Automatic Test Research Articles

Design and Realization of Fully Automatic Pump Performance Test System

With the development of automation technology, it gradually replaces manual labor in various fields. Pumps are widely used in various production processes in the industrial field. To enhance the automation level of the pump production and testing process will significantly reduce production costs. This paper aims to design and realize a set of fully automatic, high-precision pump performance testing system. The fully automated operation of the performance test is designed according to the flow rate automatic sampling method, to achieve the accurate measurement of the pump operating conditions. Utilizing the PID algorithm, the valve is automatically adjusted through PLC control to realize the accurate positioning of the flow measurement point. With the help of the software program to carry out the calculation and analysis of test data, to achieve the visualization of the test process of the whole performance test data management. At the same time, SQL Server database is used to realize rapid query and management of test data. After the test verification, the system realizes the full-automatic measurement of the pump performance curve, and the measurement accuracy conforms to the standard of ISO 9906:2012.

Experiment and simulation study on the functional fatigue of shape memory alloy beam actuators

The functional fatigue behavior of shape memory alloy (SMA) beam actuators is gaining importance as their utilization in engineering applications becomes more widespread. However, research on the functional fatigue behavior of SMA beam actuators under bending conditions is not as extensive as that on SMA wires. In this paper, an experimental study and theoretical analysis of the functional fatigue behavior of SMA beam actuators were conducted. A measuring method for bending deflection and an automatic thermal cyclic test bench was designed. A series of functional fatigue tests were conducted on SMA beam actuators under different bias load conditions and the functional fatigue patterns were obtained. The material damage factor is defined and calculated through specimen tests. By incorporating the damage factor to modify the existing constitutive model, a model considering functional fatigue and tension-compression asymmetry is obtained. Finite element analysis (FEA) is performed based on this modified model to simulate the actuating performance of SMA beam actuators and to compute the deflection at different numbers of cycles. Additionally, a small parameter study on the actuator shape is conducted using FEA. By comparing the FEA results with functional fatigue experimental data, the effectiveness of the modified model is validated, demonstrating its capability to describe functional fatigue and predict actuator lifespan.

Toward granular search-based automatic unit test case generation

Unit testing verifies the presence of faults in individual software components. Previous research has been targeting the automatic generation of unit tests through the adoption of random or search-based algorithms. Despite their effectiveness, these approaches aim at creating tests by solely optimizing metrics like code coverage, without ensuring that the resulting tests have granularities that would allow them to verify both the behavior of individual production methods and the interaction between methods of the class under test. To address this limitation, we propose a two-step systematic approach to the generation of unit tests: we first force search-based algorithms to create tests that cover individual methods of the production code, hence implementing the so-called intra-method tests; then, we relax the constraints to enable the creation of intra-class tests that target the interactions among production code methods. The assessment of our approach is conducted through a mixed-method research design that combines statistical analyses with a user study. The key results report that our approach is able to keep the same level of code and mutation coverage while providing test suites that are more structured, more understandable and aligned to the design principles of unit testing.

Robotic Process Automation Efficiency for Mobile App Testing: An Empirical Investigation

In today’s rapidly evolving software environment, the graphical user interface (GUI) plays a crucial role in providing intuitive, user-friendly interaction. However, traditional intrusive GUI testing methods often face challenges such as interrupting user workflows, requiring significant manual effort and insufficient test scenario coverage. Non-intrusive testing methods, such as Robotic Process Automation (RPA), offer a solution to validate GUI functionality without modifying the application’s code or affecting the user experience. RPA systems automate repetitive tasks by simulating user interactions, becoming valuable tools in GUI testing. However, challenges like limited computational resources, time constraints, or restricted exploration capabilities may limit the efficiency of individual RPA agents, thus restricting coverage and effectiveness. To address this issue, this study explores the performance of a single RPA agent versus an RPA cluster under different testing conditions, using three popular testing methods: Monkey, Stoat and Q-testing. Experimental results indicate that an RPA cluster outperforms a single RPA in GUI coverage and error detection, making a significant contribution to the field of non-intrusive GUI exploration testing. The findings of this study provide directions for future research to ensure the delivery of high-quality mobile applications.

BFTDiagnosis: An automated security testing framework with malicious behavior injection for BFT protocols

In peer-to-peer computing networks, Byzantine Fault Tolerance (BFT) protocols are a popular solution to ensure the consistency security in the presence of some malicious nodes, thus are widely employed in blockchain systems. However, BFT protocols still face various security threats in practice. Currently, testing the security of BFT protocols often requires manual operations. I.e., it lacks comprehensive automation testing techniques. This makes it difficult to cover various scenarios of malicious node behaviors. Therefore, it is an urgent requirement to design an automated testing framework that can comprehensively and efficiently evaluate the security of BFT protocols.This paper proposes BFTDiagnosis, an automated security testing framework with malicious behavior injection for BFT protocols. The framework can automatically configure and initiate protocol testing tasks, and construct consensus nodes to execute different BFT protocols. During testing, consensus nodes can inject malicious behaviors based on pattern matching strategies and malicious behavior triggering mechanisms to simulate various malicious scenarios. Through an Analyzer, BFTDiagnosis can collect protocol runtime data from consensus nodes and calculate four security quantification indicators to evaluate protocol performance.We conducted a load consumption evaluation of BFTDiagnosis. The results indicate its acceptable performance. Additionally, we tested PBFT, Basic-HotStuff, and Chained-HotStuff protocols using the BFTDiagnosis framework, validating the effectiveness of the framework and the rationality of security quantification indicators. Finally, we compared it with nine related technologies and found that BFTDiagnosis is good at testing scenario comprehensiveness and fault localization capability, and can intuitively evaluate the security of BFT protocols through four quantification indicators. The above results show that BFTDiagnosis is an effective and comprehensive security testing framework for BFT protocols.

Novel Feature-Based Difficulty Prediction Method for Mathematics Items Using XGBoost-Based SHAP Model

The level of difficulty of mathematical test items is a critical aspect for evaluating test quality and educational outcomes. Accurately predicting item difficulty during test creation is thus significantly important for producing effective test papers. This study used more than ten years of content and score data from China’s Henan Provincial College Entrance Examination in Mathematics as an evaluation criterion for test difficulty, and all data were obtained from the Henan Provincial Department of Education. Based on the framework established by the National Center for Education Statistics (NCES) for test item assessment methodology, this paper proposes a new framework containing eight features considering the uniqueness of mathematics. Next, this paper proposes an XGBoost-based SHAP model for analyzing the difficulty of mathematics tests. By coupling the XGBoost method with the SHAP method, the model not only evaluates the difficulty of mathematics tests but also analyzes the contribution of specific features to item difficulty, thereby increasing transparency and mitigating the “black box” nature of machine learning models. The model has a high prediction accuracy of 0.99 for the training set and 0.806 for the test set. With the model, we found that parameter-level features and reasoning-level features are significant factors influencing the difficulty of subjective items in the exam. In addition, we divided senior secondary mathematics knowledge into nine units based on Chinese curriculum standards and found significant differences in the distribution of the eight features across these different knowledge units, which can help teachers place different emphasis on different units during the teaching process. In summary, our proposed approach significantly improves the accuracy of item difficulty prediction, which is crucial for intelligent educational applications such as knowledge tracking, automatic test item generation, and intelligent paper generation. These results provide tools that are better aligned with and responsive to students’ learning needs, thus effectively informing educational practice.

3022: Automation of the Rotation Period quality control test of a Tomotherapy linear accelerator

3022: Automation of the Rotation Period quality control test of a Tomotherapy linear accelerator

Development of an Automated Morphometric Approach to Assess Vascular Outcomes following Exposure to Environmental Chemicals in Zebrafish.

Disruptions in vascular formation attributable to chemical insults is a pivotal risk factor or potential etiology of developmental defects and various disease settings. Among the thousands of chemicals threatening human health, the highly concerning groups prevalent in the environment and detected in biological monitoring in the general population ought to be prioritized because of their high exposure risks. However, the impacts of a large number of environmental chemicals on vasculature are far from understood. The angioarchitecture complexity and technical limitations make it challenging to analyze the entire vasculature efficiently and identify subtle changes through a high-throughput in vivo assay. We aimed to develop an automated morphometric approach for the vascular profile and assess the vascular morphology of health-concerning environmental chemicals. High-resolution images of the entire vasculature in Tg(fli1a:eGFP) zebrafish were collected using a high-content imaging platform. We established a deep learning-based quantitative framework, ECA-ResXUnet, combined with MATLAB to segment the vascular networks and extract features. Vessel scores based on the rates of morphological changes were calculated to rank vascular toxicity. Potential biomarkers were identified by vessel-endothelium-gene-disease integrative analysis. Whole-trunk blood vessels and the cerebral vasculature in larvae exposed to 150 representative chemicals were automatically segmented as comparable to human-level accuracy, with sensitivity and specificity of 95.56% and 95.81%, respectively. Chemical treatments led to heterogeneous vascular patterns manifested by 31 architecture indexes, and the common cardinal vein (CCV) was the most affected vessel. The antipsychotic medicine haloperidol, flame retardant 2,2-bis(chloromethyl)trimethylenebis[bis(2-chloroethyl) phosphate], and tert-butylphenyl diphenyl phosphate ranked as the top three in vessel scores. Pesticides accounted for the largest group, with a vessel score of , characterized by a remarkable inhibition of subintestinal venous plexus and delayed development of CCV. Multiple-concentration evaluation of nine per- and polyfluoroalkyl substances (PFAS) indicated a low-concentration effect on vascular impairment and a positive association between carbon chain length and benchmark concentration. Target vessel-directed single-cell RNA sequencing of cells from larvae treated with , perfluorohexanesulfonic acid, or benzylbutyl phthalate, along with vessel-endothelium-gene-disease integrative analysis, uncovered potential associations with vascular disorders and identified biomarker candidates. This study provides a novel paradigm for phenotype-driven screenings of vascular-disrupting chemicals by converging morphological and transcriptomic profiles at a high-resolution level, serving as a powerful tool for large-scale toxicity tests. Our approach and the high-quality morphometric data facilitate the precise evaluation of vascular effects caused by environmental chemicals. https://doi.org/10.1289/EHP13214.

Can Oscillometry Replace Spirometry as a Major Tool for Lung Function Testing? – An Overview

Abstract Developing countries face a huge challenge in managing obstructive lung disorders due to frequency, severity, management, and economic impact. Spirometry has been the popular choice to assess the severity and reversibility of airflow obstruction, but the success of evaluation depends on the practitioner’s skills and the patient’s cooperation. Impulse oscillometry (IOS), a variant of forced oscillation technique is preferred over spirometry since it can be performed without forced respiratory maneuvers. The objective of this review is to evaluate IOS techniques and weigh its benefits against spirometry. Publications from international electronic databases such as PubMed, Scopus, and Web of Science were searched using relevant keywords for 5 years (2018–2023). A total of 416 articles were filtered, and of these, 70 were selected which specifically discussed the principles, procedures, parameters, and interpretations of spirometry and oscillometry. From the full-text articles included, we have reflected on the history, defined, explained, compared, and contrasted spirometry and oscillometry methods to establish the versatility of oscillometry technique to identify small airway functions and its application in special clinical conditions. This review presents an easily comprehensible synthesis of oscillometry and spirometry bringing out the principles, advantages, and limitations that are suitable for a larger spectrum of healthcare and research community.

Design of Laser-Powered Opto-Electrical Current Transformer and Its Application in Electrical Automation of Substations

The novel power equipment represented by the Opto-Electrical Current Transformer (OECT) possesses unparalleled advantages compared to traditional Current Transformers (CTs), rendering it with vast potential in power systems. In the design of OECT, this study employs laser power supply and focuses on the overall perspective, particularly the design of the laser power supply module and the optical fiber digital transmission module. The laser power supply module selects a high-power semiconductor laser to provide power to the circuit, incorporating line filters, thermistor resistors, and a laser overcurrent protection circuit. An automatic temperature control circuit based on PI regulation is utilized to stabilize the working temperature of the laser diode (LD). The photoelectric conversion device PPC-6E achieves a maximum photoelectric conversion efficiency of 40%, and the MAX639 DC–DC conversion chip ensures stable output voltage. The optical fiber digital transmission module adopts a circuit composed of multiple NOR gate logic for electro-optical conversion, a low-power driving circuit based on the 74LVC1G07 chip, and the HFBR-2412 photoelectric converter to simplify the circuit board design. To achieve a higher communication baud rate, a quartz multimode optical fiber with a diameter of 62.5 μm is chosen. In the experimental phase, a simulation of high-power AC power with equal turns is conducted. The linearity/temperature test results demonstrate that the designed OECT in this study meets expectations. In the electrical automation test of substations, a comparison between traditional CTs and the designed OECT is carried out using traditional protection algorithms and optical differential protection algorithms. The results indicate that, compared to traditional protection algorithms, the optical differential algorithm using the designed OECT achieves faster protection times.

EVALUATION OF NEW DEVELOPED MODELS FOR ESTIMATION OF DIFFUSE SOLAR RADIATION OVER IKEJA, LAGOS STATE, NIGERIA

This study investigates the estimation of diffuse solar radiation in Ikeja, Nigeria (6.58°N, 3.33°E, 39.40m above sea level). Employing a 22-year dataset (2001-2022) of monthly average climatic data from NASA website, nineteen new models were developed to predict diffuse solar radiation. These models incorporated various meteorological parameters including global solar radiation, wind speed, temperature, pressure, and relative humidity. A categorized approach was used, with models falling into five groups: modified Page, Liu and Jordan; clearness index with one additional variable; two-variable; three-variable; and a four-variable model. Evaluation using five statistical tests tools of Mean Bias Error (MBE), Root Mean Square Error (RMSE), Mean Percentage Error (MPE), t-test, and Coefficient of determination (R²) identified Equation 28h (the model relating diffuse radiation to clearness index and temperature) as the most suitable model out of all the models in each of the five categories for estimation of diffuse solar radiation for Ikeja. Hence, emphasizing the importance of considering both atmospheric clarity and temperature for accurate diffuse solar radiation estimation in this coastal location.

Synthetic Gaia DR3 Surveys from the FIRE Cosmological Simulations of Milky Way-mass Galaxies

The third data release (DR3) of Gaia has provided a fivefold increase in the number of radial velocity measurements of stars, as well as a stark improvement in parallax and proper motion measurements. To help with studies that seek to test models and interpret Gaia DR3, we present nine Gaia synthetic surveys, based on three solar positions in three Milky Way-mass galaxies of the Latte suite of the Fire-2 cosmological simulations. These synthetic surveys match the selection function, radial velocity measurements, and photometry of Gaia DR3, adapting the code base Ananke, previously used to match the Gaia DR2 release by Sanderson et al. The synthetic surveys are publicly available and can be found at http://ananke.hub.yt/. Similarly to the previous release of Ananke, these surveys are based on cosmological simulations and thus are able to model nonequilibrium dynamical effects, making them a useful tool in testing and interpreting Gaia DR3.

Advances in Traditional Electrical Validation of High-Speed Serial Connections Using Innovative Debugging Methods and Machine Learning Models.

As technology continues to shrink and more heterogeneous blocks are combined into single System on a chip (SOCs), the design of high-performance integrated circuits is getting more and more difficult. In the course of silicon validation, which includes testing (Wafer Testing, Automatic Test Equipment), digital validation (Functional Data route, FSM), analogue bench validation (Electrical, Interoperability), and system validation, a number of challenges that arise from the complicated design are uncovered. The process, methods, and constraints of each domain are unique. Electrical problems that have already passed through earlier stages of design are the primary focus of analogue validation. The analogue signal or mix signal nature of IPs makes it impossible for digital validation or any of the other post-silicon domains to discover electrical flaws on its own. As a result, studies focusing on analogue bench validation have grown in prominence. Recent developments in analogue bench validation, focusing on high-speed serial interface in particular, are highlighted in the proposed study. In addition, this article summarises recent technological developments that provide avenues for further study regarding analogue bench validation.

FATE: A Flexible FPGA-Based Automatic Test Equipment for Digital ICs

The limits of chip technology are constantly being pushed with the continuous development of integrated circuit manufacturing processes and equipment. Currently, chips contain several billion, and even tens of billions, of transistors, making chip testing increasingly challenging. The verification of very large-scale integrated circuits (VLSI) requires testing on specialized automatic test equipment (ATE), but their cost and size significantly limit their applicability. The current FPGA-based ATE is limited in its scalability and support for few test channels and short test vector lengths. As a result, it is only suitable for testing specific chips in small-scale circuits and cannot be used to test VLSI. This paper proposes a low-cost hardware and software solution for testing digital integrated circuits based on design for testability (DFT) on chips, which enables the functional and performance test of the chip. The solution proposed can effectively use the resources within the FPGA to provide additional test channels. Furthermore, the round-robin data transmission mode can also support test vectors of any length and it can satisfy different types of chip test projects through the dynamic configuration of each test channel. The experiment successfully tested a digital signal processor (DSP) chip with 72 scan test pins (theoretically supporting 160 test pins). Compared to our previous work, the work in this paper increases the number of test channels by four times while reducing resource utilization per channel by 37.5%, demonstrating good scalability and versatility.

The tale of HORTON: Lessons learned in a decade of scientific software development.

HORTON is a free and open-source electronic-structure package written primarily in Python 3 with some underlying C++ components. While HORTON's development has been mainly directed by the research interests of its leading contributing groups, it is designed to be easily modified, extended, and used by other developers of quantum chemistry methods or post-processing techniques. Most importantly, HORTON adheres to modern principles of software development, including modularity, readability, flexibility, comprehensive documentation, automatic testing, version control, and quality-assurance protocols. This article explains how the principles and structure of HORTON have evolved since we started developing it more than a decade ago. We review the features and functionality of the latest HORTON release (version 2.3) and discuss how HORTON is evolving to support electronic structure theory research for the next decade.

Synthetic human gonadal tissues for toxicology

The process of mammalian reproduction involves the development of fertile germ cells in the testis and ovary, supported by the surrounders. Fertilization leads to embryo development and ultimately the birth of offspring inheriting parental genome information. Any disruption in this process can result in disorders such as infertility and cancer. Chemical toxicity affecting the reproductive system and embryogenesis can impact birth rates, overall health, and fertility, highlighting the need for animal toxicity studies during drug development. However, the translation of animal data to human health remains challenging due to interspecies differences. In vitro culture systems offer a promising solution to bridge this gap, allowing the study of mammalian cells in an environment that mimics the physiology of the human body. Current advances on in vitro culture systems, such as organoids, enable the development of biomaterials that recapitulate the physiological state of reproductive organs. Application of these technologies to human gonadal cells would provide effective tools for drug screening and toxicity testing, and these models would be a powerful tool to study reproductive biology and pathology. This review focuses on the 2D/3D culture systems of human primary testicular and ovarian cells, highlighting the novel approaches for in vitro study of human reproductive toxicology, specifically in the context of testis and ovary.

Artificial intelligence techniques and tools for performance testing & monitoring of server-less computing

Artificial intelligence techniques and tools for performance testing & monitoring of server-less computing

An Engineered Minimal-Set Stimulus for Periodic Information Leakage Fault Detection on a RISC-V Microprocessor

Recent evaluations of counter-based periodic testing strategies for fault detection in Microprocessor (μP) have shown that only a small set of counters is needed to provide complete coverage of severe faults. Severe faults are defined as faults that leak sensitive information, e.g., an encryption key on the output of a serial port. Alternatively, fault detection can be accomplished by executing instructions that periodically test the control and functional units of the μP. In this paper, we propose a fault detection method that utilizes an ’engineered’ executable program combined with a small set of strategically placed counters in pursuit of a hardware Periodic Built-In-Self-Test (PBIST). We analyze two distinct methods for generating such a binary; the first uses an Automatic Test Generation Pattern (ATPG)-based methodology, and the second uses a process whereby existing counter-based node-monitoring infrastructure is utilized. We show that complete fault coverage of all leakage faults is possible using relatively small binaries with low latency to fault detection and by utilizing only a few strategically placed counters in the μP.

Residual Stress Characterization in Microelectronic Manufacturing: An Analysis Based on Raman Spectroscopy

AbstractIn the rapidly evolving era of information and intelligence,microelectronic devices are pivotal across various fields, such as mobile devices, big data computing, electric vehicles, and aerospace. However, the electrical performance of these devices often suffers due to residual stress from microelectronic manufacturing. This issue is compounded by the additional thermal stress that accumulates during device operation. Therefore, it is essential to understand, characterize, and control this residual stress to ensure the reliability and efficiency of microelectronic devices. Raman spectroscopy emerges as an invaluable tool for nondestructive, fast, noncontact, and precise testing of micro‐scale mechanics, significantly aiding in stress and strain analysis within microelectronic manufacturing. This article aims to provide a thorough overview of the theory and application beyond a mere compilation of recent advances. Theoretically, it critically evaluates existing models that describe the Raman‐stress relation. Practically, it explores the application of Raman spectroscopy in researching residual stress in various components, including substrate materials, epitaxial films, and packaging. Through a detailed examination of current applications, it highlights the significance of Raman spectroscopy in understanding micro‐scale mechanics. Finally, it offers both theoretical and practical insights into the future developments of Raman‐stress detection technology.

Geology, geochronology, and genesis of Au mineralization from the Huangshui'an Mo-Au-Pb deposit in Eastern Qinling, China

Huangshui'an deposit, situated in the Xiong'ershan area of Qinling orogenic belt (QOB) in China, is a globally rare carbonatite-type molybdenum polymetallic deposit that contains economic Mo, Au, Pb, and REE mineralization. The molybdenite Re-Os ages (Ca. 213.5–209.2 Ma) indicates that Huangshui'an Mo mineralization formed at Late Triassic. However, it is still unclear whether the Au mineralization is related to carbonatite dykes, and the formation age and genesis mechanism of Au mineralization remain poorly understood at Huangshui'an. This paper presents a comprehensive investigation of the Au mineralization events at the Huangshui'an deposit, including geology, mineralogy, and geochronology. The aim is to provide insights into its formation and mineralization processes and offer a broader understanding of regional Au metallogeny. Based on petrographic investigations, four stages are identified in the Au mineralization as follows: (I) quartz-K-feldspar stage; (II) quartz-pyrite-gold stage, including (IIA) pyrite-native gold sub-stage and (IIB) gold-tellurite-bismuthide sub-stage; (III) quartz-pyrite-polymetallic sulphide-oxide stage; and (IV) calcite-quartz-chlorite stage. The LA-ICP-MS titanite U-Pb dating yields a weighted mean age of 130.8 ± 0.63 Ma which determined that the Au mineralization at Huangshui’an was in the Early Cretaceous and was an independent mineralization event, which may be related to the lithosphere's destructive effect on the North China Craton (NCC). Combined with mineralography by automatic quantitative mineral analysis and testing system (TIMA), we consider that tellurium-bismuth minerals are closely associated with Au mineralization. The sulfur and tellurium fugacity of the ore-forming fluids in each stage were calculated using metal sulfide-oxides and tellurium-bismuth minerals. It was concluded that the precipitation of Au in the Huangshui'an deposit was mainly due to the combined effects of sulfidation, gold collection-redissolution by the low-melting point chalcophile elements (LMCE) melts, and the variation of sulfur fugacity and tellurium fugacity.