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Journal articles on the topic 'Data-driven test case design'

Author: Grafiati

Published: 23 June 2021

Last updated: 29 July 2025

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1

Prakash Shrivastava, Divya. "Unit Test Case Design Metrics in Test Driven Development." International Journal of Software Engineering 2, no. 3 (2012): 43–48. http://dx.doi.org/10.5923/j.se.20120203.01.

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Zhao, Jian Ping, Xiao Yang Liu, Hong Ming Xi, Li Ya Xu, Jian Hui Zhao, and Huan Ming Liu. "A Lightweight-Leveled Software Automated Test Framework." Advanced Materials Research 834-836 (October 2013): 1919–24. http://dx.doi.org/10.4028/www.scientific.net/amr.834-836.1919.

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To resolve the problem of a large amount of automated test scripts and test data files, through the test tool QTP, data-driven and keyword-driven testing mechanism, a test automation framework based on three layer data-driven mechanism is designed, including the design of the TestSet managing test case files, the design of the TestCase storing test cases and the design of the TestData storing test data.Through controlling the test scale and applying the test data pool, reconfigurable and optimization of test scripts are designed. The methods above can decouple the test design and the script de

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Doddapaneni, Jagan Mohan Rao. "AI Test Design and Script Generator: Enhancing Software Testing through AI-driven Automation." International Journal of Multidisciplinary Research and Growth Evaluation 6, no. 1 (2025): 1942–43. https://doi.org/10.54660/.ijmrge.2025.6.1.1942-1943.

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The evolution of software testing has led to the adoption of AI-driven tools to optimize the efficiency, accuracy, and coverage of test case generation. This paper introduces an AI Test Design and Script Generator, a cutting-edge solution that automates requirement and document reviews, enhances test coverage through generative AI, and ensures secure segmentation of customers, organizations, and departments. Unlike traditional automation tools, this AI-driven approach integrates with private Large Language Models (LLMs), providing intelligent test generation without collecting personal or sens

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Aulich, Marcel, Georgios Goinis, and Christian Voß. "Data-Driven AI Model for Turbomachinery Compressor Aerodynamics Enabling Rapid Approximation of 3D Flow Solutions." Aerospace 11, no. 9 (2024): 723. http://dx.doi.org/10.3390/aerospace11090723.

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The development of new turbomachinery designs requires numerous time-consuming and computationally intensive computational fluid dynamics (CFD) calculations. However, most of the generated high spatial resolution data remain unused at later development steps. That is also the case with automated optimization processes that use only a few integral values to determine objectives and constraints. To make further use of this vast amount of CFD data a data-driven AI model based on the Transformer architecture is developed and trained using the available CFD data. The presented method subsequently p

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Pandhare, Harshad Vijay. "From Test Case Design to Test Data Generation: How AI is Redefining QA Processes." International Journal of Engineering and Computer Science 13, no. 12 (2024): 26737–57. https://doi.org/10.18535/ijecs.v13i12.4956.

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The accelerating pace of software development, fueled by agile methodologies and continuous integration practices, has exposed the limitations of traditional Quality Assurance (QA) techniques. Manual test case design and static test data provisioning are no longer sufficient to meet the demands of modern software systems that require high reliability, rapid releases, and robust performance under varied conditions. This paper explores how Artificial Intelligence (AI) is fundamentally transforming QA workflows—particularly in the realms of test case design and test data generation. It examines t

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Hanhela, Matti, Olli Gröhn, Mikko Kettunen, Kati Niinimäki, Marko Vauhkonen, and Ville Kolehmainen. "Data-Driven Regularization Parameter Selection in Dynamic MRI." Journal of Imaging 7, no. 2 (2021): 38. http://dx.doi.org/10.3390/jimaging7020038.

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In dynamic MRI, sufficient temporal resolution can often only be obtained using imaging protocols which produce undersampled data for each image in the time series. This has led to the popularity of compressed sensing (CS) based reconstructions. One problem in CS approaches is determining the regularization parameters, which control the balance between data fidelity and regularization. We propose a data-driven approach for the total variation regularization parameter selection, where reconstructions yield expected sparsity levels in the regularization domains. The expected sparsity levels are

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Lyu, Zhi-Jun, Qi Lu, YiMing Song, Qian Xiang, and Guanghui Yang. "Data-Driven Decision-Making in the Design Optimization of Thin-Walled Steel Perforated Sections: A Case Study." Advances in Civil Engineering 2018 (2018): 1–14. http://dx.doi.org/10.1155/2018/6326049.

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The rack columns have so distinctive characteristics in their design, which have regular perforations to facilitate installation of the rack system that it is more difficult to be analyzed with traditional cold-formed steel structures design theory or standards. The emergence of industrial “big-data” has created better innovative thinking for those working in various fields including science, engineering, and business. The main contribution of this paper lies in that, with engineering data from finite element simulation and physical test, a novel data-driven model (DDM) using artificial neural

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Robertson, P. K., R. G. Campanella, P. T. Brown, I. Grof, and J. M. O. Hughes. "Design of axially and laterally loaded piles using in situ tests: A case history." Canadian Geotechnical Journal 22, no. 4 (1985): 518–27. http://dx.doi.org/10.1139/t85-072.

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A 915 mm diameter steel pipe pile was driven and tested by the B.C. Ministry of Transportation and Highways as part of their foundation studies for the proposed Annacis channel crossing of the Fraser River. The pile was driven open ended to a maximum depth of 94 m. The pile was tested axially to failure when the pile tip was at depths of 67, 78, and 94 m below ground surface. Following the final axial load test, the pile was loaded laterally to a total deflection at the ground surface of 150 mm. A slope indicator casing was installed in the pile to monitor the deflected shape during lateral lo

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SADEGHI, ALIREZA, and SEYED-HASSAN MIRIAN-HOSSEINABADI. "MBTDD: MODEL BASED TEST DRIVEN DEVELOPMENT." International Journal of Software Engineering and Knowledge Engineering 22, no. 08 (2012): 1085–102. http://dx.doi.org/10.1142/s0218194012500295.

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Test Driven Development (TDD), as a quality promotion approach, suffers from some shortages that discourage its usage. One of the most challenging shortcomings of TDD is the low level of granularity and abstraction. This may lead to production of software that is not acceptable by the end users. Additionally, exploiting of TDD is not applicable in the enterprise systems development. To overcome this defect, we have merged TDD with Model Based Testing (MBT) and suggested a framework named Model Based Test Driven Development (MBTDD). According to TDD, writing test cases comes before programming,

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Lerro, Angelo, Alberto Brandl, Manuela Battipede, and Piero Gili. "A Data-Driven Approach to Identify Flight Test Data Suitable to Design Angle of Attack Synthetic Sensor for Flight Control Systems." Aerospace 7, no. 5 (2020): 63. http://dx.doi.org/10.3390/aerospace7050063.

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Digital avionic solutions enable advanced flight control systems to be available also on smaller aircraft. One of the safety-critical segments is the air data system. Innovative architectures allow the use of synthetic sensors that can introduce significant technological and safety advances. The application to aerodynamic angles seems the most promising towards certified applications. In this area, the best procedures concerning the design of synthetic sensors are still an open question within the field. An example is given by the MIDAS project funded in the frame of Clean Sky 2. This paper pr

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Lerro, Angelo, Alberto Brandl, Manuela Battipede, and Piero Gili. "A Data-Driven Approach to Identify Flight Test Data Suitable to Design Angle of Attack Synthetic Sensor for Flight Control Systems." Sensors 7, no. 5 (2020): 63. https://doi.org/10.3390/aerospace7050063.

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Digital avionic solutions enable advanced flight control systems to be available also on smaller aircraft. One of the safety-critical segments is the air data system. Innovative architectures allow the use of synthetic sensors that can introduce significant technological and safety advances. The application to aerodynamic angles seems the most promising towards certified applications. In this area, the best procedures concerning the design of synthetic sensors are still an open question within the field. An example is given by the MIDAS project funded in the frame of Clean Sky 2. This paper pr

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CHO, YONGSUN, WOOJIN LEE, and KIWON CHONG. "THE TECHNIQUE OF BUSINESS MODEL DRIVEN ANALYSIS AND TEST DESIGN FOR DEVELOPMENT OF WEB APPLICATIONS." International Journal of Software Engineering and Knowledge Engineering 15, no. 04 (2005): 587–605. http://dx.doi.org/10.1142/s0218194005002452.

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A technique for creating analysis models of a web application from a business model is proposed for easy and effective development. Moreover, a technique for generating test cases from the sequence diagrams for a web application is proposed. The use case diagram and web page list are generated from the business model which is depicted using the notations of the UML (Unified Modeling Language) activity diagram. The page diagram and logical/physical database models are created based on the web page list and extracted data fields. Test cases for the web application are generated from call message

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Siva Sai Kumar Yachamaneni. "AI-driven test automation: revolutionizing enterprise integration." Global Journal of Engineering and Technology Advances 23, no. 1 (2025): 437–44. https://doi.org/10.30574/gjeta.2025.23.1.0133.

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This article examines how AI-driven test automation is transforming enterprise integration testing by addressing the limitations of traditional testing approaches. As modern organizations increasingly rely on seamless integration between diverse applications and systems, conventional testing methods struggle with maintenance burdens, limited test coverage, and inefficient execution. It explores how artificial intelligence introduces intelligence and adaptability throughout the testing lifecycle, from test design to execution and analysis. The article analyzes five core components of AI-driven

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Xu, Xiaoyu, Hongbo Chen, Chenliang Zhang, Yanhui Duan, and Guangxue Wang. "Data-Driven Sensitivity Analysis of the Influence of Geometric Parameterized Variables on Flow Fields Under Different Design Spaces." Aerospace 11, no. 12 (2024): 984. http://dx.doi.org/10.3390/aerospace11120984.

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In aerodynamic shape optimization, geometric parameterized variables have a significant impact on the flow field, thereby influencing both the effectiveness and efficiency of the optimization process. This paper utilizes flow field data from computational fluid dynamics (CFD) to develop a data-driven approach for analyzing the influence of geometric parameterized variables on the objective function and flow field across various design spaces. A data-driven method, namely a sensitivity analysis based on the Kriging model, is proposed along with three design space variation schemes (scaling, tra

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Hussain, Talha, Rizwan Bin Faiz, Mohammad Aljaidi, et al. "Maximizing Test Coverage for Security Threats Using Optimal Test Data Generation." Applied Sciences 13, no. 14 (2023): 8252. http://dx.doi.org/10.3390/app13148252.

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As time continues to advance, the need for robust security threat mitigation has become increasingly vital in software. It is a constant struggle to maximize test coverage through optimal data generation. We conducted explanatory research to maximize test coverage of security requirements as modeled in the structured misuse case description (SMCD). The acceptance test case is designed through the structured misuse case description for mitigation of security threats. Mal activity is designed from SMCD upon which constraints are specified in object constraint language (OCL) in order to minimize

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Georgiou, Aris, George Haritos, Moyra Fowler, and Yasmin Imani. "Advanced phase powertrain design attribute and technology value mapping." Journal of Engineering, Design and Technology 14, no. 1 (2016): 115–33. http://dx.doi.org/10.1108/jedt-05-2014-0031.

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Purpose – The purpose of this paper is to focus on how the concept design stage of a powertrain system can be improved by using a purely objective driven approach in selecting a final concept design to progress further. This research investigation will examine the development of a novel test-bed to assist in the selection of powertrain technologies during the concept design phase at Ford Motor Company Ltd, serving as the main contribution to knowledge. Design/methodology/approach – The objectives of this research were achieved by carrying out a literature review of external published work rela

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Pahwa, Payal, and Renu Miglani. "Test Case Design using Black Box Testing Techniques for Data Mart." International Journal of Computer Applications 109, no. 3 (2015): 18–22. http://dx.doi.org/10.5120/19169-0636.

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Naddeo, Alessandro, and Nicola Cappetti. "Comfort driven design of innovative products: A personalized mattress case study." Work 68, s1 (2021): S139—S150. http://dx.doi.org/10.3233/wor-208013.

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BACKGROUND: Human-centred design asks for wellbeing and comfort of the customer/worker when interacting with a product. Having a good perception-model and an objective method to evaluate the experienced (dis)comfort by the product user is needed for performing a preventive comfort evaluation as early as possible in the product development plan. The mattress of a bed is a typical product whose relevance in everyday life of people is under-evaluated. Fortunately, this behaviour is quickly changing, and the customer wants to understand the product he/she buys and asks for more comfortable and for

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Bagge-Petersen, Claudia M., Henriette Langstrup, Jakob E. Larsen, and Anne Frølich. "Critical user-configurations in mHealth design: How mHealth-app design practices come to bias design against chronically ill children and young people as mHealth users." DIGITAL HEALTH 8 (January 2022): 205520762211095. http://dx.doi.org/10.1177/20552076221109531.

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Mobile health smartphone applications (mHealth-apps) are increasingly emerging to assist children's and young people's management of chronic conditions. However, difficulties persist in applying design approaches in mHealth projects that return apps that are useful to this group. In this article, we explore ethnographically two self-proclaimed ‘user-driven’ projects designing mHealth apps for Danish patients below the age of 18 living with, respectively, haemophilia and rheumatoid arthritis. These projects initially included the perspectives of children and young people to inform the designs,

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Octavially, Reynaldi Prama, Rosa Reska Riskiana, Kusuma Ayu Laksitowening, Dana Sulistyo Kusumo, Monterico Adrian, and Nungki Selviandro. "Test Case Analysis with Keyword-Driven Testing Approach on Angkasa Website Using Katalon Studio Tools." Ultimatics : Jurnal Teknik Informatika 13, no. 2 (2022): 134–41. http://dx.doi.org/10.31937/ti.v13i2.2391.

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Abstract— Testing a software is an important stage of a series of software development. Functional testing of each feature on the Angkasa website is intended to try out the function to match the required specifications. To achieve a functional test result, there are elements of features on the web page that require keywords. These keywords are used to perform actions or actions in running a web page, these keywords will help in making Test Cases for the testing process. Because it takes the right keywords to test on the web. To overcome this problem, this study analyzes the use of the Keyword

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Badhan, Istiaque Ahmed, Moohtasim Haque Neeroj, and Irfan Chowdhury. "THE EFFECT OF AI-DRIVEN INVENTORY MANAGEMENT SYSTEMS ON HEALTHCARE OUTCOMES AND SUPPLY CHAIN PERFORMANCE: A DATA-DRIVEN ANALYSIS." Frontline Marketing, Management and Economics Journal 4, no. 11 (2024): 15–52. http://dx.doi.org/10.37547/marketing-fmmej-04-11-03.

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There has been much focus toward increasing integration of AI in healthcare generally, with a specific focus on inventory management systems in particular. As more hospitals in the United States public and private side face increasing costs and concerns over cost and length of operation all systems supporting inventory must be made most efficient and AI system offers the US hospitals the opportunity to maintain accurate inventory and hence improve the quality of patient care. But the literature review presents a small number of studies that focus on the effects of these systems as the means to

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Cai, Hui, and Jun Jia. "Using Discrete Event Simulation (DES) To Support Performance-Driven Healthcare Design." HERD: Health Environments Research & Design Journal 12, no. 3 (2018): 89–106. http://dx.doi.org/10.1177/1937586718801910.

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Aim: This article aims to provide a description of fundamental elements of discrete event simulation (DES), the process and the values of applying DES in assisting healthcare design and planning decision-making. More importantly, it explores how new technology such as electronic medical records, real-time location services (RTLS), and other simulation methods such as space syntax analysis (SSA) can facilitate and complement DES. Background: Healthcare administrators increasingly recognize DES as an effective tool for allocating resources and process improvement. However, limited studies have d

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Hossain, Md Jakir, and Mia Naeini. "Multi-Area Distributed State Estimation in Smart Grids Using Data-Driven Kalman Filters." Energies 15, no. 19 (2022): 7105. http://dx.doi.org/10.3390/en15197105.

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Low-latency data processing is essential for wide-area monitoring of smart grids. Distributed and local data processing is a promising approach for enabling low-latency requirements and avoiding the large overhead of transferring large volumes of time-sensitive data to central processing units. State estimation in power systems is one of the key functions in wide-area monitoring, which can greatly benefit from distributed data processing and improve real-time system monitoring. In this paper, data-driven Kalman filters have been used for multi-area distributed state estimation. The presented s

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Wendy Matende, Tichaona Remias, and Shelter Muguti. "Enhancing mathematics achievement in underserved high schools through data-driven instructional strategies: A case study approach." World Journal of Advanced Research and Reviews 27, no. 1 (2025): 1768–77. https://doi.org/10.30574/wjarr.2025.27.1.2648.

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This paper discusses data-driven instructional practices to enhance mathematics performance in disadvantaged high schools. The study employs the mixed-methods case study design to determine how data collection, analysis, and instructional adaptation can help resolve long-standing achievement gaps in resource-scarce educational settings. The research is based on three urban high schools with the majority of students being low-income and historically marginalized. It explores the role of formative assessment, real-time instructional changes, and collaborative teacher practices based on student p

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MEDDERS, STEPHEN C., EDWARD B. ALLEN, and EDWARD A. LUKE. "USING RULE STRUCTURE TO EVALUATE THE COMPLETENESS OF RULE-BASED SYSTEM TESTING: A CASE STUDY." International Journal of Software Engineering and Knowledge Engineering 20, no. 07 (2010): 975–86. http://dx.doi.org/10.1142/s0218194010005006.

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Rule-based systems are typically tested using a set of inputs which will produce known outputs. However, one does not know how thoroughly the software has been exercised. Traditional test-coverage metrics do not account for the dynamic data-driven flow of control in rule-based systems. Our literature review found that there has been little prior work on coverage metrics for rule-based systems. This paper proposes test-coverage metrics for rule-based systems derived from metrics defined by prior work, and presents an industrial scale case study. We conducted a case study to evaluate the practic

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Teguh Prasetyo, Hakam Muzakki, and M Nur Rajab Zainal A. "Design a Data Acquisition System on Deflection Test Equipment." Technium: Romanian Journal of Applied Sciences and Technology 16 (October 29, 2023): 293–98. http://dx.doi.org/10.47577/technium.v16i.10000.

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The purpose of performing a deflection test is to determine the behavior of the material when given load variations. Acquisition data is used to read deflection value. Data acquisition is the process of collecting signals derived from changes in physical behavior, in this case read deflection on material test. The sensor used to read the behavior of the material when subjected to load is strain gauge BF 350 AA sensor. Data is captured in real time. Based on testing using a data acquisition system, deflection data was obtained with the smallest difference being 0.032 mm and the largest differen

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Liu, Zoey, and Emily Prud’hommeaux. "Data-driven Model Generalizability in Crosslinguistic Low-resource Morphological Segmentation." Transactions of the Association for Computational Linguistics 10 (2022): 393–413. http://dx.doi.org/10.1162/tacl_a_00467.

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Abstract Common designs of model evaluation typically focus on monolingual settings, where different models are compared according to their performance on a single data set that is assumed to be representative of all possible data for the task at hand. While this may be reasonable for a large data set, this assumption is difficult to maintain in low-resource scenarios, where artifacts of the data collection can yield data sets that are outliers, potentially making conclusions about model performance coincidental. To address these concerns, we investigate model generalizability in crosslinguist

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Kwak, Kiseok, Kyung Jun Kim, Jungwon Huh, Ju Hyung Lee, and Jae Hyun Park. "Reliability-based calibration of resistance factors for static bearing capacity of driven steel pipe piles." Canadian Geotechnical Journal 47, no. 5 (2010): 528–38. http://dx.doi.org/10.1139/t09-119.

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As part of a study to develop load and resistance factor design (LRFD) codes for foundation structures in South Korea, resistance factors for the static bearing capacity of driven steel pipe piles were calibrated in the framework of the reliability theory. A database of 52 static load test results was compiled, and the data from these load test piles were sorted into two cases: a standard penetration test (SPT) N-value at pile tip (i) less than 50 and (ii) equal to or more than 50. Reliability analyses and resistance factor calibration for the two static bearing capacity analysis methods adopt

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Wang, Shikai, Jingyi Chen, Lei Yan, and Zuwei Shui. "Automated Test Case Generation for Chip Verification Using Deep Reinforcement Learning." Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online) 4, no. 1 (2025): 1–12. https://doi.org/10.60087/jklst.v4.n1.001.

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This paper presents a novel automated test case generation framework leveraging deep reinforcement learning (DRL) for chip verification. The framework addresses the growing complexity in modern chip designs where traditional verification methods must help achieve comprehensive coverage efficiently. Our approach implements a custom deep Q-network architecture optimized for processing coverage feedback and generating test vectors, incorporating an innovative reward mechanism that balances coverage optimization with simulation efficiency. The proposed system features a hierarchical state space re

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Mehdian, Mostafa, Hamid Mirzahossein, and Ali Abdi Kordani. "A Data-Driven Functional Classification of Urban Roadways Based on Geometric Design, Traffic Characteristics, and Land Use Features." Journal of Advanced Transportation 2022 (March 11, 2022): 1–9. http://dx.doi.org/10.1155/2022/9970464.

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The functional classification system (FCS) of roads means categorizing roads based on their service characteristics. The two primary considerations in classifying highway and street networks are accessibility and mobility, where by increasing the role of one, the other’s role is reduced. In this paper, besides the conventional variables such as geometric design characteristics, parking lots, land use features, and accessibility; the Sydney Coordinated Adaptive Traffic System (SCATS) data following the real-time traffic flow and average speed of vehicles collected by Location-Based Services (LB

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Eilouti, Buthayna. "A language-driven reverse-engineering tool for the analysis of architectural precedents: A Palladian case study." Spatium, no. 45 (2021): 21–33. http://dx.doi.org/10.2298/spat2145021e.

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The analysis of precedents represents a significant point of departure for design processing. By applying a language/ design analogy, this research introduces a reverse-engineering tool that helps guide the systematic analysis of architectural precedents. The visual tool consists of four main layers: the morphological, the semantic, the semiotic, and the pragmatic. To test the tool?s applicability, a prominent precedent from the Palladian designs is analyzed as a case study. By developing the tool and demonstrating its applicability for the analysis of the underlying regulatory and formative p

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Taras, Chura, and Zvarych Myroslav. "Intelligent test case generation from textual security requirements in SCRUM: an NLP-driven approach." Advances in Cyber-Physical Systems 10, no. 1 (2025): 95–99. https://doi.org/10.23939/acps2025.01.095.

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This paper presents a method for automatically generating security-oriented test cases from textual requirements in SCRUM environments using Natural Language Processing. The proposed approach has combined transformer-based semantic analysis with behavior-driven development test templates to extract and translate functional, non-functional, and misuse-case security requirements. The solution has been tested on 30 real-world requirements derived from agile software projects. Evaluation results have demonstrated that the system achieved 91% precision, 93% recall, and complete (100%) coverage of i

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Ren, Ye, Honghai Ji, Deli Li, Yongqiang Xie, Shuangshuang Xiong, and Li Wang. "Data-Driven Containment Control for a Class of Nonlinear Multi-Agent Systems: A Model Free Adaptive Control Approach." Applied Sciences 14, no. 13 (2024): 5527. http://dx.doi.org/10.3390/app14135527.

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This paper studies the containment control problem of heterogeneous multi-agent systems (MASs) with multiple leaders. The follower agent dynamics are assumed to be unknown and nonlinear. First, each follower is transformed into an incremental data description based on the dynamic linearization technique. Then, a distributed model-free adaptive containment control law is proposed such that all followers will be driven into the convex hull of the leaders. Furthermore, the algorithm is extended to the time-switching and dynamic leaders case. As a data-driven approach, the proposed controller desi

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Zhang, Hui Nan, Shi Hai Wang, Xiao Xu Diao, and Bin Liu. "Test Case Generating for Integrated Modular Avionics Software Health Monitoring." Applied Mechanics and Materials 494-495 (February 2014): 873–80. http://dx.doi.org/10.4028/www.scientific.net/amm.494-495.873.

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Avionics software is safe-critical embedded system and its architecture is evolving from traditional federated architecture to Integrated Modular Avionics (IMA) to improve resource usability. As an architecture widely employed in the avionics industry, supports partitioning concepts. To insure the development of the avionics software constructed on IMA operating system with high reliability and efficiency Health Monitoring (HM) has been shown to be a key step in reducing the life cycle costs for structural maintenance and inspection. In this paper , we propose a model-driven test methodology u

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Abdurohman, Maman, and Arif Sasongko. "Software for Simplifying Embedded System Design Based on Event-Driven Method." International Journal of Electrical and Computer Engineering (IJECE) 5, no. 3 (2015): 491. http://dx.doi.org/10.11591/ijece.v5i3.pp491-502.

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Complexity of embedded system application increases along with the escalation of market demand. Embedded system design process must be enhanced to face design complexity problem. One of challenges in designing embedded system is speed, accuracy, and flexibility. The design process is usually conducted recursively to fulfill requirement of user and optimization. To solve this problem, it needs a system design that is flexible for adaptation. One of solutions is by optimizing all or some of the design steps. This paper proposes a design framework with an automatic framework code generator with o

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Huynh, Quyet-Thang, Le-Trinh Pham, Nhu-Hang Ha, and Duc-Man Nguyen. "An Effective Approach for Context Driven Testing in Practice — A Case Study." International Journal of Software Engineering and Knowledge Engineering 30, no. 09 (2020): 1245–62. http://dx.doi.org/10.1142/s0218194020500333.

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Software testing is a continuous process during the software development stages to ensure quality software products. Researchers, experts and software engineers keep going on studying new techniques, methods and approaches of testing to accommodate changes in software development because of the flexible requirement along with the changing of technology. So, developers and testers need to have effective methods, tools and approaches to create a high-quality product at an efficient cost. This paper provides an effective approach for context-driven testing (CDT) in an agile software development p

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Su, Shaojuan, Zhe Miao, Yong Zhao, and Nanzhe Song. "Digitally twin driven ship cooling pump fault monitoring system and application case." Brodogradnja 75, no. 4 (2024): 1–17. http://dx.doi.org/10.21278/brod75403.

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The rise of digital twin technology has provided innovative methods for monitoring and optimizing ship cooling pumps. This paper proposes a digital twin-based framework for the status monitoring and visualization of ship cooling pumps. By establishing highly realistic physical and mathematical models and integrating actual operational data, a comprehensive virtual environment was created to simulate the operational status of ship cooling pumps. Using the random forest algorithm for data training and testing, the results showed that the root mean square error for the training set was 0.0037873,

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Shaufiah, Shaufiah. "Pengembangan Rules-Driven Workflow Management System (RDWfMS) dengan Menggunakan Teknik Data Mining untuk Sistem Informasi Research Center." Indonesian Journal on Computing (Indo-JC) 2, no. 1 (2017): 39. http://dx.doi.org/10.21108/indojc.2017.2.1.93.

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<p><em>The tight competition of business and technology today makes the organisation must be able to adapt to changes. The changes could affect not only business process model of the organisation but also their information system, which lead to high cost and time-consuming. Therefore, the design and implementation of an information system should handle with care. Furthermore, the organisation also needs to process data into information and knowledge to support their business. Hence, this research is developed to undertake those problems by developing the information system using hy

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Parente, Jéssica, Tiago Martins, João Bicker, and Penousal Machado. "Designing Dynamic Logotypes to Represent Data." International Journal of Art, Culture and Design Technologies 8, no. 1 (2019): 16–30. http://dx.doi.org/10.4018/ijacdt.2019010102.

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This work explores how data can influence the design of logotypes and how they can convey information. The authors use the University of Coimbra, in Portugal, as a case study to develop data-driven logotypes for its faculties and, subsequently, for its students. The proposed logotypes are influenced by the current number of students in each faculty, the number of male and female students, and the nationality of the students. The resulting logotypes are able to portray the diversity of students in each faculty. The authors also test this design approach in the creation of logotypes for the stud

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Ivanov, Valentin, Klaus Augsburg, Carlos Bernad, et al. "Connected and Shared X-in-the-Loop Technologies for Electric Vehicle Design." World Electric Vehicle Journal 10, no. 4 (2019): 83. http://dx.doi.org/10.3390/wevj10040083.

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The presented paper introduces a new methodology of experimental testing procedures required by the complex systems of electric vehicles (EV). This methodology is based on real-time connection of test setups and platforms, which may be situated in different geographical locations, belong to various cyber-physical domains, and are united in a global X-in-the-loop (XIL) experimental environment. The proposed concept, called XILforEV, allows exploring interdependencies between various physical processes that can be identified or investigated in the process of EV development. The paper discusses t

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Movva, Himadeep. "Automated Testing Using UiPath Test Suite: A Framework for Scalable and Efficient Testing." International Scientific Journal of Engineering and Management 02, no. 06 (2023): 1–8. https://doi.org/10.55041/isjem01208.

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Testing is one of the key components of any software development. RPA, with its advanced features, including those of Artificial Intelligence, can bring state-of-the-art solutions to automate use cases that were never imagined could be automated. This research study, through an in-depth analysis of features of the UiPath Test suite, explores the functionality of automated testing within UiPath and how a robust mechanism of an automated test management system through an efficient testing framework produces an RPA software product that is of robust design and highest quality. This research study

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di Stefano, Andrea Giuseppe, Matteo Ruta, Gabriele Masera, and Simi Hoque. "Leveraging Machine Learning to Forecast Neighborhood Energy Use in Early Design Stages: A Preliminary Application." Buildings 14, no. 12 (2024): 3866. https://doi.org/10.3390/buildings14123866.

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The need for energy efficiency in neighborhood-scale architectural design is driven by environmental imperatives and escalating energy costs. This study identifies three key phases in a design process framework where machine learning can be applied to optimize energy consumption in early design stages. The overall framework integrates machine learning tools into the design workflow, enhancing design exploration from concept level and enabling targeted energy assessments. This paper focuses on the first phase (Phase 1) of the framework, which employs machine learning for building energy forecas

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Ruolin Qi. "AUBIQ: A Generative AI-Powered Framework for Automating Business Intelligence Requirements in Resource-Constrained Enterprises." Frontiers in Business and Finance 2, no. 01 (2025): 66–86. https://doi.org/10.71465/fbf262.

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In today’s ever-changing data-driven environment, obtaining requirements for business intelligence (BI) systems remains a major challenge. This pain point is particularly prominent in small and medium-sized enterprises with limited resources: weak technical teams, high external communication costs and long response cycles make traditional manual specification processes more difficult to maintain. This paper proposes a new AI-driven codeless framework AUBIQ, which uses semantic search and large language models (LLM) to automate and accelerate the specification of BI system requirements. The sys

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Krinitskiy, Mikhail, Marina Aleksandrova, Polina Verezemskaya, et al. "On the Generalization Ability of Data-Driven Models in the Problem of Total Cloud Cover Retrieval." Remote Sensing 13, no. 2 (2021): 326. http://dx.doi.org/10.3390/rs13020326.

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Total Cloud Cover (TCC) retrieval from ground-based optical imagery is a problem that has been tackled by several generations of researchers. The number of human-designed algorithms for the estimation of TCC grows every year. However, there has been no considerable progress in terms of quality, mostly due to the lack of systematic approach to the design of the algorithms, to the assessment of their generalization ability, and to the assessment of the TCC retrieval quality. In this study, we discuss the optimization nature of data-driven schemes for TCC retrieval. In order to compare the algori

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Al-Hasan, Abrar R. "Social Media and Vaccine Intention: The Case of Kuwait." Arab Journal of Administrative Sciences 30, no. 3 (2024): 617–58. http://dx.doi.org/10.34120/ajas.v30i3.261.

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Purpose: The COVID-19 pandemic has underscored our heavy reliance on social media platforms for primary information. Misinformation related to the pandemic has significantly affected behaviors related to vaccine hesitancy and overall business confidence. This study uses the extended Information Motivation Behavior (IMB) model to examine the impact of pandemic-era social media usage on vaccine hesitancy and trust in e-commerce.Study design/methodology/approach: Structural equation modeling is used to assess the extended IMB model. Sample and data: Online survey data from a diverse cross-section

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Koh, Hyeyoung, and Hannah B. Blum. "Shear connector design using data analytics approaches." ce/papers 6, no. 3-4 (2023): 831–35. http://dx.doi.org/10.1002/cepa.2561.

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AbstractThe field of structural engineering can be augmented with advanced data analysis techniques. Structural engineering applications consist of datasets which may include experimental or/and computational data, and can be used to derive design provisions based on the measured data. Cluster analysis is a data exploration technique that involves identifying groups in a dataset and providing relationships between input parameters, which could supplement existing engineering intuition and knowledge. As a test case, this paper reanalyzes the existing test data for shear connectors using a clust

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Yilmaz Çetin, Almıla, and Caglar Ucler. "CUSTOMER-FOCUSED AIRCRAFT SEAT DESIGN: A CASE STUDY WITH AHP-QFD." Aviation 27, no. 4 (2023): 225–33. http://dx.doi.org/10.3846/aviation.2023.20210.

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Aviation is rapidly expanding and recovering from the pandemic impact driven by the experience economy. This is particularly subject to interfaces such as the aircraft seats, which are getting intense attention as a differentiator in the cabin. The focal point of this paper is to assess and convert customer requirements into what must be done for an optimum aircraft seat. To achieve this, a 2-step analytic hierarchy process and quality function deployment (AHP-QFD) methodology was successfully applied, consolidating product quality characteristics. Then, it leverages a novel scoring method of

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Zhou, Qianqian, Shuai Teng, Zuxiang Situ, et al. "A deep-learning-technique-based data-driven model for accurate and rapid flood predictions in temporal and spatial dimensions." Hydrology and Earth System Sciences 27, no. 9 (2023): 1791–808. http://dx.doi.org/10.5194/hess-27-1791-2023.

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Abstract. An accurate and rapid urban flood prediction model is essential to support decision-making for flood management. This study developed a deep-learning-technique-based data-driven model for flood predictions in both temporal and spatial dimensions, based on an integration of long short-term memory (LSTM) network, Bayesian optimization, and transfer learning techniques. A case study in northern China was applied to test the model performance, and the results clearly showed that the model can accurately predict the maximum water depths and flood time series for various hyetograph inputs,

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Xiaoyue, Liu, and Yang Aimin. "DESIGN OF A VIRTUAL SIMULATION SYSTEM FOR DATABASE TEST CASES." Universal Journal of Mathematics and Mathematical Sciences 21, no. 1 (2025): 57–65. https://doi.org/10.17654/2277141725004.

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This paper introduces the research methods and design framework of the database test case virtual simulation system. It proposes three methods for generating simulation data for computer database cases, represented by the semantic knowledge based reasoning rules. The system provides corresponding simulated data and experimental environments for database-related course experiments in higher education and enterprise application software testing.

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Xie, Juexing, and Wen Luo. "General Surgery Clinical Information Management System Based on Intelligent Data Management." Computational Intelligence and Neuroscience 2022 (August 1, 2022): 1–11. http://dx.doi.org/10.1155/2022/8601164.

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In order to improve the effect of surgical clinical information management, this paper combines the intelligent data management technology to construct the general surgery clinical information management system. Based on the design and development of general surgery clinical medical case information management system, this paper studies the mutual conversion between XML data and relational data, and designs a clinical medical case information management system based on the design idea of layered architecture. The clinical medical case information management system mainly adopts the modular des

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