Software Development Expertise Research Articles

Reviewability and supportability: New complementary principles to empower research software practices

In today's scientific landscape, research software has evolved from being a supportive tool to becoming a fundamental driver of discovery, particularly in life sciences. Beyond its roots in software engineering, research software now plays a crucial role in facilitating efficient data analysis and enabling the exploration of complex natural phenomena. The advancements in simulations and modeling through research software have significantly accelerated the pace of scientific research while reducing associated costs. This growing reliance underscores the importance of software in ensuring reproducibility – a cornerstone of scientific rigor and trustworthiness. Although verifying reproducibility presents challenges, well-developed and openly accessible research software enhances transparency and aids in the early detection of errors. Although verifying reproducibility can be challenging, well-developed and accessible research software improves transparency and facilitates error detection. This mini-review examines the characteristics of research software and summarizes the key events that have shaped its development, alongside changes in requirements and guidelines. Moreover, we propose two additional principles – reviewability and supportability – complementing the widely accepted FAIR principles (Findability, Accessibility, Interoperability, and Reusability). These new principles aim to improve the efficiency and effectiveness of software evaluation during the peer review process. Through this review, we aim to assist scientists, especially those without extensive software development expertise, in understanding best practices for developing research software and the underlying motivations driving these practices.

Mobile health application for the treatment of urinary incontinence after radical prostatectomy: development and quality analysis.

To describe the development and quality analysis stages of a mobile health application for the treatment of urinary incontinence in men after radical prostatectomy. A technological development study. Eight clinical experts and eight software development experts participated in quality assessment. Six characteristics and 22 subcharacteristics were assessed using an online form. Agreement rates above 70% were considered satisfactory. The percentages of agreement of characteristics by clinical experts and developers were performance efficiency (90.5%), compatibility (100%) (both assessed only by the developers), functional suitability (78.5; 100%), usability (74.2; 82.7%), reliability (95.0; 82.3%) and security (87.6; 91.4%). Accessibility, user error protection, maturity and recoverability subcharacteristics showed agreement below 70%, which guided researchers to incorporate software improvements. The application presented satisfactory technical quality, configuring digital technological innovation that favors nursing care for men with urinary incontinence after radical prostatectomy.

Facilitators and Barriers in the Implementation of a Digital Surveillance and Outbreak Response System in Ghana Before and During the COVID-19 Pandemic: Qualitative Analysis of Stakeholder Interviews.

In the past 2 decades, many countries have recognized the use of electronic systems for disease surveillance and outbreak response as an important strategy for disease control and prevention. In low- and middle-income countries, the adoption of these electronic systems remains a priority and has attracted the support of global health players. However, the successful implementation and institutionalization of electronic systems in low- and middle-income countries have been challenged by the local capacity to absorb technologies, decisiveness and strength of leadership, implementation costs, workforce attitudes toward innovation, and organizational factors. In November 2019, Ghana piloted the Surveillance Outbreak Response Management and Analysis System (SORMAS) for routine surveillance and subsequently used it for the national COVID-19 response. This study aims to identify the facilitators of and barriers to the sustainable implementation and operation of SORMAS in Ghana. Between November 2021 and March 2022, we conducted a qualitative study among 22 resource persons representing different stakeholders involved in the implementation of SORMAS in Ghana. We interviewed study participants via telephone using in-depth interview guides developed consistent with the model of diffusion of innovations in health service organizations. We transcribed the interviews verbatim and performed independent validation of transcripts and pseudonymization. We performed deductive coding using 7 a priori categories: innovation, adopting health system, adoption and assimilation, diffusion and dissemination, outer context, institutionalization, and linkages among the aspects of implementation. We used MAXQDA Analytics Pro for transcription, coding, and analysis. The facilitators of SORMAS implementation included its coherent design consistent with the Integrated Disease Surveillance and Response system, adaptability to evolving local needs, relative advantages for task performance (eg, real-time reporting, generation of case-base data, improved data quality, mobile offline capability, and integration of laboratory procedures), intrinsic motivation of users, and a smartphone-savvy workforce. Other facilitators were its alignment with health system goals, dedicated national leadership, political endorsement, availability of in-country IT capacities, and financial and technical support from inventors and international development partners. The main barriers were unstable technical interoperability between SORMAS and existing health information systems, reliance on a private IT company for data hosting, unreliable internet connectivity, unstable national power supply, inadequate numbers and poor quality of data collection devices, and substantial dependence on external funding. The facilitators of and barriers to SORMAS implementation are multiple and interdependent. Important success conditions for implementation include enhanced scope and efficiency of task performance, strong technical and political stewardship, and a self-motivated workforce. Inadequate funding, limited IT infrastructure, and lack of software development expertise are mutually reinforcing barriers to implementation and progress to country ownership. Some barriers are external, relate to the overall national infrastructural development, and are not amenable even to unlimited project funding.

Leverage Artificial Immune Algorithm to Maintain Data Integrity

Abstract: Robust and efficient data security measures are of the utmost importance given the growing reliance on digital technologies. I recommend developing a simulated security testing platform using artificial immune algorithms to improve data security in response to the needs of the user. This software provides the capacity to simulate different cyber-attacks, making it easier to assess the efficacy of different safeguards. The platform may adapt to these attacks and learn from them by utilizing the strength of artificial immune mechanisms, increasing its resistance to threats in the future. I acquired beneficial expertise in software development, algorithm design, and data security as a result of my active participation in this project. I'm thrilled to share this study as a proof of my abilities and unwavering commitment to the data security area. The suggested approach makes use of Python-based machine learning techniques, and adds HTML, CSS, and JS for the user interface. The suggested approach also includes a user-friendly interface built using HTML, CSS, and JS, making it easier to integrate with present systems.

Evaluation of requirement engineering best practices for secure software development in GSD: An ISM analysis

AbstractTechnological advancement makes the world a global village. Security is an evergreen and everlasting area, because of the continuous threat from Hackers and Crackers. The immense use of software systems has modernized human society in every aspect. Thus, it is crucial to devise new processes, techniques, and tools to support teams in the development of secure code from the early stages of the software development process, while potentially reducing the costs and shortening the time to market. Considering the significance of software security, it is important to consider the security practices from the early phase of the software development life cycle (SDLC), that is, requirements engineering (RE). Hence, this study aims to identify and categorize RE practices important to apply for secure software development (SSD) in a geographically distributed development environment. To study the RE practices concerning SSD, we conducted a questionnaire survey with industrial experts in the global software development (GSD) context.Furthermore, the interpretive structure modeling (ISM) approach was applied to evaluate the relationship between the RE security practice core categories. This paper identifies 70 practices and classifies them into 11 fundamental dimensions (categories) to assist GSD organizations in specifying the requirements for SSD. The ISM results show that the “Awareness of Secure Requirement Engineering (SRE)” category has the most decisive influence on the other 10 core categories of the identified RE security practices. With the help of empirical evidence and the ISM approach, this work attempts to identify potential security practices and to give a set of secure RE practices that can be used to improve the security of the software development process.

A Comprehensive, Affordable, Open-Source Hardware-Software Solution for Flexible Implementation of Complex Behaviors in Head-Fixed Mice.

Experiments that take advantage of head-fixed behavioral tasks have been a staple of systems neuroscience research for half a century. More recently, rodents came to the forefront of these efforts, primarily because of the rich experimental possibilities afforded by modern genetic tools. There is, however, a considerable barrier to entering this field, requiring expertise in engineering, hardware and software development, and significant time and financial commitment. Here, we present a comprehensive, open-source hardware and software solution to implement a head-fixed environment for rodent behaviors (HERBs). Our solution provides access to three frequently used experimental frameworks (two-alternative forced choice, Go-NoGo, or passive sensory stimulus presentation) in a single package. The required hardware can be built at a relatively low cost compared with commercially available solutions, from off-the-shelf components. Our graphical user interface-based software provides great experimental flexibility and requires no programming experience for either installation or use. Furthermore, an HERBs takes advantage of motorized components that allow the precise, temporal separation of behavioral phases (stimulus presentation, delays, response window and reward). Overall, we present a solution that will allow laboratories to join the growing community of systems neuroscience research at a substantially lower cost of entry.

Udo Krüger Charts TechnoTeam's Journey

Udo Krüger Charts TechnoTeam's Journey

Representation of an Interdisciplinary Approach for Evaluation of Precision of a Neurocognitive Screening Bundle: A Proposal

Neurocognitive disorders encompass a range of conditions characterized by cognitive impairments, presenting significant challenges to individuals, families, and healthcare systems worldwide. Traditional paper-and-pencil assessments have limitations, including restricted access, limited frequency, and subjective interpretation. This research proposal aims to address these limitations by developing a reliable digital platform, a neurocognitive screening bundle, for year-round monitoring of neurocognitive symptom domains. The proposed research project adopts an interdisciplinary approach by integrating knowledge and expertise from the fields of neurology, psychology, cognitive neuroscience, and computer science. Neurology provides clinical context and expertise in understanding neurocognitive symptom domains, ensuring that the chosen screening bundle aligns with clinical needs. Psychology contributes insights into human behavior and cognitive processes, aiding in the selection, adaptation, or development of assessments targeting specific neurocognitive functions. Additionally, psychologists contribute expertise in data analysis and interpretation, enabling the identification of meaningful patterns within the collected data. Cognitive neuroscience offers a deeper understanding of the underlying neural mechanisms associated with neurocognitive symptom domains. By identifying the neural networks, brain regions, and cognitive processes involved in specific cognitive functions, cognitive neuroscientists bridge the gap between cognitive assessment and neurobiological underpinnings, aiding in the selection and interpretation of neurocognitive measures. Computer science plays a pivotal role in developing and evaluating the digital platform for neurocognitive screening. Computer scientists leverage their expertise in software development, data analysis, and machine learning to design algorithms for data processing, ensure data security and privacy, and develop user-friendly interfaces for assessments. By integrating technical skills with knowledge from other disciplines, computer scientists enhance the accuracy, reliability, and usability of the digital platform. This interdisciplinary research project aims to provide a comprehensive, accessible, and reliable tool for year-round monitoring of neurocognitive symptom domains, surpassing the limitations of traditional assessment methods. By leveraging the expertise from neurology, psychology, cognitive neuroscience, and computer science, this study aims to advance the field and improve clinical outcomes for individuals with neurocognitive disorders. The findings of this research project have the potential to revolutionize neurocognitive assessments, leading to more effective diagnosis and monitoring of these challenging conditions.

Generating multiple conceptual models from behavior-driven development scenarios

Researchers have proposed that generating conceptual models automatically from user stories might be useful for agile software development. It is, however, unclear from the state-of-the-art what a consistent and complementary set of models to generate is, how these models can be generated such that relationships and dependencies in a set of related user stories are unveiled, and why these models are useful in agile software development projects. In this paper, we address these questions through a Design Science research study. First, we define four stylized versions of Unified Modeling Language (UML) diagrams (i.e., use case diagram, class diagram, activity diagram, state machine diagram) that will be the target of the model generation. Although these stylized UML diagrams have a reduced abstract syntax, they offer different perspectives on the software system in focus with potential usefulness for requirements and software engineering. Second, we develop an automated model generation approach based on different design artifacts including a Natural Language Processing (NLP) tool that implements our approach. Key to our solution is the use of the Behavior-Driven Development (BDD) scenario template to document user stories. Using an example set of BDD scenarios as source of the model generation, we demonstrate the feasibility of our approach via the NLP tool that implements our approach. Third, we conduct an empirical study with experts in agile software development involving the researcher-guided interactive use of our tool to explore the use of the generated models. This study shows the perceived usefulness of the models that our tool can generate and identifies different uses and benefits of the models for requirements analysis, system design, software implementation, and testing in projects that employ agile methods.

Assessing Soft Skills for Software Requirements Engineering Processes

Software requirement engineering (SRE) is the process of establishing, documenting, and maintaining software requirements. The goal of this research is to investigate the importance of soft skills in SRE. The data collection was performed through an online questionnaire. Descriptive statistics, principal components analysis (PCA), and stepwise regression techniques were used to analyze the data. A comprehensive review determined the 31 soft skills associated with SRE. There were 122 software development experts in Gaza who participated in the survey. The PCA analysis extracted six factors, named problem-solving, learning willingness, commitment, pressure resilience, critical thinking, and interpersonal skills. The analysis discovered that the level of SRE practice in Gaza is 73.71%. Furthermore, it was determined that 89.2% of respondents have critical thinking skills, and 85% have problem-solving and commitment skills. The result shows that all soft skills factors have strong links to SRE. However, only four soft skills (problem-solving, willingness to learn, pressure tolerance, and critical thinking) were found to have an impact on SRE. Considering these findings, we recommend focusing on the development of soft skills, especially problem-solving and willingness to learn skills, for the team analyzing software system requirements.

Design and Evaluation of a Choreography-Based Virtual Reality Authoring Tool for Experiential Learning in Industrial Training

The use of virtual reality (VR) for industrial training helps minimize risks and costs by allowing more frequent and varied use of experiential learning activities, leading to active and improved learning. However, creating VR training experiences is costly and time-consuming, requiring software development experts. Additionally, current authoring tools lack integration with existing data and are desktop-oriented, which detach the pedagogic process of creating the immersive experience from experiencing it in a situated context. In this article, we present a novel interactive approach for immersive authoring of VR-based experiential training by the trainers themselves, from inside the virtual environment and without the support of development experts. The design includes identifying interactable elements, such as 3-D models, equipment, tools, settings, and environment. The trainer also specifies by demonstration the actions to be performed by trainees, as a virtual choreography. During course execution, trainees’ activities are also registered as virtual choreographies and matched to those specified by the trainer. Thus, trainer and trainee are culturally situated within their area semantics and social discourse, rather than adopting concepts of the VR system for the learning content. We conducted a usability case study with professionals from an international wind energy company, using detailed models of wind turbines and real-world procedures. Trainers set up a training course using the immersive authoring tool, and trainees executed the course. The learning experience and usability were analyzed, and the training was certified by comparing real-world task completion between a user who had undergone virtual training and a user who did not.

Analyzing knowledge sharing behaviors in virtual teams: Practical evidence from digitalized workplaces

Software development is an intensely knowledge-intensive industry that demands collaboration on behalf of everyone who participates in the process. Moreover, the successful accomplishment of the process depends on knowledge sharing and acquisition among the stakeholders. For this reason, organizations must understand how the knowledge-sharing process unrolls among employees. Nowadays, geographical distance is unavoidable, so researchers must consider subjective distance. This study provides an analysis of knowledge-sharing behavior within employees in software development roles in virtual teams, namely functional and technical, having subjective distance in mind. A research model based on a literature review was proposed to understand different dimensions of knowledge sharing. Afterward, the research model was empirically tested based on data collected in an organization with expertise in ERP software development through the implementation of a questionnaire. The method used to analyze the data was PLS-SEM. Results suggest that individuals share knowledge mainly to fulfill intrinsic needs; however, organizational culture also plays an essential role in knowledge sharing. The results are fundamental for both academics and practitioners to acknowledge how knowledge sharing occurs and, consequently, help in the decision-making processes regarding Knowledge Management within the companies.

An open source toolkit for repurposing Illumina sequencing systems as versatile fluidics and imaging platforms

Fluorescence microscopy is a key method in the life sciences. State of the art -omics methods combine fluorescence microscopy with complex protocols to visualize tens to thousands of features in each of millions of pixels across samples. These -omics methods require precise control of temperature, reagent application, and image acquisition parameters during iterative chemistry and imaging cycles conducted over the course of days or weeks. Automated execution of such methods enables robust and reproducible data generation. However, few commercial solutions exist for temperature controlled, fluidics coupled fluorescence imaging, and implementation of bespoke instrumentation requires specialized engineering expertise. Here we present PySeq2500, an open source Python code base and flow cell design that converts the Illumina HiSeq 2500 instrument, comprising an epifluorescence microscope with integrated fluidics, into an open platform for programmable applications without need for specialized engineering or software development expertise. Customizable PySeq2500 protocols enable experimental designs involving simultaneous 4-channel image acquisition, temperature control, reagent exchange, stable positioning, and sample integrity over extended experiments. To demonstrate accessible automation of complex, multi-day workflows, we use the PySeq2500 system for unattended execution of iterative indirect immunofluorescence imaging (4i). Our automated 4i method uses off-the-shelf antibodies over multiple cycles of staining, imaging, and antibody elution to build highly multiplexed maps of cell types and pathological features in mouse and postmortem human spinal cord sections. Given the widespread availability of HiSeq 2500 platforms and the simplicity of the modifications required to repurpose these systems, PySeq2500 enables non-specialists to develop and implement state of the art fluidics coupled imaging methods in a widely available benchtop system.

No-code platform for time series prediction

Machine learning platforms that provide no-code capabilities allow for users to use machine learning without advanced domain knowledge or training. These tools enable those having no formal expertise in software development to create machine learning applications. Our analysis of existing no-code ML platforms reveals that most of them offer core ML, but not deep learning network models and can not be accessed for free. Therefore we have created a web-based application that allows researchers to experiment with machine learning solutions concerning time series prediction without the need for coding. This paper presents a case study demonstrating the operation of the platform.

How Software Quality Mediates the Impact of Intellectual Capital on Commercial Open-Source Software Company Success

The recent surge in the number of commercial open-source software (COSS) companies shows the growing importance of COSS companies in the software industry. As knowledge-based firms, COSS companies’ success depends heavily on the interplay among intangible resources such as human capital, relational capital, structural capital, and software quality. To observe these relationships, we conducted a hypothesis-testing questionnaire-type survey involving 200 software development experts and users working at 60 multinational COSS companies. Accordingly, the study unearthed two different but conjoint ways (i.e., direct and indirect) in which intellectual capital impacts COSS company’s success. On the one hand, relational capital one of the intellectual capital components directly affects COSS company success. One the other hand, relational and structural capital indirectly affect COSS company success through human capital, which, in turn, is itself mediated by software quality in a sequential mediation model. Therefore, COSS companies may need to prioritize software quality as it is the most critical variable impacting the success of COSS companies.

PRIORITIZED RISKS AND TREATMENT STRATEGIES IN GLOBAL SOFTWARE DEVELOPMENT (GSD)

The study conducts a review for the literature in order to compile the risks that are directly related to the GSD strategy. The case study adopts a Delphi methodology that allows the researcher to achieve consensus on the most relevant and critical risks associated with the GSD project. Twenty software development experts from all around the world participated in the study, with a minimum of fifteen expert in each Delphi round. The four rounds of the Delphi method used in this study are designed to gain consensus on the most crucial risks of the GSD strategy, as well as perform a risk assessment for all the risks compiled from the literature and verified by the participating experts. The results show that there are ten main risks that gained consensus by software development experts and need to be addressed as a priority in GSD projects, where all of them have medium to high probability of occurrence and impact on the software project success using a GSD strategy.

The effects of using the agile methodology as an instructional format for software development courses

The objective of traditional software development courses focuses on competencies in the programming languages and technical tools. Project methodologies and software development are typically taught as theory-driven and separate courses in Information Systems undergraduate programs. Rather than teaching project methodologies as secondary to the learning phase of software development, these methodologies can be actively incorporated into the software development course, applying the theoretical concepts in the classroom with the same tools used in the industry for product development. This research evaluates the effects of instituting the project methodology Agile as an active learning, instructional tool for a low-code software development course using the Mendix platform to give students hands-on learning of Agile while increasing their expertise in software development. The use of Agile in an instructional pedagogical approach enhanced student learning and prepared students with skills directly applicable in the industry. Future research could be applied to measure the Agile methodology as an instructional format for technical courses other than software development.

The Development of POTENSIA; The Android-Based Psychological Application for Mapping and Assessments of Student Mental Health During the COVID-19 Pandemic

<span lang="EN-US">Students experience various essential changes related to their psychological conditions during their education in college. Students' adaptability to the demands of these changes will give birth to new skills for the next stage of psychological development. However, academic stress, social problems, career, and personal-emotional problems can hinder the productivity and development of students in terms of mental health. This issue increased with the new-normal life during the COVID-19 pandemic, which also impacted the education process. For this reason, it is necessary to have a mobile-based online psychological assessment to map the mental health conditions of students during the pandemic. This study aims to develop and validate an Android-based online psychological assessment application to map students' mental health conditions. This study involved ten experts in counseling and software development, five counselors, and 638 users of the POTENSIA application. According to application development needs, data analysis using Aiken's V coefficient test, Confirmatory Factor Analysis (CFA), and Rasch Model Analysis. The results of the study prove that the application is considered valid and practical to use. The effectiveness of the application is considered very good in mapping the mental health conditions of students.</span>

Prediction of Risk Percentage in Software Projects by Training Machine Learning Classifiers

Recently, software project failures have been increasing due to lack of planning and budget constraints. In this regard, identifying the suitable software model with the consideration of risk factors is imperative. Therefore, this study investigates the key software models utilized in the industry through an interaction with software development experts and literature survey. In this study, 15 standard indicators were chosen where a survey was conducted through a questionnaire. The major performance metrics which were taken into consideration are network, security, software, machine learning, internet of things and application programming interface. We proposed a novel framework for the received dataset through questionnaire in which the machine learning classifiers were applied and risk predictions for each of the identified software models were accomplished. Using this outcome, software product managers can identify the appropriate software model according to the software requirements along with risk prediction percentage.

Content and usability validation of the Retire with Health web software.

to validate the content and usability of the Retire with Health web software. a methodological study. The content validation was carried out by seven experts in the aging subject, using an instrument that evaluated the objectives, contents, relevance, and the environment of the web software. Usability was validated by seven experts in software development, referring to ergonomics, functionality, usability, and efficiency. The data were submitted to statistical analysis, described by calculating the Content Validity Index. the global Content Validity Index found 0.97 for the usability aspects and 1.00 for the content. After incorporating all the experts' suggestions, the Retire with Health web software was made available on the internet (www.aposentarsecomsaude.com.br). content validation and usability showed that the web software meets the objective of supporting reflection on retirement, with a high level of agreement among experts.