psychology: A Journal of Reviews 38, no. 12 (December 1993): 1304–6. http://dx.doi.org/10.1037/032864.

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40

Neubrand, Tobias. "Non-Destructive Testing Testing." Consumer Electronics Test & Development 2021, no. 2 (January 2022): 44–45. http://dx.doi.org/10.12968/s2754-7744(23)70078-x.

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41

Hareesh, Kumar Rapolu. "Automated Testing in Java-Comparative Analysis of Automated Testing Tools." INTERNATIONAL JOURNAL OF INNOVATIVE RESEARCH AND CREATIVE TECHNOLOGY 7, no. 6 (November 5, 2021): 1–5. https://doi.org/10.5281/zenodo.14883117.

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The following research project has signified with a detailed analysis of several automated testing tools which are being constructed specifically for Java applications. It has risen with the rising complexity of software systems in which effective testing has been considered for determining quality and reliability. Moreover, the combination of testing tools such as TestNG and JUnit has paved the path for supporting the community. Furthermore, the utilisation of valid recommendations such as TestNG for integration testing and Selenium for UI testing has proved to be suitable for specific testing needs. Therefore, this has advantaged the developers and the users to choose the most appropriate testing tools.

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42

Sarika, Rane, Potdar Varad, Trivedi Harsh, and Ughade Yash. "Designing White Box Test Cases for Online Food Delivery System." Journal of Advancement in Software Engineering and Testing 4, no. 3 (February 18, 2022): 1–4. https://doi.org/10.5281/zenodo.6134394.

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<em>Let’s say, you are given a completely wrapped gift package and given the task of observing and noting all of the flaws you can uncover without opening the wrapper. You won't be able to see what's inside a Black Box, just as you won't be able to see what's within an object. White box testing is a software analysis approach that involves analysing a product's fundamental structure, architecture, and code in order to ensure input-output flow and enhance design, usability, and security. It's one of two parts of the software testing technique known as Box Testing. Test coverage data is used to identify appropriate test cases, hence improving the quality of testing and conserving testing resources. A set of test cases is generated as a result. Selenium is a web application testing tool that automates tests across browsers. It's used to guarantee that web apps are of good quality, whether they're responsive, progressive, or standard. The test Executor application processes the generated test cases and determines if the results passed or failed based on the outcomes of image grabbing, OCR text extraction, and comparison with expected text.</em>

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43

ROTHMAN, ARTHUR I. "Confidence Testing: an Extension of Multiple-choice Testing1." Medical Education 3, no. 3 (January 29, 2009): 237–39. http://dx.doi.org/10.1111/j.1365-2923.1969.tb02089.x.

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44

Samir, Amira, Maghawry Huda Amin, and Nagwa Badr. "An Enhanced Testing Approach for Mobile Applications." JUCS - Journal of Universal Computer Science 29, no. (2) (February 28, 2023): 152–78. https://doi.org/10.3897/jucs.86295.

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Nowadays, there is an enormous number of mobile applications that are continuously being launched to the market. As a result of this rapid process, there is a need to increase the speed of testing process using enhanced approaches. This research aims to increase the effectiveness of the graphical user interface testing process of mobile applications. This is achieved by proposing an enhanced combinatorial-based metaheuristic approach. The proposed approach aims to maximize statement and branch coverage by applying Cuckoo search, for event selection. The approach was compared to monkey, frequency, random and greedy approaches. Experiments were conducted on different mobile applications. During the same testing time duration, the proposed approach achieved higher coverage than the other approaches. The proposed approach proved its effectiveness in mobile application testing compared to the other approaches.

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45

Kusum, Talwar Pritika, Puri Amit, and Kumar Guneet. "Overview of software testing." Global Journal of Engineering and Technology Advances 19, no. 1 (April 30, 2024): 104–12. https://doi.org/10.5281/zenodo.13690783.

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Software testing is a task conducted to assess the quality of software and enhance its performance. This process ensures that the software behaves as expected according to user requirements. The software development life cycle (SDLC) outlines various stages such as Analysis, Requirements, Design, Development, Testing, Deployment, and Maintenance to guide the software development process. The primary objective of SDLC is to deliver error-free software that meets user expectations within specified timeframes. Software testing is an integral part of SDLC, serving to identify issues and ensure the completeness, correctness, and quality of the developed software. The ultimate goal is to create efficient software and maintain high-quality assurance throughout the product's lifecycle. This review paper aims to provide a brief discussion on how the software development life cycle contributes to efficient software development and how the software testing life cycle process ensures better quality assurance for the product.

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46

Morgan, L. "Testing defects in automated ultrasonic testing and radiographic testing." Insight - Non-Destructive Testing and Condition Monitoring 60, no. 11 (November 1, 2018): 606–12. http://dx.doi.org/10.1784/insi.2018.60.11.606.

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47

Cody, Hanson, and R. Walcott Kristen. "NETCDL : THE NETWORK CERTIFICATION DESCRIPTION LANGUAGE." International Journal of Computational Science, Information Technology and Control Engineering (IJCSITCE) 5, no. 3 (August 6, 2019): 1–20. https://doi.org/10.5281/zenodo.3361024.

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Modern IP networks are complex entities that require constant maintenance and care. Similarly, constructing a new network comes with a high amount of upfront cost, planning, and risk. Unlike the disciplines of software and hardware engineering, networking and IT professionals lack an expressive and useful certification language that they can use to verify that their work is correct. When installing and maintaining networks without a standard for describing their behavior, teams find themselves prone to making configuration mistakes. These mistakes can have real monetary and operational efficiency costs for organizations that maintain large networks. In this research, the Network Certification Description Language (NETCDL) is proposed as an easily human readable and writeable language that is used to describe network components and their desired behavior. The complexity of the grammar is shown to rank in the top 5 out of 31 traditional computer language grammars, as measured by metrics suite. The language is also shown to be able to express the majority of common use cases in network troubleshooting. A workflow involving a certifier tool is proposed that uses NETCDL to verify network correctness, and a reference certifier design is presented to guide and standardize future implementations.

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48

D. A., Oke,, Oladiran, G. F, and Raheem, S. B. "Correlation between Destructive Compressive Testing (DT) and Non Destructive Testing (NDT) for Concrete Strength." International Journal of Engineering Research and Science 3, no. 5 (May 31, 2017): 27–30. http://dx.doi.org/10.25125/engineering-journal-ijoer-may-2017-12.

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49

Pedersen, Jean, and Peter Ross. "Testing Understanding and Understanding Testing." College Mathematics Journal 16, no. 3 (June 1985): 178. http://dx.doi.org/10.2307/2686568.

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50

Noijons, José. "Testing Computer Assisted Language Testing." CALICO Journal 12, no. 1 (January 14, 2013): 37–58. http://dx.doi.org/10.1558/cj.v12i1.37-58.

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Much computer assisted language learning (CALL) material that includes tests and exercises looks attractive enough but is clearly lacking in terms of validation: the possibilities of the computer and the inventiveness of the programmers mainly determine the format of tests and exercises, causing possible harm to a fair assessment of pupils' language abilities. This article begins with a definition of computer assisted language testing (CALT), followed by a discussion of the various processes involved. E3oth advantages and disadvantages of CALT are outlined. Psychometric aspects of computer adaptive testing are then discussed. Issues of validity and reliability in CALT are acknowledged. A table of factors in CALT distinguishes between test content and the mechanics of taking a test, before, during and after a test. The various factors are examined and comprise a table for developing a CALT checklist. The article ends with a call for professional testers and developers of educational software to work together in developing CALT.

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