Software Issues Research Articles

Nurses' experiences and teaching suggestions regarding electronic patient record systems: qualitative method study

AimThe study was conducted to determine nurses' experiences with electronic patient record systems and their suggestions for incorporating them into undergraduate nursing education. BackgroundThe integration of computers into healthcare represents one of the most significant developments of the 21st century. Understanding nursing professionals' experiences with electronic patient record systems and the innovations they seek in teaching can provide effective methods for training future users. DesignQualitative, cross-sectional, interpretive phenomenological design. MethodsThe study was conducted with 12 nurses. Data were collected through face-to-face interviews using semi-structured interview questions and analysed using content analysis. ResultsNurses' experiences were categorised into two main themes: using and teaching the Electronic Patient Record System. Participants reported difficulties related to inadequate physical infrastructure and software issues in the clinical setting. On the other hand, nurses acknowledged that electronic patient record systems enabled them to collect accurate, complete and traceable data, improved the quality of care and saved time for care. It was identified that nurses required training on these systems during their undergraduate education, especially learning from their colleagues. Participants suggested that teaching should involve the development of demo software. ConclusionsUsing electronic recording systems in hospitals enhances care management and facilitates documentation. Nurses recommend that students and practising nurses receive theoretical and practical training to adapt effectively to hospital systems. The development of demo software was proposed as a valuable educational tool.

Model-driven development for functional correctness of avionics systems: a verification framework for SysML specifications

AbstractCurrently, the most widespread software quality assurance methods in the avionics domain are semi-automated reviews and testing. However, their effort grows disproportionately to the size of the system under development. Also, these methods cannot achieve exhaustive coverage due to the complexity of today’s avionics systems and their potentially infinite set of combinations of possible inputs and system states. Furthermore, the later software issues are detected in the development process, the more expensive it is to fix them. To overcome these issues, a model-driven verification approach for modeling and analyzing avionics systems in early phases of the development is presented. To this end, semantics is given to SysML v2 models by a mapping to a theorem prover encoding. The development of a dedicated SysML v2 profile supporting event-driven data flow specifications, the encoding of corresponding structures in the theorem prover Isabelle, and a generator creating theorems from SysML v2 models are presented. The approach is evaluated by formally proving a representative liveness property of a hierarchical system model from the avionics domain. Since liveness properties can be negated only by infinite data sequences and thus cannot be covered exhaustively by testing, this case study demonstrates the added value for meeting typical safety requirements in the avionics domain. The results can be transferred from avionics to other domains, as well.

Gerontological Simulation Lab: Process Mapping a New Virtual Ward for the Nursing Home Liaison Service

Abstract Background Simulation-based training is an increasingly accepted way for multidisciplinary teams to learn together. Its use in geriatric departments around Ireland is increasingly visible. The application of simulation to pathway and process development however is less common. We decided therefore to deploy a simulation lab to test a new virtual ward platform for local nursing homes. Methods We developed, in partnership with a digital provider, a piece of software that could enable the efficient and safe operation of a virtual ward. Our simulation was conducted in two phases. Phase 1 involved bench simulation of the platform in order to identify any obvious software issues. Phase 2 involved the development of two simulated patient scenarios that would specifically test the operation of the pathway. Nursing staff from our local nursing homes and specialist MDT members from our own department were invited to the Sim lab in order to work through the developed scenarios. Results Bench simulation of the software during phase 1 identified three significant limitations to the software developed. These were resolved before progressing to phase II testing. The simulated scenarios at our lab worked well and participants shared positive feedback regarding the pathway and technology. They found the software easy to navigate, practical and agreed unanimously to its future use. There were further minor technical issues identified that have been fed back to the software company for resolution. The simulation facilitated training using the “live” system for both the staff at our nursing homes and our own team members. Conclusion The simulation lab proved to be an ideal environment for testing both our new virtual ward pathway and the digital technology developed for its enablement. It facilitated the creation of a comprehensive process map and ensures that all stakeholders had a clear understanding of the new pathway.

Assessing gender bias in the software used in computer science and software engineering education

Women are underrepresented in Computer Science (CS)/ Software Engineering (SE) and other technology related degrees. As undergraduates, they are also less likely to persist with CS/SE studies than men enrolled in those same courses. Gender correlated differences in personal characteristics, behaviour, and preferences mean that course design decisions may introduce unintended bias. To address this issue, we drew inspiration from the GenderMag method. GenderMag uses personas with evidence-based gender differences in problem-solving traits to detect usability issues in software. In this paper we investigate the personal qualities of CS and SE students, and how these influence their CS/SE learning journey. A series of persona development workshops were held to gather an extensive and unique qualitative dataset capturing the prior experiences, preferences, learning styles, motivations, goals, frustrations, and constraints of CS/SE students. Gender differences were used to construct preliminary male and female student personas. These personas were used in cognitive walkthroughs of software applications commonly used in education, and their performance compared to GenderMag’s Tim and Abi. While the student personas were less effective and lacked specificity compared to Abi, they were able to identify issues not detectable with GenderMag. Furthermore, the findings show the utility of persona development workshops as a data collection method and introduce a comprehensive list of CS/SE student qualities that may inspire future investigations.

“I would have to walk around to find the best Wi-Fi connection…”: qualitatively exploring challenges associated with rapid rollout of telehealth in Canadian long-term care homes

BackgroundEarly in the COVID-19 pandemic, long-term care (LTC) homes in British Columbia, Canada, restricted visitation to ensure the safety of their residents against transmission of the novel coronavirus. As such, these LTC homes had to quickly implement a rapid rollout of telehealth services to maintain physician care for residents while avoiding the infection risk of in-person visits amidst lockdown measures. The abrupt transition from traditional in-person physician care to telehealth presented significant challenges. Investigating these challenges is pivotal to the development of strategies for sustained telehealth use for physician services in LTC homes. This analysis is part of a broader qualitative, utilization-focused evaluation study of telehealth services rapidly implemented for physician care in LTC homes within the Fraser Health Authority region of British Columbia. The evaluation has aimed to consider integral factors such as telehealth challenges, facilitators, preferences, and continued use. Semi-structured interviews and focus groups were conducted with 70 physicians, staff, residents, and family caregivers across 27 different LTC homes in the region. All interviews and focus groups were transcribed verbatim and were analyzed using a thematic approach to identify common barriers surrounding the rapid rollout of telehealth in LTC across relevant groups.ResultsFrom the data, four challenges were identified: connectivity challenges (e.g., inconsistent or no Wi-Fi or cellular connectivity), device challenges (e.g., lack of accessible devices and software issues), privacy challenges (e.g., lack of private space to support telehealth use), and informational challenges (e.g., lack of electronic medical record access). All challenges posed barriers to telehealth access for both care provider and recipient groups in LTC settings.ConclusionsThe challenges identified in this analysis are supported by existing literature, which is significant given the different contexts within which such research has been undertaken. Collectively, this knowledge base can support evidence-informed improvements to telehealth for physician care in LTC settings. Future research should capture the perspectives of diverse cultural groups, LTC residents with cognitive impairments, and those who provide and receive care in rural settings.

A case report of system configuration issue in medical imaging due to system upgrade- changes in hardware and software.

Although the rapid growth in the efficiency of medical imaging is undeniable, the expansion of health information technology (HIT) into medical imaging has not been as seamless or well-integrated as it was thought to be. The socio-technical complexities in medical imaging associated with HIT systems can cause risks to patient harm and inconvenience, both individually and collectively, often in new, unforeseen, and unexpected ways. This study reflects a retrospectively collected single incident report related to medical imaging HIT systems, aiming to develop a set of preventive and corrective strategies. A combination of multiple deductive approaches (existing frameworks), i.e., HIT Classification Systems and 18-step medical imaging process workflow and inductive method (content analysis), were used to analyze the incident. The incident was identified as a "system configuration"-related software issue, contributed by system upgrade- changes in hardware and software. The incident was determined to occur during steps 10-12, i.e., "study selection and retrieval," "calling up of patient's referral," and "image review and interpretation," causing severe disruptions in the clinical workflow for several weeks. We propose 16 preventive and corrective strategies grouped under four key areas based on the socio-technical aspects associated with HIT systems. The key areas are (i) preparation and integration for upgraded systems, (ii) training for medical imaging specialists, (iii) contingency planning/immediate backup system, and (iv) system design and configuration. These strategies are expected to help healthcare staff, analysts, reporters, researchers, and relevant stakeholders improve care delivery and patient safety in medical imaging in the context of any system upgrades.

How Often Does Technology Fail in Robotic-Assisted Arthroplasty? A Comprehensive Analysis of a United States Food and Drug Administration Database

BackgroundRobotic-assisted arthroplasty is a growing alternative to conventionally instrumented arthroplasty; however, the incidence of adverse events (AEs) associated with this technology reported to the United States Food and Drug Administration (FDA) remains poorly quantified. The objective of this study was to categorize AEs associated with robotic-assisted arthroplasty and calculate their annual incidence as reported to the FDA. MethodsThe FDA’s Manufacturer and User Facility Device Experience database was queried for AEs from January 1, 2017 to December 31, 2021 associated with the most prevalent robotic-arthroplasty system. The AEs were calculated using national surgical numbers provided by the manufacturer and grouped by total hip arthroplasty (THA), total knee arthroplasty (TKA), or partial knee arthroplasty (PKA). ResultsThere were 1,710 unique AEs across the study period, with 436 THA, 1,005 TKA, and 269 PKA, representing incidence rates of 0.37, 0.30, and 0.40%, respectively. All procedures demonstrated lower rates of AEs in the final year of the study, compared to the first year. Most complications were related to mechanical problems, not software issues. Surgical delays due to AEs occurred in THA (0.13% cumulative incidence, 14.0 minutes average delay), TKA (0.13%, 20.6 minutes), and PKA (0.22%, 19.4 minutes). No cases were canceled due to AEs in THA, though a few TKA (0.003%) and PKA (0.02%) cases were not performed. Patient injuries occurred in 0.05, 0.05, and 0.08% of THA, TKA, and PKA, respectively. Surgical reintervention was necessary in 0.004, 0.003, and 0.01% of THA, TKA, and PKA, respectively. ConclusionsRobotic-assisted arthroplasty has a small number and relatively low rate of AEs reported to the FDA as measured through the Manufacturer and User Facility Device Experience database, with rates steadily decreasing over the study period. Patient injury, case delay, and reoperation represent only a small fraction of the already rare AEs in the database.

How do software practitioners perceive human-centric defects?

Context:Human-centric software design and development prioritises the way users prefer to complete their jobs, rather than expecting users to adapt to the software. Software users can have different genders, ages, cultures, languages, disabilities, socioeconomic statuses, and educational backgrounds, among many other differences. Due to the inherently varied nature of these differences and their impact on software usage, preferences and issues of users can vary, resulting in user-specific defects that we term as ‘human-centric defects’ (HCDs). Objective:This research aims to understand the perception and current management practices of such HCDs by software practitioners, identify key challenges in reporting, understanding and fixing them, and provide recommendations to improve HCDs management in software engineering. Methods:We conducted a survey and interviews with software engineering practitioners to gauge their knowledge and experience on HCDs and the defect tracking process. Results:We analysed fifty (50) survey- and ten (10) interview-responses from SE practitioners and identified that there are multiple gaps in the current management of HCDs in software engineering practice. There is a lack of awareness regarding human-centric aspects, causing them to be lost or under-appreciated during software development. Our results revealed that handling HCDs could be improved by following a better feedback process with end-users, a more descriptive taxonomy, and suitable automation. Conclusion:HCDs, given their diverse end-user base, present a major challenge to software practitioners. In the software engineering domain, research on HCDs has been limited and requires effort from research and practice communities to create awareness and support for human-centric aspects.

Improving VulRepair’s Perfect Prediction by Leveraging the LION Optimizer

In current software applications, numerous vulnerabilities may be present. Attackers attempt to exploit these vulnerabilities, leading to security breaches, unauthorized entry, data theft, or the incapacitation of computer systems. Instead of addressing software or hardware vulnerabilities at a later stage, it is better to address them immediately or during the development phase. Tools such as AIBugHunter provide solutions designed to tackle software issues by predicting, categorizing, and fixing coding vulnerabilities. Essentially, developers can see where their code is susceptible to attacks and obtain details about the nature and severity of these vulnerabilities. AIBugHunter incorporates VulRepair to detect and repair vulnerabilities. VulRepair currently predicts patches for vulnerable functions at 44%. To be truly effective, this number needs to be increased. This study examines VulRepair to see whether the 44% perfect prediction can be increased. VulRepair is based on T5 and uses both natural language and programming languages during its pretraining phase, along with byte pair encoding. T5 is a text-to-text transfer transformer model with an encoder and decoder as part of its neural network. It outperforms other models such as VRepair and CodeBERT. However, the hyperparameters may not be optimized due to the development of new optimizers. We reviewed a deep neural network (DNN) optimizer developed by Google in 2023. This optimizer, the Evolved Sign Momentum (LION), is available in PyTorch. We applied LION to VulRepair and tested its influence on the hyperparameters. After adjusting the hyperparameters, we obtained a 56% perfect prediction, which exceeds the value of the VulRepair report of 44%. This means that VulRepair can repair more vulnerabilities and avoid more attacks. As far as we know, our approach utilizing an alternative to AdamW, the standard optimizer, has not been previously applied to enhance VulRepair and similar models.

Leveraging lightweight blockchain for secure collaborative computing in UAV Ad-Hoc Networks

Unmanned Aerial Vehicle (UAV) Ad-Hoc Networks (UANET) enable collaborative work among UAVs for versatile task execution, but they face security challenges due to physical vulnerabilities, software issues, and dynamic wireless networks. This paper proposes a secure collaborative computing framework based on blockchain technology. Specifically, we first design a lightweight blockchain scheme suitable for UANET and present an improved Practical Byzantine Fault Tolerance (PBFT) consensus algorithm based on trust evaluation, aiming to reduce consensus overhead and establish trust relationships among UAVs. Furthermore, we devise a smart contract-based UAV task allocation strategy that considers both task execution efficiency and offloading security. This strategy enables UAVs to make optimal task-offloading decisions and facilitates collaborative computing according to smart contract rules. Simulation results demonstrate that our proposed consensus algorithm reduces average consensus latency by 47% and message count by 76% compared to PBFT-based algorithms. Additionally, the task allocation strategy decreases task costs by 48% compared to local computing strategies, achieving efficient and secure collaboration among UAVs in UANET. The real-world experiments with a UAV swarm further validate the efficiency and security of our framework, confirming its practical applicability in UANET.

Improving self-dependency in Pakistan: Experience of a locally prepared automated PD machine.

The increasing burden of haemodialysis on healthcare systems merits efforts to make peritoneal dialysis (PD) more accessible to the population in need of kidney replacement therapy. Automated PD (APD) may be a suitable alternative to continuous ambulatory peritoneal dialysis for home dialysis especially for children, elderly and patients who lead a busy schedule in their jobs thus leaving more time for personal and family activities during the day. Recently, a local bioengineering company took the initiative to develop a locally manufactured, low-cost APD cycler in Pakistan, with an aim to improve the self-dependency and home-based kidney replacement therapy. We herein present our first experience of APD on this locally manufactured APD cycler. It was an investigator-led study on the utility of a locally manufactured APD cycler and the safety and efficacy of the standard operating procedures developed and adopted by the study authors. A total of eight patients agreed to participate in this study extending from September 2021 to August 2022. There were four male and four female patients, and the mean age was 52.5 + 19.71 years. The locally manufactured cycler provided more than 1600 h of APD sessions. The APD sessions were well tolerated with only a few instances of minor mechanical and software issues that did not require termination of therapy. There were no episodes of peritonitis; however, one of the patients had an episode of exit site and tunnel infection that did not seem to be related to the procedure. Our experience with locally manufactured APD cycler was successful and without major adverse events. We believe the locally produced APD cycler is a viable cost-effective option for patients requiring PD and may herald a new era of self-dependency for patients considering or undergoing PD in Pakistan.

Application of GIS and Artificial Intelligence in Military Operations: Prospects and Challenges

Geographic Information System (GIS) and Remote Sensing have been considered significant in the military due to their spatiality in nature. Recent military developments have seen various military institutions depending on spatial mapping tools, for the purpose of command, control, communication and coordination in military operations. In this study, the qualitativeanalytical method was used to illustrate the applications of GIS in military operations, drawing lessons from land based military developments from selected studies. An online survey was conducted to extract information from a sample of forty (40) students undertaking War Studies at the University of Zimbabwe, who were conveniently selected for the study. In-depth interviews were also done with two (2) military experts from the university. Data collected was analyzed using descriptive statistics and qualitative interpretation of recent developments in military GIS. The benefits of GIS and machine learning in military operations included access to information; improved data management; information dissemination; improved terrain analysis; object, target or pattern recognition; quick data processing algorithms; autonomous systems; and predictive analysis. The study also notes some challenges associated with GIS and machine learning in military operations include expensive to set up which constituted of respondents; training requirements; cyber-security; software issues; offensive in nature, as well as misinterpretation of situations. The study recommends the need for human-AI collaboration and the development of a regulatory framework at national, regional and international level in ensuring sustainable implementation of GIS technology in military operations.

Analysing the Impact of Simulation-Based Design Processes on Structural Performance Optimization: A Research Inquiry

With the recent advancement of several technologies and software, the simulation-based design processes for optimizing the structural strength of various erections have become very effortless. This software is an advanced version of the human mind possessed to have solutions for complex problems in real-time. However, this software lacks the creativity, broader understanding, and intuition that characterize the human mind. This paper is a research study on some computer-aided software and their efficiency in finding the structural strength of complex residential buildings. This software reduces the need for time-consuming and costly physical testing. This paper also gives compiled information about issues of simulation software, trends in optimization studies, and the effectiveness of these tools. Factors such as model simplification, material property calibration, and validation against real-world performance data are critically processed to ensure the reliability and applicability of the proposed design solutions. In addition to these, this paper is composed of a holistic approach to structural optimization with a Building Information Modelling platform within the context of the entire building lifecycle. Emphasizing sustainability and environmental considerations, the study examines how simulation-based design processes can contribute to reducing energy consumption, minimizing environmental impact, and achieving compliance with green building standards. Primarily this research inquiry provides insights and recommendations that can inform the development of best practices for optimizing the structural strength of complex residential buildings.

Analysis of the Impact of Cybersecurity on The Stability of Financial Institutions

The issue of the impact of cybersecurity is a top priority for the functioning of a financial institution. Therefore, its provision becomes a priority in organizing the further activities of the institution itself. The article aims to analyze the current trends in ensuring the cybersecurity of financial institutions and its role in their functioning. The paper describes the theoretical foundations of the cyber protection concept. The authors also outline the specifics of cybersecurity and the leading technological solutions for achieving these goals. Special attention is paid to modern, innovative solutions to maintain the stability of financial institutions and the possibility of further development. An important area of research is the disclosure of the practical experience of information corporations in providing technical solutions to ensure the security of financial transactions and support the global financial system. The study presents the experience of Ukrainian financial institutions that use variable digital defense strategies and maintain their functionality based on an effective cybersecurity system in the context of a global military conflict. The results of the study include a detailed profile of effective practical solutions to ensure the stability of financial institutions based on the implementation of blockchain technologies. The authors pay attention to the issue of modern software, hardware, and management solutions to improve the quality of cybersecurity in the context of growing cyberattacks and digital threats to the stability of financial institutions. The research findings may be helpful for further analytical studies on the effectiveness of cybersecurity and the stability of financial institutions.

Developing a Cost-Effective Surgical Scheduling System Applying Lean Thinking and Toyota's Methods for Surgery-Related Big Data for Improved Data Use in Hospitals: User-Centered Design Approach.

Surgical scheduling is pivotal in managing daily surgical sequences, impacting patient experience and hospital resources significantly. With operating rooms costing approximately US $36 per minute, efficient scheduling is vital. However, global practices in surgical scheduling vary, largely due to challenges in predicting individual surgeon times for diverse patient conditions. Inspired by the Toyota Production System's efficiency in addressing similar logistical challenges, we applied its principles as detailed in the book "Lean Thinking" by Womack and Jones, which identifies processes that do not meet customer needs as wasteful. This insight is critical in health care, where waste can compromise patient safety and medical quality. This study aims to use lean thinking and Toyota methods to develop a more efficient surgical scheduling system that better aligns with user needs without additional financial burdens. We implemented the 5 principles of the Toyota system: specifying value, identifying the value stream, enabling flow, establishing pull, and pursuing perfection. Value was defined in terms of meeting the customer's needs, which in this context involved developing a responsive and efficient scheduling system. Our approach included 2 subsystems: one handling presurgery patient data and another for intraoperative and postoperative data. We identified inefficiencies in the presurgery data subsystem and responded by creating a comprehensive value stream map of the surgical process. We developed 2 Excel (Microsoft Corporation) macros using Visual Basic for Applications. The first calculated average surgery times from intra- or postoperative historic data, while the second estimated surgery durations and generated concise, visually engaging scheduling reports from presurgery data. We assessed the effectiveness of the new system by comparing task completion times and user satisfaction between the old and new systems. The implementation of the revised scheduling system significantly reduced the overall scheduling time from 301 seconds to 261 seconds (P=.02), with significant time reductions in the revised process from 99 seconds to 62 seconds (P<.001). Despite these improvements, approximately 21% of nurses preferred the older system for its familiarity. The new system protects patient data privacy and streamlines schedule dissemination through a secure LINE group (LY Corp), ensuring seamless flow. The design of the system allows for real-time updates and has been effectively monitoring surgical durations daily for over 3 years. The "pull" principle was demonstrated when an unplanned software issue prompted immediate, user-led troubleshooting, enhancing system reliability. Continuous improvement efforts are ongoing, except for the preoperative patient confirmation step, which requires further enhancement to ensure optimal patient safety. Lean principles and Toyota's methods, combined with computer programming, can revitalize surgical scheduling processes. They offer effective solutions for surgical scheduling challenges and enable the creation of a novel surgical scheduling system without incurring additional costs.

Automated continuous rhythm monitoring with implantable cardiac monitor and real-time smartphone alerts during af episodes: SMART-ALERT study

Abstract Introduction The 'Pill-in-the-pocket' oral anticoagulation (OAC) strategy is based upon the concept of dynamic thromboembolic risk which increases during and shortly after an atrial fibrillation (AF) episode. Limiting OAC use in low-risk patients with infrequent AF may offer comparable stroke protection and reduce bleeding. However, this approach relies on precise continuous rhythm monitoring with real-time alerts to patients. LINQ II implantable cardiac monitor transmits regularly to Carelink via smartphone app, but lacks patient alerts. To address this limitation, we developed bespoke software that triages transmissions in Carelink and sends alerts via SMS to patients. Purpose This feasibility study evaluates the precision of the LINQ II in detecting AF and assesses the efficacy of bespoke software in delivering 'real-time' SMS alerts to participants' smartphones, and measures compliance with these alerts. Methods In this single-center feasibility study, individuals with frequent AF episodes underwent LINQII implantation. The bespoke software, operating in the cloud, systematically reviewed all Carelink transmissions at 5-min intervals. SMS alerts were triggered based on specific criteria: 1)AF &amp;gt;30 min; 2)only the initial AF episode &amp;gt;30 min within a 24h period was transmitted; and 3)AF episodes uploaded or detected after a 24h delay were disregarded. Participants confirmed receipt of the alert by responding to the SMS, and timestamps for these interactions were recorded in a database (Fig. 1). Results A total of 50 patients were prospectively enrolled, and LINQ II was implanted. The median age was 49 years, 62% male, 90% had paroxysmal AF. Over a 3-month mean follow-up, 4080 AF episodes &amp;gt;30 min occurred in 32 patients. Among these, 700 met the criteria for triggering an alert, with 72.14% sent to patients within 24 h. Alerts were not transmitted for 3 main reasons: smartphone failure to transmit to Carelink within a 24 h period, software issues connecting to Carelink (website maintenance), and updates in the webservers. The median time from an AF episode to the transmission of SMS alerts was 2.47 h, with 85.54% of alerts being sent within 12 hours. Once an SMS was sent, the median time for acknowledgment was 4.3 min. The median time from an AF episode to acknowledgment was 4.23 h (Fig. 2). Notably, 97.62% of episodes were acknowledged within 24 hours. Patients failed to acknowledge an SMS alert on only 3 occasions. Conclusions Safely delivering 'pill-in-the-pocket' OAC requires a closed-loop system where devices provide real-time alerts during during AF , thus minimising delays in initiating OAC. This feasibility study establishes that the integration of bespoke software with LINQ II exhibits promising efficacy with a high percentage of SMS alerts within 24 hours, exceptional patient compliance, and a median response time of only 4.3 min. Nonetheless, further efforts are needed for seamless integration with Carelink to enhance connectivity.

Defect Prediction via Tree-Based Encoding with Hybrid Granularity for Software Sustainability

Defects in software may result in system crashes, sluggish performance, or even deadlock, leading to the depletion of valuable resources. Implementing defect prediction can assist quality assurance teams in identifying potential software issues and rationalizing the allocation of testing resources, thereby decreasing the elimination of resources and enhancing software sustainability. Researchers have recently incorporated deep learning into defect prediction, extracting structural-semantic features from codes' abstract syntax trees (ASTs). However, inappropriate node granularity in ASTs may adversely impact the effectiveness of the extracted features. In addition, converting AST nodes into integer vectors may lead to the loss of structure information, resulting in poor model predictive capability. This paper proposes a tree-based encoding method with hybrid granularity for defect prediction to address these challenges. Specifically, five granularity selection schemes are extended to generate various ASTs from codes. Subsequently, a tree-based continuous bag-of-words model is utilized to map nodes of ASTs into numeric vector representations that conform to the tree-like structure of codes. The matrices converted from ASTs are then fed into a convolutional neural network to extract program features automatically. Experiments involving 24 versions of open-source projects demonstrate that our method can improve the effectiveness of extracted features in defect prediction tasks.

Conversation in forums: How software forum posts discuss potential development insights

User feedback on software usage is utilised by developers to improve their software. Software product forums are platforms rich in software-related user feedback, such as forum threads containing bug reports or requests for new features. However, previous studies have mainly focused on analysing user feedback from software product forums as individual sentences, which can lead to missing insights and a lack of understanding of the overall context of forum posts. To fill this gap in research, this work examines user feedback found in software product forum posts to investigate the differences between content classifications found in forum sentences and posts. We manually evaluated software product forum posts collected from two open-sourced software product forums and discovered five new types of user feedback that can only be identified when examining user feedback in the form of forum posts. Additionally, we examined the association between sentence classifications found within software product forums. Our results indicate that contextual information complimenting product improvement insights can be found in software product forums, with a confidence of 0.75 and 0.69 for the association between apparent bug and application usage sentences. This information can be used to reduce manual efforts required to chase up missing contextual information when attempting to understand or fix software issues. We also provide insights into the progression of posts in software product forums at the thread-level, and our progression flowchart can be used to summarise the sequence of events in software product forum threads. Our findings reveal the importance of looking at user feedback within software product forums in the format of forum posts to identify new insights on user feedback for software improvements.Editor’s note: Open Science material was validated by the Journal of Systems and Software Open Science Board.

Analysis of the Impact of Cybersecurity on the Stability of Financial Institutions

"The issue of the impact of cybersecurity is a top priority for the functioning of a financial institution. Therefore, its provision becomes a priority in organizing the further activities of the institution itself. The article aims to analyze the current trends in ensuring the cybersecurity of financial institutions and its role in their functioning. The paper describes the theoretical foundations of the cyber protection concept. The authors also outline the specifics of cybersecurity and the leading technological solutions for achieving these goals. Special attention is paid to modern, innovative solutions to maintain the stability of financial institutions and the possibility of further development. An important area of research is the disclosure of the practical experience of information corporations in providing technical solutions to ensure the security of financial transactions and support the global financial system. The study presents the experience of Ukrainian financial institutions that use variable digital defense strategies and maintain their functionality based on an effective cybersecurity system in the context of a global military conflict. The results of the study include a detailed profile of effective practical solutions to ensure the stability of financial institutions based on the implementation of blockchain technologies. The authors pay attention to the issue of modern software, hardware, and management solutions to improve the quality of cybersecurity in the context of growing cyberattacks and digital threats to the stability of financial institutions. The research findings may be helpful for further analytical studies on the effectiveness of cybersecurity and the stability of financial institutions."

Improving the quality of software issue report descriptions in Turkish: An industrial case study at Softtech

Improving the quality of software issue report descriptions in Turkish: An industrial case study at Softtech