Unit Testing Research Articles

PENGARUH UNIT-UNIT USAHA TERHADAP KINERJA KEUANGAN PADA KOPERASI PEGAWAI REPUBLIK INDONESIA (KPRI) GURU-GURU RAUNG SITUBONDO

This study aims (1) to determine the partial effect of savings and loan business units, self-service business units and general fueling station business units on financial performance (2) to determine the simultaneous effect of savings and loan business units, self-service business units and station business units. general refueling on financial performance (3) to determine the effect of savings and loan business units, self-service business units and general refueling station business units which have a dominant influence on financial performance. The method used is multiple linear regression analysis, t test, f test, dominant test and coefficient of determination. The result of this research is multiple linear regression equation Y = 4.191 + 0.057 X1 + 0.052 X2 - 0.552 X3 + e. Partial testing is the savings and loan business unit (count )1,578 < t_table 2,042, the self-service business unit tcount 0.395 < ttable 2,036 and the general fuel filling station business unit -tcount -4.693 > -ttable -2,036. Thus, the savings and loan business unit, the self-service business unit and the general fueling station business unit have no effect on financial performance. Simultaneous testing of savings and loan business units, self-service business units and general fueling station business units has an effect on financial performance because the value of Fcount is 7.649 > Ftable 2.90. There is no dominant variable to influence the financial performance variable.

ENTRANT: A Large Financial Dataset for Table Understanding

Tabular data is a way to structure, organize, and present information conveniently and effectively. Real-world tables present data in two dimensions by arranging cells in matrices that summarize information and facilitate side-by-side comparisons. Recent research efforts aim to train large models to understand structured tables, a process that enables knowledge transfer in various downstream tasks. Model pre-training, though, requires large datasets, conveniently formatted to reflect cell and table characteristics. This paper presents ENTRANT, a financial dataset that comprises millions of tables, which are transformed to reflect cell attributes, as well as positional and hierarchical information. Hence, they facilitate, among other things, pre-training tasks for table understanding with deep learning methods. The dataset provides table and cell information along with the corresponding metadata in a machine-readable format. We have automated all data processing and curation and technically validated the dataset through unit testing of high code coverage. Finally, we demonstrate the use of the dataset in a pre-training task of a state-of-the-art model, which we use for downstream cell classification.

Information System for Payment of Dues and Savings at SMA Negeri 1 Cibungbulang School Based on WEB

SMA Negeri 1 Cibungbulang, in recording Student Dues and Savings, still uses a spreadsheet application, where transaction recording use spreadsheet application has identified four cases that were complained of by the school administration: first, when recording payment transaction data, there was still an error in data input; secondly, when created the recapitulation report is still less effective and efficient; third when entering the school year the school Administration needs to re-create spreadsheet pages to separate old and new data; fourth transaction data is still prone to be scattered due to manual storage. Because of this, we need a better alternative to managing student finances so that it can be more effective and efficient. This study aims to analyze, design, and build a WEB-based Information System for Student Dues and Savings at SMA Negeri 1 Cibungbulang. The results obtained can improve the performance of the school administration in managing school finances. The system development method used is the waterfall model, which consists of four steps: Requirement Analysis and Definition, System and Software Design, Implementation and Unit Testing, Integration and System Testing. The results of this study obtained an information system that can manage information consisting of student data, class data, monthly dues data, savings, and recapitulation reports with automatically generate recapitulation reports also present a user-friendly user interface design so that errors in payment input and calculating the number of months in one semester do not occur. This information system is aimed at School Treasurer Staff, School Treasurer, and the Principal.

Organizing Graphical User Interface tests from behavior‐driven development as videos to obtain stakeholders' feedback

AbstractDemonstrating software early and responding to feedback is crucial in agile development. However, it is difficult for stakeholders who are not on‐site customers but end users, marketing people, or designers, and so forth to give feedback in an agile development environment. Successful graphical user interface (GUI) test executions can be documented and then demonstrated for feedback. In our new concept, GUI tests from behavior‐driven development (BDD) are recorded, augmented, and demonstrated as videos. A GUI test is divided into several GUI unit tests, which are specified in Gherkin, a semi‐structured natural language. For each GUI unit test, a video is generated during test execution. Test steps specified in Gherkin are traced and highlighted in the video. Stakeholders review these generated videos and provide feedback, for example, on misunderstandings of requirements or on inconsistencies. To evaluate the impact of videos in identifying inconsistencies, we asked 22 participants to identify inconsistencies between (1) given requirements in regular sentences and (2) demonstrated behaviors from videos with Gherkin specifications or from Gherkin specifications alone. Our results show that participants tend to identify more inconsistencies from demonstrated behaviors, which are not in accordance with given requirements. They tend to recognize inconsistencies more easily through videos than through Gherkin specifications alone. The types of inconsistency are threefold: The mentioned feature can be incorrectly implemented, not implemented, or an unspecified new feature. We use a fictitious example showing how this feedback helps a product owner and her team manage requirements. We conclude that GUI test videos can help stakeholders give feedback more effectively. By obtaining early feedback, inconsistencies can be resolved, thus contributing to higher stakeholder satisfaction.

Design and Implementation of Real-Time Sensors for Three-Phase Induction Motor Performance Monitoring using Internet of Thing (IoT)

This article delves into the design and implementation of cost-effective sensors tailored for real-time monitoring of three-phase induction motor performance. The research primarily centers on the assessment of the operational effectiveness of a suite of sensors, including the PZEM-004t power sensor, MLX90614 temperature sensors, NJK-5002C rotation sensors, and ADXL345 vibration sensors, within the context of three-phase induction motor performance analysis. The monitoring system for three-phase induction motor performance is built around the ESP-32 platform, incorporating the ADXL345 vibration sensor. This article successfully presents the individual sensor performance, which was systematically evaluated through testing on a three-phase induction motor that had been meticulously designed and closely observed. The unit tests reveal that all sensors employed in the experiments exhibit an average error rate of less than 5%. When assessed as an integrated system, the three-phase induction motor performance monitoring system demonstrates robust functionality, effectively measuring critical variables such as voltage, current, power factor, temperature, vibration, and rotational speed.

METHODS OF ENHANCING UNIT TEST QUALITY FOR RELIABLE CODE

In modern software engineering, unit testing plays a central role in maintaining the reliability and quality of the code. In light of this, the article "Methods for Improving Unit Tests to Improve Code Reliability" highlights various strategies and practices aimed at optimizing the unit testing process. Based on extensive research and many years of experience, methods such as improving the independence of tests, increasing their determinism and readability, as well as the introduction of test automation techniques are presented. Important aspects are discussed, including test-driven development (TDD), test coverage analysis, and component isolation. The purpose of the article is to provide readers with a comprehensive set of recommendations for creating faster, clearer and more reliable tests, which ultimately contributes to the development of better software.

Development of a Land and Building Tax Monitoring Module in the North Isimu Village Information System

The information system is a tool to facilitate the potential and resource management in a village. However, due to the current development of the information system in Isimu Utara Village, there are some unavailable and inaccessible features in the system, one of which is the monitoring feature for land and building tax payments. Thus, the researcher is concerned with developing new features in the village information system as one of the alternatives to overcome the problem. This research aimed to develop a land and building tax monitoring module that could be integrated into existing systems. This research implemented the Extreme Programming (XP) method because it had fast and iterative development stages for each part and was aligned with the main goals and targets of development. The result showed that the monitoring module was integrated successfully and became one of the main menus in the village information system. The result of the Unit Test and Acceptance Test also showed that the program has run well.

An empirical study of testing machine learning in the wild

Background: Recently, machine and deep learning (ML/DL) algorithms have been increasingly adopted in many software systems. Due to their inductive nature, ensuring the quality of these systems remains a significant challenge for the research community. Traditionally, software systems were constructed deductively, by writing explicit rules that govern the behavior of the system as program code. However, ML/DL systems infer rules from training data i.e., they are generated inductively). Recent research in ML/DL quality assurance has adapted concepts from traditional software testing, such as mutation testing, to improve reliability. However, it is unclear if these proposed testing techniques are adopted in practice, or if new testing strategies have emerged from real-world ML deployments. There is little empirical evidence about the testing strategies. Aims: To fill this gap, we perform the first fine-grained empirical study on ML testing in the wild to identify the ML properties being tested, the testing strategies, and their implementation throughout the ML workflow. Method: We conducted a mixed-methods study to understand ML software testing practices. We analyzed test files and cases from 11 open-source ML/DL projects on GitHub. Using open coding, we manually examined the testing strategies, tested ML properties, and implemented testing methods to understand their practical application in building and releasing ML/DL software systems. Results: Our findings reveal several key insights: 1.) The most common testing strategies, accounting for less than 40%, are Grey-box and White-box methods, such as Negative Testing , Oracle Approximation , and Statistical Testing . 2.) A wide range of \(17\) ML properties are tested, out of which only 20% to 30% are frequently tested, including Consistency , Correctness , and Efficiency . 3.) Bias and Fairness is more tested in Recommendation (6%) and CV (3.9%) systems, while Security & Privacy is tested in CV (2%), Application Platforms (0.9%), and NLP (0.5%). 4.) We identified 13 types of testing methods, such as Unit Testing , Input Testing , and Model Testing . Conclusions: This study sheds light on the current adoption of software testing techniques and highlights gaps and limitations in existing ML testing practices.

Quality of medicines for Cardio-Vascular Diseases (CVDs) in the Ethiopian border with Kenya: The case of enalapril maleate and furosemide tablet quality in Borena and Gedeo zones.

Hypertension (HTN), a cardiovascular disease (CV), is a major public health challenge. Therefore, the quality of drugs used to treat it has become a major concern. Enalapril and furosemide are among the drugs prescribed to manage hypertension. Hence, this study is aimed at evaluating the quality of different brands of enalapril and furosemide tablets available in the Gedeo and Borena zones, southern Ethiopia. Thirteen generic brands of enalapril maleate (5 mg) and furosemide (40 mg) tablets were evaluated for visual defects, in vitro dissolution test, weight variations, friability, hardness, and disintegration tests. The analysis of active pharmaceutical ingredient (API) content was performed by high performance liquid chromatography (HPLC). Out of 55 samples, 7 (12.73%) failed to comply with the criteria for visual inspection; otherwise, all samples passed the identification test. Except for one brand of each of enalapril maleate and furosemide, all passed the dissolution test. The assay value showed that all enalapril maleate samples were within the limits of United States Pharmacopoeia (USP), 2020. Additionally, except for two batches, all furosemide samples were within the USP and British Pharmacopoeia (BP), 2020 standards. Out of 55 samples, 8% (2/25) and 6.67% (2/30) of enalapril maleate and furosemide tablets failed the uniformity of dosage units test per the USP-2020, respectively. All samples passed the disintegration test, and selected furosemide samples passed the microbial limit tests. However, 36% (9/25) and 20% (6/30) of enalapril maleate and furosemide samples failed to pass hardness test. Generally, from the total samples, 50.91% (28/55) were substandard (did not meet the specifications failing any one or more parameters assessed). The studied drugs circulating in the market did not meet some of the needed quality specifications. This could have brought a risk of reduced efficacy due to the distribution of poor quality medicines in the area.

Evaluating and Improving ChatGPT for Unit Test Generation

Unit testing plays an essential role in detecting bugs in functionally-discrete program units (e.g., methods). Manually writing high-quality unit tests is time-consuming and laborious. Although the traditional techniques are able to generate tests with reasonable coverage, they are shown to exhibit low readability and still cannot be directly adopted by developers in practice. Recent work has shown the large potential of large language models (LLMs) in unit test generation. By being pre-trained on a massive developer-written code corpus, the models are capable of generating more human-like and meaningful test code. In this work, we perform the first empirical study to evaluate the capability of ChatGPT (i.e., one of the most representative LLMs with outstanding performance in code generation and comprehension) in unit test generation. In particular, we conduct both a quantitative analysis and a user study to systematically investigate the quality of its generated tests in terms of correctness, sufficiency, readability, and usability. We find that the tests generated by ChatGPT still suffer from correctness issues, including diverse compilation errors and execution failures (mostly caused by incorrect assertions); but the passing tests generated by ChatGPT almost resemble manually-written tests by achieving comparable coverage, readability, and even sometimes developers' preference. Our findings indicate that generating unit tests with ChatGPT could be very promising if the correctness of its generated tests could be further improved. Inspired by our findings above, we further propose ChatTester, a novel ChatGPT-based unit test generation approach, which leverages ChatGPT itself to improve the quality of its generated tests. ChatTester incorporates an initial test generator and an iterative test refiner. Our evaluation demonstrates the effectiveness of ChatTester by generating 34.3% more compilable tests and 18.7% more tests with correct assertions than the default ChatGPT. In addition to ChatGPT, we further investigate the generalization capabilities of ChatTester by applying it to two recent open-source LLMs (i.e., CodeLLama-Instruct and CodeFuse) and our results show that ChatTester can also improve the quality of tests generated by these LLMs.

Forecasting the parameters of performance monitoring of complex technical systems

The problem of monitoring the performance of technical systems is considered, corresponding to the stage of final control during the production of a product, as well as the stage of testing the product before its use. Based on the generalization and development of the existing approaches, models and methods for monitoring the performance of complex technical systems were developed, and models for predicting the parameters of their control were proposed. Methods of optimizing the number of tests of units of technical systems when monitoring their performance were developed. Methods for estimating the optimal level of the total defect rate are proposed. The efficiency of the proposed approaches is illustrated using a specific numerical example. The methods and models presented in the article can be useful for engineering and technical workers of design bureaus, research institutes, research and production associations and enterprises in ensuring the reliability of products and technical systems.

Pemanfaatan Metode TOPSIS dalam Membangun Sistem Pendukung Keputusan untuk Menentukan Jenis Penyakit Tanaman Gandum; Studi Kasus di Ladang Gandum Alahan Panjang, Sumatera Barat

Wheat (Triticum aestivum L.) is an annual plant that can grow in highland areas. There are many types of diseases that attack wheat plants, making it difficult for farmers to determine the type of disease. Therefore, it is necessary to build a Decision Support System (DSS) that can determine the type of disease that attacks wheat plants. This research aimed to design and develop a Decision Support System (DSS) application to identify the types of diseases affecting wheat by observing the physical characteristics of the plants. These disease characteristics (criteria) were then inputed into the system, which used an algorithm based on the Technique for Order of Preference by Similarity to a Ideal Solution (TOPSIS) method. The DSS method used was TOPSIS, which considered four criteria: Flower, Stem, Seed, and Leaf. The application development method for the DSS used the Waterfall model, which consisted of the following stages: requirements, definition, system and software design, implementation, and unit testing. A DSS application using the TOPSIS method can determine the type of wheat disease based on physical characteristics as criteria that are inputed into the application. This application can help wheat farmers identify the diseases affecting their plants. The use of the TOPSIS method algorithm in developing the SPK application is an innovation that can help Alahan Panjang wheat farmers in detecting diseases types affecting their crops based on visible physical characteristics. Automatically, the system provides recommendations on the type of disease affecting the wheat plants.

PPH 21 Tax Calculation Application for Permanent Employees at The Bandung Regency Fire Service

This study aims to create a software application that can accurately compute PPh 21 (income tax) for full-time employees at the Bandung Regency Fire Department. The development process will utilize an Object-Oriented Analysis and Design (OOAD) System Development approach. The primary aim of this study is to mechanize the computation of PPh 21 in compliance with relevant tax statutes while streamlining tax and payroll administration at the organization. The development methodology comprises five primary phases: requirements analysis, system design, implementation, testing, and assessment. During the requirements analysis phase, data is gathered through interviews, observations, and literature research to comprehend the system's functional and non-functional requirements. The system design step entails developing a system architectural design that includes class, use case, and interaction diagrams to guarantee that the system fulfills the given requirements. Implementation involves creating program code based on the design and integrating system components. The testing phase encompasses unit, integration, system, and acceptance testing to verify that the system operates as intended and is error-free. The evaluation phase incorporates the participation of end users to gather input on the system's usability, efficiency, and precision and introduce enhancements prior to its complete implementation. The research findings demonstrate that using this internet-based application can enhance the effectiveness and precision of tax computations, mitigate the likelihood of data loss, and facilitate heightened job efficiency at the Bandung Regency Fire Department. This application is anticipated to favorably impact tax and payroll management at the agency while also enhancing the quality of public services through digitalization and technological innovation.

Automated Testing in DevOps: Strategies and Tools

Automated testing is a cornerstone of the DevOps methodology, enabling rapid and reliable software delivery. This paper explores the strategies and tools integral to implementing effective automated testing within a DevOps framework. Key strategies include continuous testing, shift-left testing, and test-driven development, among others. The paper also provides an overview of various tools that facilitate automated testing at different stages of the software development lifecycle, from unit testing to performance and security testing. Through case studies and analysis, the paper highlights both the benefits and challenges of automated testing in DevOps, and discusses future trends and advancements in the field

Testing Multi-Subroutine Quantum Programs: From Unit Testing to Integration Testing

Quantum computing has emerged as a promising field with the potential to revolutionize various domains by harnessing the principles of quantum mechanics. As quantum hardware and algorithms continue to advance, developing high-quality quantum software has become crucial. However, testing quantum programs poses unique challenges due to the distinctive characteristics of quantum systems and the complexity of multi-subroutine programs. This article addresses the specific testing requirements of multi-subroutine quantum programs. We begin by investigating critical properties by surveying existing quantum libraries and providing insights into the challenges of testing these programs. Building upon this understanding, we focus on testing criteria and techniques based on the whole testing process perspective, spanning from unit testing to integration testing. We delve into various aspects, including IO analysis, quantum relation checking, structural testing, behavior testing, integration of subroutine pairs, and test case generation. We also introduce novel testing principles and criteria to guide the testing process. We conduct comprehensive testing on typical quantum subroutines, including diverse mutants and randomized inputs, to evaluate our proposed approach. The analysis of failures provides valuable insights into the effectiveness of our testing methodology. Additionally, we present case studies on representative multi-subroutine quantum programs, demonstrating the practical application and effectiveness of our proposed testing principles and criteria.

Vestibular Migraine and Recurrent Vertigo in Children: A Diagnostic Focus From a Tertiary Hospital Study

BackgroundTo improve diagnostic precision in pediatric vertigo, particularly in Vestibular Migraine of Childhood (VMC), probable VMC (pVMC), Recurrent Vertigo of Childhood (RVC), and unspecified categories, by delineating clinical characteristics and prevalence to refine diagnostics and treatments. MethodsRetrospective analysis of 102 pediatric patients (five to 18 years; 46 females, 56 males) at the Dizziness Center of the Otolaryngology Department in a tertiary-level hospital from January 2019 to December 2023. Patients were classified into VMC, pVMC, RVC, and indeterminate groups. Evaluations included audiometry and vestibular tests (video head impulse test [vHIT] or caloric testing), conducted in the audiology unit and vestibular testing laboratory. Data were analyzed using IBM SPSS 20.0. ResultsDiagnoses were 8.8% VMC, 31.4% pVMC, 51.0% RVC, and 8.8% indeterminate. Nausea and vomiting were common in VMC and pVMC; cochlear symptoms like tinnitus and hearing loss predominated in VMC. Although vestibular testing showed no significant group differences, VMC had more vHIT abnormalities and RVC had more caloric test anomalies. ConclusionsThis study highlights the need for comprehensive diagnostics in pediatric vestibular disorders, revealing unique and overlapping traits across VMC, pVMC, and RVC. Insights call for further research to refine diagnostic criteria and improve treatment methods.

أثر استخدام استراتيجية الصف المقلوب في تنمية النمو المعرفي بوحدة الغذاء لدى أطفال الروضة

This study aimed to reveal the effect of using the flipped classroom strategy in developing the cognitive growth of the food unit among kindergarten children. The experimental method was used with a semi-experimental design, one-group, on a research sample consisting of (22) children from the third level from the Kindergarten Teachers Training Center in the city of Jeddah. The two researchers prepared a pre-post cognitive test for the food unit. The results of the study revealed that there are statistically significant differences between the mean scores of the children of the experimental group in the pre and post applications to measure the growth of basic and higher thinking skills among kindergarten children in the food unit, and the differences came in favor of the post application. The study also recommends training and encouraging kindergarten and early childhood teachers to use the flipped classroom strategy in the educational process.

Transfusion support and pre-transfusion testing in autoimmune haemolytic anaemia.

Autoimmune haemolytic anaemia (AIHA) is characterized by an increased destruction of red blood cells due to immune dysfunction and auto-antibody production. Clinical manifestations are mainly related to anaemia, which can become life-threatening in case of acute haemolysis. Aiming at counterbalancing severe anaemia, supportive treatments for these patients frequently include transfusions. Unfortunately, free serum auto-antibodies greatly interfere in pre-transfusion testing, and the identification of compatible red blood cell units for AIHA patients can be challenging or even impossible. Problems faced in pre-transfusion testing often lead to delay or abandonment of transfusions for AIHA patients. In this review, we discuss publications concerning global transfusion management in AIHA, with a focus on pre-transfusion testing, and practical clues to manage the selection of transfusion units for these patients. Depending on the degree of transfusion emergency, we propose an algorithm for the selection and laboratory testing of units to be transfused to AIHA patients.

Development of the ITSJava Application as a Computer-assisted Learning Media in Object-Oriented Programming Courses

This research aims to develop ITSJava application as an interactive learning media for object-oriented programming (OOP) course in information technology education programme at Gorontalo State University. ITSJava was developed using the Personal Xtreme Programming (PXP) development method which consists of six stages: needs identification, planning, initial iteration, design, implementation, and system testing. The results of system testing show that the ITSJava application is suitable for use as a medium for learning OOP. This system can help students learn OOP in an interactive and adaptive way to students' learning styles. Hopefully, this system can be further developed by adding a unit test function to ensure the accuracy of the program code written by students and ensure that the code runs according to the expectations and logic expected by the lecturer.

A Control Flow Graph Generation Method for Java Projects

Many software quality assurance methods depend on the control flow graph (CFG) for theanalyzing process. However, existing methods for Java projects have not described details of the CFGgeneration process, which is critical for having a fully automatic analysis method. This paper presentsa novel method, named CFG4J, for generating CFG associated with a given Java unit. The generatedCFG will be used in many other software quality assurance methods such as test data generation forunit testing, unit debugging, code coverage computation, etc. We have implemented CFG4J in a tooland performed some initial experiments with some common units with potential results. Finally, wegive some discussions about the experimental results at the end of the paper.Keywords: Control flow graph, unit testing, test data generation, Java projects.