Program Analysis Research Articles

Australia’s jurisdiction and law enforcement in combating IUU fishing in the Southern Ocean

Australia used to be an active law enforcer in the Southern Ocean in the 2000s and manifested its fulfillment of multiple roles and duties in exercising jurisdictions effectively to deter the Illegal, Unreported and Unregulated (IUU) fishing in this region. This paper provides an updated review of Australia’s maritime enforcement against IUU fishing. Australia’s approach to combating IUU fishing in the Southern waters has been reflected in its legislation, institutional arrangements, as well as judicial cases. This paper examines international and national laws relevant to Australia’s jurisdictions in the Southern Ocean, as well as critically reviews Australia’s institutional arrangements and availability of military resources in maritime enforcement. A analysis of enforcement programs and judicial practices is also provided by this paper.

Improving Robustness in IoT Malware Detection through Execution Order Analysis

The rapid expansion of the Internet of Things (IoT) has significantly increased the prevalence of malware targeting IoT devices. Although machine learning models offer promising solutions for automatic malware detection, they are increasingly vulnerable to adversarial attacks. These attacks exploit the model’s feedback loop to iteratively refine malware, producing adversarial samples that evade detection. As such, enhancing the robustness of these models is of paramount importance. Our research introduces a novel approach to bolster malware detection by retaining additional semantic information within the execution order analysis of malware programs. The method significantly improves the resilience of detection models against adversarial samples and implements two adversarial attack methods to rigorously test our model’s robustness by generating authentic adversarial examples for validation. We highlight the critical impact of preserving semantic integrity in malware detection and present a solution to counteract the growing threat of adversarial attacks in IoT environments.

Integrating Behavioural Economics into Skill Development

Abstract The contemporary economic scenario, characterized by modern technology and global relationships, demands a workforce equipped with both traditional economic knowledge and modern skills. This research explores the evolving trends in economics skill development, focusing on how educational institutions are adapting their curricula to meet these emerging demands. Traditional lecture-based methods, as criticized by early scholars like Becker and Watts, are increasingly being replaced by interactive, student-centred methodologies that foster critical thinking and problem-solving abilities. The integration of digital tools and data analytics into economics education, highlighted by McGoldrick and Peterson, reveals the broader shift toward data-driven decision-making in the global economy. Furthermore, the integration of behavioural economics, data science, and other interdisciplinary fields, enhancing students' ability to apply economic concepts to real-world experiments. This research employs a diverse-methods approach, combining surveys of educators and students with content analysis of current economics programs, to identify key trends in skill development. This study reveals a strong emphasis on data analysis skills, the integration of interdisciplinary content, and the adoption of experiential learning methods such as internships and case studies. These shifts specify a move away from traditional theory to practical, applied learning experiences enhance the students to meet demands of the modern economy. The study concludes with recommendations for better investment in educational resources, and an increased focus on experiential learning. By adapting these trends, economics education can continue to produce professionals capable of navigating the people towards global economy.

Effectiveness of Live Webinars to Teach Financial Literacy: A Case Study Among Public Employees

In the wake of economic downturns, a global pandemic, and changes to work-based benefits, the need for financial education is evident as adults continue to show low levels of financial literacy. To address these issues, a financial wellness program for working adults consisting of six 1-hour webinars taught by area experts and business professionals was created among public employees in Nebraska, the United States. The sample for this case study program analysis includes 424 participants who participated in all six live webinars and completed both a pre- and post-assessment of financial knowledge, behavior, and attitudinal questions. An estimatedttest showed an 11-percentage point increase from pre- to post-assessment on the knowledge questions. Additionally, participants reported positive changes in attitude regarding their finances. Regression results showed that individuals with the lowest income benefited the most, answering 1.8117–2.1176 more questions correctly, suggesting that the webinars were especially beneficial for people who might be struggling the most financially. The positive findings from this study show that impactful financial education can be delivered online via live webinar format. This is useful for providers who develop and plan financial literacy programs for adults.

Universal Basic Income: Inspecting the Mechanisms

Abstract We examine the mechanisms driving the aggregate and distributional impacts of Universal Basic Income (UBI) through model analysis of various UBI programs and financing schemes. The main adverse effect is the distortionary tax increase to fund UBI, reducing labor force participation. Secondary channels are a decline in demand for self-insurance, depressing aggregate capital, and a positive income effect that further deters labor force participation. Due to these channels, introducing UBI alongside existing social programs reduces output and average welfare. Partially substituting existing programs with UBI mitigates the adverse effects, increases average welfare, but does not deliver a Pareto improvement.

A Combined Approach of Program Analysis and Deep Learning for Code Completion

A Combined Approach of Program Analysis and Deep Learning for Code Completion

Ukrainian agriculture in times of war: Analysis of support programmes

Ukrainian agriculture in times of war: Analysis of support programmes

Analysis of The Professional Development Program of General Foundation Course Teachers In Higher Vocational Colleges in China:Basis for The Teacher Professional Development Framework

Higher vocational education in China plays a vital role in national economic development by preparing a skilled workforce. General Foundation Courses (GFC) are crucial in this system, providing essential skills in mathematics, language, and basic sciences, yet they often receive less attention and fewer resources compared to specialized courses. This disparity leads to outdated teaching methods and insufficient professional development for GFC teachers. Professional Development Programs (PDPs) aim to address these issues, but their effectiveness needs thorough evaluation. This study assesses the current state of PDPs for GFC teachers in China's higher vocational colleges, identifying challenges and proposing a comprehensive framework for improvement. Using qualitative research methods, including semi-structured interviews with 12 GFC teachers and document analysis, the study highlights the importance of institutional support, relevance of training programs, and continuous professional development. Findings suggest that increased resources, customized PDPs, and ongoing professional growth opportunities are crucial for enhancing teaching practices and student outcomes. The study's implications underscore the need for policymakers and educational administrators to prioritize resource allocation, design tailored PDPs, and promote continuous learning to improve the quality of vocational education and contribute valuable insights to the literature on teacher professional development.

Investigating the Effectiveness of Using Corpus-Based Developed Materials in Vocabulary Learning for Saudi EFL Students

Many studies have employed corpus linguistics methodologies to gain insights into L2 learning and teaching. While these studies have contributed to a comprehensive theoretical understanding of corpus use in L2 instruction, particularly in vocabulary learning, there remains a gap in practical application, especially within the context of English as a Foreign/Second Language (EFL/ESL). Therefore, this paper empirically examined the effectiveness of using the corpus approach for EFL students’ vocabulary development and explored students’ attitudes toward using a corpus to develop their vocabulary. In a five-week experimental study, involving 24 Saudi EFL female students, participants were evenly divided into two groups: the control and experimental groups. These objectives were investigated using a mixed-method design, comprising both quantitative and qualitative approaches, which included pretests, posttests, questionnaires, and diaries for the experimental group only. Data were statistically analyzed using the SPSS program (v.25), incorporating T-tests and descriptive statistical analysis, alongside a descriptive analysis of learners’ diaries to corroborate the questionnaire findings. The findings showed that both groups revealed improved vocabulary during the study period based on the post-test results, but favored the experimental group that received the corpus-based approach. Furthermore, the attitudes questionnaire’s results showed most students held positive attitudes toward using the COCA corpus for vocabulary learning, despite facing some difficulties, which, as described in their weekly diaries, could be overcome over time through practice and training.

Analysis of the Youth Posyandu Program and Family Assistance Team in Efforts to Reduce Stunting in Tayu District, Pati Regency

Education is held to equip the community, especially the less fortunate, with the ability to maintain health that can be used to improve their quality of life. This case study research was conducted to analyze the Youth Posyandu and Family Assistance Team programs and to examine the impact of the implementation of the program. The research conducted in Tayu District, Pati Regency from September to November 2023 is a qualitative research. Data collection was carried out by the researcher himself as a research instrument using interview, observation, and documentation guidelines. Data analysis was carried out using qualitative data analysis techniques. To achieve data validity, triangulation and observation extension were carried out. The results of the study showed that there was a positive impact on the target group, although it was still at the individual level. Therefore, the Youth Posyandu and Family Assistance Team that will be developed need to emphasize their sustainability and accountability in community empowerment efforts. Keywords: program analysis, youth posyandu, family assistance team, non-formal education, impact

Online courses for adults: do they replace or supplement on-site courses?

ABSTRACT The COVID-19 pandemic led to a marked increase in the number of online courses in adult education. However, such courses are viewed ambivalently because, on one hand, they are associated with digitalisation processes and an increased accessibility, reach, and flexibility of learning opportunities, whereas, on the other hand, there are concerns about acceptance issues and participation barriers. Given this context, the present study examines whether new online courses for adults have supplemented or replaced existing on-site courses by conducting a program analysis of online courses at public adult education centres (Volkshochschulen, VHS) in Germany. VHS are the largest providers of adult education in the country. A comparison of programs from the years 2018, 2019 (pre-pandemic), and 2024 (post-pandemic) shows that most online courses supplement the existing program, and that the content of approximately every second online course can also be learned on-site at the educational centre. In contrast, 29 per cent of online courses have replaced an earlier on-site course. Hybrid courses, which enable both online and offline learning, are rare. Results are discussed along with their implications for adult education centres and adult learners.

Story of Your Lazy Function’s Life: A Bidirectional Demand Semantics for Mechanized Cost Analysis of Lazy Programs

Lazy evaluation is a powerful tool that enables better compositionality and potentially better performance in functional programming, but it is challenging to analyze its computation cost. Existing works either require manually annotating sharing, or rely on separation logic to reason about heaps of mutable cells. In this paper, we propose a bidirectional demand semantics that allows for extrinsic reasoning about the computation cost of lazy programs without relying on special program logics. To show the effectiveness of our approach, we apply the demand semantics to a variety of case studies including insertion sort, selection sort, Okasaki's banker's queue, and the implicit queue. We formally prove that the banker's queue and the implicit queue are both amortized and persistent using the Rocq Prover (formerly known as Coq). We also propose the reverse physicist's method, a novel variant of the classical physicist's method, which enables mechanized, modular and compositional reasoning about amortization and persistence with the demand semantics.

Deriving with Derivatives: Optimizing Incremental Fixpoints for Higher-Order Flow Analysis

At the heart of efficient program analysis implementations are incremental solutions to fixpoint problems. These solutions can be interpreted as the derivative of the underlying analysis function. Methods that describe how to systematically derive higher-order analyses from program semantics, such as Abstracting Abstract Machines, don’t shed light on how to efficiently implement those analyses. In this paper, we explore complementary techniques to optimize the derivative computation towards deriving efficient implementations. In particular, we use static specializations (by partial evaluation and rewriting) and dynamic specializations (in the form of tracking dependencies during the fixpoint), yielding efficient incremental fixpoints. We present how these optimizations apply to an example analysis of continuation-passing-style λ-calculus, and describe how they pair particularly well with tunable and optimized workset-based fixpoint methods. We demonstrate the efficacy of this approach on a flow analysis for the Standard ML language, yielding an average speed-up of 56x over an existing fixpoint method for higher-order analyses from the literature.

Analysis of Extracurricular Programs That Affect College Students' Writing and Speaking Skills

Communication skills such as writing and speaking contribute to learners' satisfaction with school life, academic achievement, and improvement of adaptability. In particular, the extracurricular activities experienced during college affect the acquisition of key qualities necessary for social life. The purpose of this study is to identify the extracurricular programs that affect the writing and speaking ability of college students. To confirm the purpose of this study, data were collected through an online survey conducted from April to May 2022 for current students at 4-year E-University located in Gyeonggi-do. The measurement tool is the Korea-National Survey of Student Engagement (K-NSSE). The Undergraduate Education Satisfaction Survey is a diagnostic tool that can obtain objective information on the quality and performance of undergraduate education by diagnosing undergraduate students' learning participation, learner psychology, high-efficiency program participation, and student performance. For the analysis method, frequency analysis and descriptive statistical analysis were performed. In addition, correlation analysis was performed to examine the validity between variables and to confirm multicollinearity. Finally, multiple regression analysis was performed to verify the influence of the non-examination program on the writing and speaking ability of college students. Results showed that the extracurricular program on the writing ability of college students had an influence in the order of learning mentoring, freshman orientation, professor's research project, and learning community activity. Moreover, the extracurricular program that affected the speaking ability of college students had an influence in the order of learning mentoring, professor's research project, freshman orientation, and learning community activity.

The Influence Of Employee Performance Competence On The Indonesian Coast Guard Ships

This research aims to determine (1) the influence of intellectual competence, emotional competence and social competence of employees on employee performance and, (2) the most dominant factors influencing employee performance on the State Ships of the Indonesian Maritime Security Agency or Indonesian Coast Guard (KN Bakamla RI) in 2023. There are the diverse competencies possessed by Bakamla employees who serve on the Republic of Indonesia's KN Bakamla cause less than optimal organizational performance so that an effort is needed to fill this gap. This research is mix method research, namely a combination of quantitative methods and qualitative methods. Data was collected using the methods (1) interviews, (2) documentation, and (3) questionnaires. Next, the data was processed and analyzed using multiple linear regression analysis, SPSS version 22 program and descriptive analysis. The results of the research show that employee competency influences employee performance at KN Bakamla RI, both partially and simultaneously. Partially, intellectual competence has a partial influence of 76.6% on performance, then emotional competence has a partial influence of 58.3% on performance, and social competence has a partial influence of 62.8% on performance. Simultaneously, intellectual competence, emotional competence, and social competence have a large influence on 62.3% of employee performance. There needs to be regular competency development so that employees can develop their competencies to further improve performance. This research was conducted in April-May 2024.

Assessment of emerging and persistent contaminants in an anthropogenic-impacted watershed: Application using targeted, non-targeted, and in vitro bioassay techniques

Emerging and persistent contaminants (EPC) pose a significant challenge to water quality monitoring efforts. Effect-based monitoring (EBM) techniques provide an efficient and systematic approach in water quality monitoring, but they tend to be resource intensive. In this study, we investigated the EPC distribution for various land uses using target analysis (TA) and non-target screening (NTS) and in vitro bioassays, both individually and integrated, in the upper Ping River Catchment, northern Thailand. Our findings of NTS showed that urban areas were the most contaminated of all land use types, although agriculture sites had high unexpected pollution levels. We evaluated the reliability of NTS data by comparing it to TA and observed varying inconsistencies likely due to matrix interferences and isobaric compound interferences. Integrating NTS with in vitro bioassays for a thorough analysis posed challenges, primary due to a scarcity of concentration data for key compounds, and potentially additive or non-additive effects of mixture samples that could not be accounted for. While EBM approaches place emphasis on toxic sites, this study demonstrated the importance of considering non-bioactive sites that contain toxic compounds with antagonistic effects that may go undetected by traditional monitoring approaches. The present work emphasizes the importance of improving NTS workflows and ensuring high-quality EBM analyses in future water quality monitoring programs.

Analysis of the Implementation of Training and Development Programs for Teachers in the Context of Curriculum Change: Evaluation and Recommendations

The implementation of training and development programs for teachers plays a crucial role in enhancing their skills and capabilities, especially in the context of curriculum change. This study conducts a comprehensive analysis of such programs, focusing on their effectiveness, challenges, and areas for improvement. Through a literature review approach, various scholarly works, empirical studies, and best practices are examined to evaluate the impact of training and development initiatives on teacher performance and student outcomes. The evaluation encompasses aspects such as program design, delivery methods, content relevance, participant engagement, and organizational support. It delves into the strategies employed to address the evolving needs of teachers amid curriculum transformations, considering factors like technological integration, pedagogical innovations, and curriculum alignment. Furthermore, the study explores the role of continuous professional development in sustaining teacher motivation, fostering a culture of lifelong learning, and adapting to dynamic educational landscapes. Based on the analysis, several recommendations are proposed to enhance the efficacy of training and development programs for teachers. These recommendations encompass tailored professional development pathways, collaborative learning communities, mentorship programs, feedback mechanisms, and resource allocation strategies. The findings of this study contribute valuable insights to educational policymakers, administrators, and stakeholders involved in designing and implementing teacher training initiatives within the framework of curriculum change.

Toward better pandemic governance and preparedness: South Korea’s whole-of-nation approach to COVID-19

BackgroundThe profound impact of coronavirus disease (COVID-19) has led to an increased demand for sustainable pandemic governance practices. This study explored emerging hybrid governance practices that provide robust evidence on how to address the complex challenges of pandemics effectively. South Korea, which was severely affected by COVID-19, has implemented a novel governance approach using a whole-of-nation (WoN) model. This hybrid pandemic governance approach, which integrates both whole-of-government and whole-of-society approaches, has enabled synergistic and cohesive multi-sectoral coordination among all stakeholders (public authorities, private enterprises, and civil society) to address multifaceted challenges collectively and strengthen their resilience capacity. This study investigated South Korea’s WoN practices and their embedded context and identified key governance enablers facilitating this approach.MethodsThis study employed a case study design based on an extensive analysis of policy and program documents, drawing on South Korea’s publicly available data from January 1, 2020 to March 30, 2023. It assessed six system-level collaborative pandemic governance practices and key enablers, all of which were intended to fortify the country’s pandemic response.ResultsThe primary areas of the country’s WoN governance practices for COVID-19 control were (i) whole-of-government policy-making and response, (ii) COVID-19 testing system, (iii) digital surveillance of COVID-19, (iv) COVID-19 triage and treatment system, (v) domestic vaccine production, and (vi) community engagement. Key governance enablers for implementing the WoN model were establishing a legal foundation, ensuring decisive and strong governance and leadership, increasing public investment, applying a whole-of-health approach with augmented investment in public health, enhancing crisis communication, and mobilizing local leaders and civil society organizations in the national public health response.ConclusionsIn exploring innovative approaches to pandemic governance for increased efficacy, responsiveness, and impact, the WoN approach emerged as highly relevant. This example of emerging practice allows policy-makers to re-evaluate their governance strategies and initiatives to improve multi-agency partnerships across the country in their pandemic-preparedness planning.

Compliance with MAB-UNESCO Functions and Management Effectiveness Evaluation between 2017 and 2024: Case Study of the El Cielo Biosphere Reserve, Mexico’s Only State-Run Reserve Belonging to MAB-UNESCO

UNESCO’s MAB Programme promotes a people-centered conservation strategy to strengthen the sustainability of social and ecological systems. However, there exist knowledge gaps regarding its implementation in specific contexts. For this study, a mixed-methods sequential exploratory design was employed. In the first phase, an initial content analysis of the management program of the El Cielo Biosphere Reserve (CBR) and the functions of the statutory framework of UNESCO’s MAB program was conducted. This analysis, which was human-driven but facilitated by artificial intelligence tools, underwent rigorous triangulation and expert validation to strengthen the reliability and robustness of the findings. Subsequently, the Management Effectiveness Tracking Tool (METT3) was issued to researchers, community members, civil servants, and former civil servants related to the management of the CBR. The 2024 results (n = 15) were contrasted with those obtained in 2017 (n = 15) using a quantitative approach consisting of descriptive, non-parametric, and Bayesian statistical techniques. We identified some problems in the implementation of the MAB-UNESCO Programme in the CBR, mainly due to the outdated management program and lack of effective governance, as well as the lack of understanding of the implications of being a MAB-UNESCO biosphere reserve. A numerical trend of deterioration in the effectiveness of the CBR’s management was detected, with overall ratings of 44.78% and 29.62% in 2017 and 2024, respectively. This was associated with a lack of regulation, weak coordination among key actors, and a progressive reduction in funding. The findings of this study are useful to guide the transition of the CBR towards a conservation model that responds to current problems and contributes to the advancement of knowledge on the implementation of the MAB Programme in specific contexts.

An empirical study on divergence of differently-sourced LLVM IRs

In solving binary code similarity detection, many approaches choose to operate on certain unified intermediate representations (IRs), such as Low Level Virtual Machine (LLVM) IR, to overcome the cross-architecture analysis challenge induced by the significant morphological and syntactic gaps across the diverse instruction set architectures (ISAs). However, the LLVM IRs of the same program can be affected by diverse factors, such as the acquisition source, i.e., compiled from source code or disassembled and lifted from binary code. While the impact of compilation settings on binary code has been explored, the specific differences between LLVM IRs from varied sources remain underexamined. To this end, we pioneer an in-depth empirical study to assess the discrepancies in LLVM IRs derived from different sources. Correspondingly, an extensive dataset containing nearly 98 million LLVM IR instructions distributed in 808,431 functions is curated with respect to these potential IR-influential factors. On this basis, three types of code metrics detailing the syntactic, structural, and semantic aspects of the IR samples are devised and leveraged to assess the divergence of the IRs across different origins. The findings offer insights into how and to what extent the various factors affect the IRs, providing valuable guidance for assembling a training corpus aimed at developing robust LLVM IR-oriented pre-training models, as well as facilitating relevant program analysis studies that operate on the LLVM IRs.