Stages Of Software Development Research Articles

Analisis Pengujian Website Desa Ketapanrame Berdasarkan Model FURPS Menggunakan Metode Euclidean Distance

The importance of software testing is very prominent in the software development stage. Software testing is an important aspect that cannot be ignored to ensure the quality of an application. One example is testing dynamic web pages such as the one that will be the main focus of the research, namely the Ketapanrame Village Website. Testing of the Ketapanrame Village Website was carried out thoroughly on various aspects, including feature functionality and web appearance aesthetics, to ensure compliance with the specified specifications. In order to achieve satisfactory results from testing, there are feature elements on the web page that will be tested using the FURPS model standard. Each indicator from the FURPS model has a special role in ensuring the overall quality of the software by involving the participation of respondents to find the average value. The challenge arises in finding an appropriate average value for testing such web pages. To overcome this problem, this research is distributing questionnaires to find values from respondents and will calculate the average value using the Euclidean Distance method. This concept was chosen because it has been proven to provide optimal average values. The test results show that the combination of the FURPS model and the Euclidean Distance calculation method provides satisfactory results. Combination suitability is not easy to do, especially in the part of finding the average value which must involve many parties to achieve optimal results.

Preliminary Estimation for Software Development Projects Empowered with a Method of Recommending Optimal Duration and Team Composition

In the early software development stages, the aim of estimation is to obtain a rough understanding of the timeline and resources required to implement a potential project. The current study is devoted to a method of preliminary estimation applicable at the beginning of the software development life cycle when the level of uncertainty is high. The authors’ concepts of the estimation life cycle, the estimable items breakdown structure, and a system of working-time balance equations in conjunction with an agile-fashioned sizing approach are used. To minimize the experts’ working time spent on preliminary estimation, the authors applied a decision support procedure based on integer programming and the analytic hierarchy process. The method’s outcomes are not definitive enough to make commitments; instead, they are supposed to be used for communication with project stakeholders or as inputs for the subsequent estimation stages. For practical usage of the preliminary estimation method, a semistructured business process is proposed.

METHODOLOGY FOR REDUCING THE RISKS OF CYBERSECURITY BREACHES AND PROTECTING INFORMATION FROM CYBER ATTACKS

The scientific article examines the problems associated with the risks of cybersecurity violations and information protection from cyber attacks. Given the dramatically increased amounts of information transmitted over networks, the number of cyber attacks is simultaneously increasing, with the aim of stealing various kinds of secret and confidential information. At the same time, the role of specialists involved in the development and implementation of information system security technologies has increased.
 The article analyzes vulnerabilities in corporate systems and suggests methods for improving encryption protocols for users' personal data. Special attention is paid to the technologies for implementing protection mechanisms at the software development stage.

THE DEVELOPMENT OF A MOBILE APPLICATION ISMIND FOR FORMATIVE STUDENTS’ ASSESSMENT

Nowadays, mobile learning utilizing mobile applications has become widely adopted due to its flexibility and the numerous benefits it offers. However, the availability of mobile apps in education especially for assessment is limited and still an emerging topic despite the affirmation of its positive impact on students’ learning outcomes and motivation. The complexity of the mobile application development process, which includes requirement elicitation, modeling, designing, developing, testing, and evaluating, could be a contributing factor to this issue. This study aimed to propose a guideline for designing and developing an educational mobile application through the development of an application named IsMind that focuses on formative assessment. Evolutionary Prototyping, a methodology under the agile approach of Software Development Life Cycle (SDLC) was deployed to meet the educational application requirement by integrating content, pedagogy, and technology aspects to provide better teaching and learning material. The activities within each phase of evolutionary prototyping including the models, tools, techniques, and deliverables were discussed extensively. The analysis and design phase were done using an object-oriented approach with appropriate models (diagrams) to present the functional requirement of the mobile application. Various CASE tools which accelerated the development process in various stages of software development were explained.UMLet software was employed to create a use case diagram, activity diagram, and sequence diagram. The user interface design, which followed The Eight Golden Rules of Interface, was developed utilizing Marvel software. Adobe Photoshop CS6, Adobe Illustrator CS6, Unity 3D, and Microsoft Visual Studio Code (C#) were utilized in the development process. The mobile application provides a variety of question types, such as Drag And Drop, Multiple Choice, Numbering, True And False, Matching, and Puzzle. The evaluation of IsMind indicated its appropriateness as an interactive teaching and learning media for assessment. The proposed steps for constructing this assessment educational mobile app. The proposed methodology consists of the details of phases, various activities within each phase, techniques, models, and tools for each activity as well as deliverables of each phase offer a helpful guideline for anyone interested in developing a similar application.

Information System for Ukrainian Text Voiceover Based on Nlp and Machine Learning Methods

During the research, an information system for voicing Ukrainian-language text was developed based on NLP and machine learning methods. The created information system is implemented in the form of a desktop application, which allows the process of voicing the Ukrainian-language text. The created system included all stages of software development: the design process, the implementation process, and the testing process. For the feasibility of creating this system, already existing software solutions on the market were analysed, their advantages and disadvantages were listed, which were subsequently taken into account to create a new system. During the system analysis of the system, a goal tree, a decision tree, and examples of context diagrams with process decomposition are given. One of the stages of the design of the economic part, where the budget that will be spent on the implementation of the system is analysed, all tax and administrative costs are calculated, development strategies are also analysed and the development strategy of the existing product with accompanying solutions and the product development strategy are selected. After that, an assessment was made for the feasibility of creating the designed system, it’s payback and profit. The object of the research is the process of the voiceover system of the Ukrainian-language text based on NLP and machine learning methods. The subject of the research is the methods and means of the Ukrainian-language text voicing system process based on NLP and machine learning methods. The purpose of the research is to create an information system for voicing Ukrainian- language text based on NLP and machine learning methods. The result of the work is a ready-to- implement information system for voicing Ukrainian-language text based on NLP and machine learning methods, an analytical review of literary and online sources related to the topic of voicing Ukrainian- language text based on NLP and machine learning methods, a systematic analysis of the research object, analysis and selection of software tools for system implementation, practical implementation of the system, economic justification of system implementation activities.

Методы разработки защищенного программного обеспечения

This article is devoted to the issue of software protection based on the use of modern security methods. One of these methods is the introduction of procedures into the software system that should reduce the level of errors and the risks of vulnerability to the system and software. The key goal of the stage-by-stage implementation of the developed program is gradual detection of previously undetected errors and code defects. During this stage of software development both the customer and the executor may encounter a rather narrow range of errors related to partial data inconsistency when loading them into databases, as well as failures of program procedure execution due to the use of multi-user access. It is at this stage that the final picture of user interaction with the program is crystallized, and the degree of loyalty of the latter to the developed interface is also determined. If the output of the system to the design capacity after a number of modifications and improvements has occurred without any special complications, it means that the preliminary work on the project and the implementation of the previous stages of development were carried out correctly.

Methodology for testing and monitoring artificial intelligence-based software for medical diagnostics

BACKGROUND: The global amount of investment in companies developing artificial intelligence (AI)-based software technologies for medical diagnostics reached $80 million in 2016, rose to $152 million in 2017, and is expected to continue growing. While software manufacturing companies should comply with existing clinical, bioethical, legal, and methodological frameworks and standards, there is a lack of uniform national and international standards and protocols for testing and monitoring AI-based software.
 AIM: This objective of this study is to develop a universal methodology for testing and monitoring AI-based software for medical diagnostics, with the aim of improving its quality and implementing its integration into practical healthcare.
 MATERIALS AND METHODS: The research process involved an analytical phase in which a literature review was conducted on the PubMed and eLibrary databases. The practical stage included the approbation of the developed methodology within the framework of an experiment focused on the use of innovative technologies in the field of computer vision to analyze medical images and further application in the health care system of the city of Moscow.
 RESULTS: A methodology for testing and monitoring AI-based software for medical diagnostics has been developed, aimed at improving its quality and introducing it into practical healthcare. The methodology consists of seven stages: self-testing, functional testing, calibration testing, technological monitoring, clinical monitoring, feedback, and refinement.
 CONCLUSION: Distinctive features of the methodology include its cyclical stages of monitoring and software development, leading to continuous improvement of its quality, the presence of detailed requirements for the results of the software work, and the participation of doctors in software evaluation. The methodology will allow software developers to achieve significant outcomes and demonstrate achievements across various areas. It also empowers users to make informed and confident choices among software options that have passed an independent and comprehensive quality check.

Incorporating statistical and machine learning techniques into the optimization of correction factors for software development effort estimation

AbstractAccurate effort estimation is necessary for efficient management of software development projects, as it relates to human resource management. Ensemble methods, which employ multiple statistical and machine learning techniques, are more robust, reliable, and accurate effort estimation techniques. This study develops a stacking ensemble model based on optimization correction factors by integrating seven statistical and machine learning techniques (K‐nearest neighbor, random forest, support vector regression, multilayer perception, gradient boosting, linear regression, and decision tree). The grid search optimization method is used to obtain valid search ranges and optimal configuration values, allowing more accurate estimation. We conducted experiments to compare the proposed method with related methods, such as use case points‐based single methods, optimization correction factors‐based single methods, and ensemble methods. The estimation accuracies of the methods were evaluated using statistical tests and unbiased performance measures on a total of four datasets, thus demonstrating the effectiveness of the proposed method more clearly. The proposed method successfully maintained its estimation accuracy across the four experimental datasets and gave the best results in terms of the sum of squares errors, mean absolute error, root mean square error, mean balance relative error, mean inverted balance relative error, median of magnitude of relative error, and percentage of prediction (0.25). The p‐value for the t‐test showed that the proposed method is statistically superior to other methods in terms of estimation accuracy. The results show that the proposed method is a comprehensive approach for improving estimation accuracy and minimizing project risks in the early stages of software development.

Performance And Functional Testing With The Black Box Testing Method

Software testing is an essential stage in software development because it plays a role in maintaining the quality of the software produced. The objective of software testing is for verification and validation, namely ensuring that the software being developed works according to the expected functions when the software is designed. In addition to improving quality, the software being developed must also have minimal errors and test whether the software is feasible to use or not. This research employed the black box testing method. Black box technical testing was a test of the input or output functionality of the software. The research also described the testing model using automated testing, which was carried out by Apache JMeter tools on performance tests and Katalon Studio to functional tests on the Perbanas portal. The final results of this research depicted the test model from studying business processes, creating test scenarios for automated testing to analyzing the test results. The performance test results aimed to find out how much throughput (transactions per second) and Response Time are. Meanwhile, functional test results aimed to find out whether the expected functions and outputs were appropriate or not. The results of the performance test on the login feature that had been carried out, the best was taken, i.e., sample data that entered approximately 5000 samples for 250 users for a load test per 5 minutes; only 0.06% failed with an average of 15 transactions per second (TPS) by a maximum response time of 68 seconds and a minimum response time of 0.2 seconds. KEYWORDS: Apache JMeter, automation test, black box test, functional test, Katalon Studio, performance test

A New Industry 4.0 Approach for Development of Manufacturing Firms Based on DFSS

The adoption of Industry 4.0 is attracting manufacturing companies, but the implementation barriers they expect to face, such as huge investment costs, and lack of skilled workers and infrastructure, make many of them hesitate to go through with implementation. The lack of a standardization approach also adds more difficulties in the implementation of advanced key technologies. Based on the design for the six sigma (DFSS) method, a new decision-making and implementation approach (DM&I) is proposed to address some implementation barriers and provide strategic guidance to implement the Industry 4.0 advanced key technologies. In this study, a systematic literature review was conducted to determine the impact of the implementation barriers for Industry 4.0 adoption. The DM&I approach has been applied in a bearing ring production line as a real case. The proposed method consists of two steps: decision-making, which consists of the define phase in determining the exact system weak point in order to reduce the improvement risk and system operation disturbance; the evaluate phase, which is the determining of the level of use of key technologies; the visualize phase, which is the stage of designing and modeling the proposed system and creating the virtual environment to simulate the system in real-time in order to support the improved decision-making process and avoid the fear of high costs; and then the optimize phase, where the optimal level of use of key technologies is determined. Then, the implementation phase consists of the develop phase, which encompasses the stage of physical system construction and hardware software development, followed by the validate phase and the integrate phase. These phases support infrastructure improvement. However, the proposed approach can be used by manufacturing companies to improve production efficacy and competitiveness.

Model Sistem Penunjang Keputusan Untuk Pengelolaan Pembiayaan Nasabah Di BPR Sehat Sejahtera Universitas Pamulang

Abstract
 
 One of the BPRs that is currently developing in South Tangerang is BPR Sehat Sejahtera. BPR Sehat Sejahtera is part of the Pamulang University Sasmita Group, whose function as a bank is to channel financing to community businesses so that they are able to support the country's economy. To distribute financing, BPR managers are expected to be able to conduct financing analysis to reduce the risk of financing failure. Until now, financing analysis carried out by BPRs tends to be manual and requires quite a long time to make financing decisions. One method that can be used to assist in financing analysis is the credit scoring model. To facilitate decision making, an SPK was formed with a credit scoring model to provide several choices regarding customer financing applications. The DSS development process follows the traditional software development stages, namely: (1) planning, (2) analysis, (3) design and (4) implementation. SPK is developed using a spreadsheet model with a dialog display that supports user needs. The credit scoring model developed uses several methods, namely discriminant analysis, multiple linear regression, logistic regression, and decision trees. Each method will produce a different credit scoring model to be included in the SPK model base. The SPK prototype developed resulted in several financing analyzes according to the credit scoring model used. The prediction accuracy shown by credit scoring models ranges from 70% -80%. This method is capable of producing a model that provides a fairly high predictive accuracy. Meanwhile, the decision tree method is still not optimal in producing a credit scoring model.
 
 Keywords: financing analysis, discriminant analysis, BPR, credit scoring, decision tree, multiple linear regression, logistic regression, decision support system (DSS)

Cross-project clone consistent-defect prediction via transfer-learning method

Code clones are comparable code snippets that are introduced into software by developers in order to increase software development productivity. A change to code clone may result in a consistent-defect if the developers forget to verify the consistency of the code after the change. To reduce such change-related maintenance costs, researchers have proposed a number of methods for predicting clone consistency in advance. Unfortunately, the effectiveness of these cross-project models is unsatisfactory, and performing such predictions with insufficient data remains a challenge. Meanwhile, cross-project defect prediction via transfer learning method is prevalent in the software engineering community. Consequently, we first construct an empirical study to explore whether transfer-learning techniques could well be utilized for clone cross-project consistent-defect prediction in the initial stages of software development. In this paper, we employ transfer-learning techniques to predict clone consistency at both the time of clone creating and clone changing in order to avoid clone consistent-defects and maintenance. We conduct an experiment on open-source projects to evaluate the effectiveness of various transfer-learning methods. Our investigation demonstrates that transfer-learning techniques have a beneficial impact on predicting cross-project clone consistent-defect, and that the size of the dataset also has a positive effect on prediction. In order to promote software safety and security, we recommend that developers leverage transfer-learning to enhance the capability for clone cross-project consistent-defect prediction early in the software development phase.

Data-driven prototyping via natural-language-based GUI retrieval

Rapid GUI prototyping has evolved into a widely applied technique in early stages of software development to facilitate the clarification and refinement of requirements. Especially high-fidelity GUI prototyping has shown to enable productive discussions with customers and mitigate potential misunderstandings, however, the benefits of applying high-fidelity GUI prototypes are accompanied by the disadvantage of being expensive and time-consuming in development and requiring experience to create. In this work, we show RaWi, a data-driven GUI prototyping approach that effectively retrieves GUIs for reuse from a large-scale semi-automatically created GUI repository for mobile apps on the basis of Natural Language (NL) searches to facilitate GUI prototyping and improve its productivity by leveraging the vast GUI prototyping knowledge embodied in the repository. Retrieved GUIs can directly be reused and adapted in the graphical editor of RaWi. Moreover, we present a comprehensive evaluation methodology to enable (i) the systematic evaluation of NL-based GUI ranking methods through a novel high-quality gold standard and conduct an in-depth evaluation of traditional IR and state-of-the-art BERT-based models for GUI ranking, and (ii) the assessment of GUI prototyping productivity accompanied by an extensive user study in a practical GUI prototyping environment.

Development of Village Administration Data E-Monography Application

Utilization and processing of basic village data by the Kedungluk Village Government, Candi District, Sidoarjo Regency, through e-monograph is an effort by the village government to carry out a transformation process to develop an information culture. This study aims to determine the development and design of an application-based information system prototype (village monograph) that provides information and potential as well as village profiles, and provides convenience for village monograph data managers and users. In addition to providing benefits to the village government through the e-monograph application prototype, this research is also expected to contribute to learning in the State Administration Study Program by presenting a learning model that can provide opportunities for students to learn directly (become a laboratory) related to the use of information technology in designing and managing public sector organizations in accordance with the learning outcomes of the fourth study program. The research method used is the Research & Development (R&D) method where one of the models suitable for this research is the SDLC (Software Development Life Cycle) model and specifically the Waterfall model which consists of six stages of software development namely requirements, design, implementation, testing, deployment and maintenance. The output of this research is software or software.

ISO/IEC 25012-based methodology for managing data quality requirements in the development of information systems: Towards Data Quality by Design

Users should trust the data that are managed by software applications constituting the Information Systems (IS). This means that organizations should ensure an appropriate level of quality of the data they manage in their IS. Therefore, the requirement for the adequate level of quality of data to be managed by IS must be an essential requirement for every organization. In order to meet this requirement, some features and elements related to data quality (DQ) should be taken into account from the initial stages of software development, attending the “data quality by design” principle. The DQ concept is considered to be multidimensional and largely context dependent. For this reason, the management of specific requirements is a difficult task. Thus, the main objective of this paper is to present a methodology for Project Management of Data Quality Requirements Specification called DAQUAVORD aimed at eliciting DQ requirements arising from different users’ viewpoints. These specific requirements should serve as typical requirements, both functional and non-functional, at the time of the development of IS that takes Data Quality into account by default leading to smarter and collaborative development.

Quality Evaluation of Modern Code Reviews Through Intelligent Biometric Program Comprehension

Code review is an essential practice in software engineering to spot code defects in the early stages of software development. Modern code reviews (e.g., acceptance or rejection of pull requests with Git) have become less formal than classic Fagan's inspections, lightweight, and more reliant on individuals (i.e., reviewers). However, reviewers may encounter mentally demanding challenges during the code review, such as code comprehension difficulties or distractions that might affect the code review quality. This work proposes a novel approach that evaluates the quality of code reviews in terms of bug-finding effectiveness and provides the reviewers with a clear message of whether the review should be repeated, indicating the code regions that may not have been well-reviewed. The proposed approach utilizes biometric information collected from the reviewer during the review process using non-intrusive biofeedback devices (e.g., smartwatches). Biometric measures such as Heart Rate Variability (HRV) and task-evoked pupillary response are captured as a surrogate of the cognitive state of the reviewer (e.g., mental workload) and inexpensive desktop eye-trackers compatible with the software development settings. This work uses Artificial Intelligence techniques to predict the cognitive load from the extracted biomarkers and classify each code region according to a set of features. The final evaluation considers various factors such as code complexity, time of the code review, the experience level of the reviewer, and other factors. Our experimental results show the approach could predict the review quality with 87.77%±4.65 accuracy and a Spearman correlation coefficient of 0.85 (p-value < 0.001) between the predicted and the actual review performance. This evaluation validates the cognitive load measurement using electroencephalography (EEG) signals as ground truth for the HRV and pupil signals.

Generating the structural graph‐based model from a program source‐code using chaotic forrest optimization algorithm

AbstractOne of the most important and costly stages in software development is maintenance. Understanding the structure of software will make it easier to maintain it more efficiently. Clustering software modules is thought to be an effective reverse engineering technique for deriving structural models of software from source code. In software module clustering, the most essential objectives are to minimize connections between produced clusters, maximize internal connections within created clusters, and maximize clustering quality. Finding the appropriate software system clustering model is considered an NP‐complete task. The previously proposed approaches' key limitations are their low success rate, low stability, and poor modularization quality. In this paper, for optimal clustering of software modules, Chaotic based heuristic method using a forest optimization algorithm is proposed. The impact of chaos theory on the performance of the other SFLA‐GA and PSO‐GA has also been investigated. The results show that using the logistic chaos approach improves the performance of these methods in the software‐module clustering problem. The performance of chaotic based FOA, SFLA‐GA and PSO‐GA is superior to the other heuristic methods in terms of modularization quality and stability of the results.

A Defect Detection Method for the Primary Stage of Software Development

In the early stage of software development, a software requirements specification (SRS) is essential, and whether the requirements are clear and explicit is the key. However, due to various reasons, there may be a large number of misunderstandings. To generate high-quality software requirements specifications, numerous researchers have developed a variety of ways to improve the quality of SRS. In this paper, we propose a questions extraction method based on SRS elements decomposition, which evaluates the quality of SRS in the form of numerical indicators. The proposed method not only evaluates the quality of SRSs but also helps in the detection of defects, especially the description problem and omission defects in SRSs. To verify the effectiveness of the proposed method, we conducted a controlled experiment to compare the ability of checklist-based review (CBR) and the proposed method in the SRS review. The CBR is a classic method of reviewing SRS defects. After a lot of practice and improvement for a long time, CBR has excellent review ability in improving the quality of software requirements specifications. The experimental results with 40 graduate students majoring in software engineering confirmed the effectiveness and advantages of the proposed method. However, the shortcomings and deficiencies of the proposed method are also observed through the experiment. Furthermore, the proposed method has been tried out by engineers with practical work experience in software development industry and received good feedback.

Software for preventing maternal death due to hemorrhage

ABSTRACT: Introduction: Postpartum hemorrhage is the most common form of obstetric hemorrhage. Then, development technologies are very important to prevention and control the risk for this and the offer good care during the pregnancy, labor and puerperium. To show the development a software for the prevention and control of Maternal Death due to hemorrhage in the third period of delivery. Methods: The study was developed in three stages. In the first stage, a literature review was carried out on the risk factors for Postpartum Hemorrhage. In the second stage, was defined the actions for risk stratification and prevention of hemorrhage in the third period of delivery, which was validated for its content. In the third stage of software development, the items of problem recognition (project); implementation; computer tools for system development were followed. The state, behavior and use diagrams were used, respecting the technical specifications agreed with the computer professional. The Front-end was used in the angular language, the visual development and the markup language based on the Back-end in the node.js language. JavaScript was used to control browser functionality. For this research all ethical and legal procedures were complied. Results: The obstetric hemorrhage requires intervention with emphasis on: recognition of risk factors for intensified surveillance; adequate preparations for timely intervention; standardized approach to accurately define quantitative blood loss; systematic approach to identify the cause of hemorrhage; continuous surveillance for clinical findings suggestive or indicative of hypovolemia and also the adequate preparation of professionals. Discussion: The software is a support to identify obstetric complications, in addition to monitoring all risk factors of hemorrhage, in labor and in the puerperium. Provides theoretical and practical support for improving the quality of evidence-based clinical practice, reducing gaps and weaknesses in assistance due to the identification of actions according to the level of risk demanded

On the Technologies of Decentralized Social Networks

The article analyzes modern centralized social networks, taking into account the existing shortcomings. A methodical approach to the development of a multiplatform decentralized social network using an interplanetary file system is proposed. Besides, a decentralized social network, an Ethereum smart contract, and a module for interacting with the interplanetary file system have been developed, a solution for the client side had been designed, a database and a local server have been configured. The ways to increase the speed of loading content are analyzed. To develop the client part of a decentralized social network, several popular frameworks have been proposed. Adapted life cycle models have been investigated, that is, ways to describe the stages of software development, depending on the characteristics of a particular project. Given the specifics of developing a multi-platform decentralized social network using IPFS, Agile is supposed to be the most appropriate life cycle model. An algorithm is proposed to calculate the computational and capacitive complexity of the system being developed. The calculation takes into account the main functions of the system components.