Static Analysis Research Articles

Formalization of Android Activity-Fragment Multitasking Mechanism and Static Analysis of Mobile Apps

The multitasking mechanism between activities and fragments plays a fundamental role in the Android operating system, which involves a wide range of features, including launch modes, intent flags, task affinities, and structured activities containing fragments. All of them are being widely used in Android apps, both open-source and commercial ones. In this paper, we present a formal semantics of the Android multitasking mechanism between activities and fragments, which accommodates all the important features and gives insofar the most comprehensive and accurate formalization. In particular, our semantics is formulated based on multi-stack systems, and fully captures the behavior of task stacks and activity stacks regarding fragments. Based on the semantics, we provide new static analysis algorithms, which are both multi-stack-aware and fragment-sensitive, thus achieve more precise static analysis for Android apps. We validate our approach by extensive experiments on both open-source and commercial Android apps. The results highlight the benefits of the considering the semantics of the multitasking mechanism between activities and fragments in static analysis, and confirm the efficacy of our approach.

Can machine learning surpass human investors? Evidence from adaptive herding behaviour in US, China and India

ABSTRACT This study examined the effectiveness of machine learning models in capturing adaptive herding behaviour in the US, China, and India. Utilising data from January 2010 to December 2023, this study incorporates market sentiment (Thomson Reuters MarketPsych Indices), news sentiment (Bloomberg Sentiment Analysis), and investor happiness measures (Hedonometer). The methodology employs both static and adaptive herding analyses using the CSAD approach, enhanced by real-time sentiment analysis and various machine learning models, including single- and multi-layer neural networks. The results indicate significant differences in herding behaviour across the three markets, with machine learning models demonstrating superior performance in capturing herding behaviour and faster normalisation after major macroeconomic events than traditional methods. These findings highlight the potential of machine learning models to challenge the static assumptions of the Efficient Market Hypothesis and provide insights for designing better trading algorithms by considering the impact of market sentiment, news sentiment, and investor happiness.

First-Principles Study on Formation Mechanism of Six-Coordinated Si in Silicophosphate Glass.

Six-coordinated Si ([6]Si) structures are readily formed in silicophosphate glasses with high P2O5 contents. Although experiments and simulations have provided some information on the local configurations around [6]Si, further research on the formation mechanism of [6]Si at the atomic scale is needed. To investigate the formation mechanism of [6]Si, we performed dynamic and static analyses based on first-principles calculations. In first-principles molecular dynamics simulations with models in which all Si atoms are four-coordinated as the initial structure, we observed that the coordination number of Si increased, and the P-Q2 (P-Qn, where n represents the number of bridging oxygen atoms) changed to P-Q3. Atomic energy analysis revealed that the energy decreases with the structural change from P-Q2 to P-Q3 exceeded the energy increase with an increase in the coordination number of Si, stabilizing of the entire system. We conclude that the key factor in the formation of [6]Si is the decrease in energy associated with the change from a nonbridging oxygen in a PO4 tetrahedral structure to bridging oxygen.

An augmented Environmental Kuznets Curve and a new measure of water pollution: an investigation of water pollution in Africa

Water pollution constitutes an increasingly urgent problem worldwide. This is particularly true for the African continent, which is experiencing high and increasing levels of water pollution. The continent holds great economic growth potential, making it imperative to understand the economic drivers of water pollution to ensure that African countries develop without degrading water quality. This study examines how countries’ income level, trade, and institutional quality affect water pollution across 42 African countries from 2002 to 2016, using newly estimated data on water pollution from the WorldQual model. An augmented Environmental Kuznets Curve (EKC) is employed using static and dynamic panel estimation techniques, specifically cross-section ordinary least squares and fixed effects regressions, and the system generalised method of moments. The static analysis reveals that economic growth initially increases pollution until reaching a turning point between 6244 and 8974 USD of Gross Domestic Product (GDP) per capita, after which pollution levels decrease. Yet, the dynamic analysis suggests the relationship between GDP and pollution is insignificant. Further, the study uncovers that the impact of institutional quality on water pollution depends on the level of trade. Specifically, at high levels of trade, higher institutional quality is associated with less water pollution, while at low levels of trade, higher in institutional quality is associated with more pollution. This study highlights the complex interplay of economic and institutional factors that must be navigated to effectively address the challenge of water pollution in Africa.

Evaluation of the sustainable development efficiency of environment and energy in China

With the increasing global demand for sustainable development, China, being one of the world’s most populous countries, is confronted with increasingly prominent challenges in sustainable development of environment and energy, specifically in terms of environmental protection and energy transformation. To promote sustainable development in China’s environment and energy sector, this paper constructs an evaluation indicator system for sustainable development of environment and energy by integrating the relevant sustainable development goals outlined in the 2030 Agenda for Sustainable Development. The DEA-SBM model is employed for static analysis of the sustainable development efficiency and dynamic analysis is conducted using the Malmquist index, aiming to reveal regional differences and trends in the efficiency of sustainable development from 2016 to 2022. The results indicate that there is a significant disparity in the sustainable development efficiency of environment and energy among the 31 provinces in China. China has seen a slight overall improvement in the sustainable development of environment and energy, with a promotion of environmentally friendly development patterns. Moreover, technological innovation proves to be a key element in achieving more efficient and environmentally friendly development. In addition, the decomposition of technical efficiency change also makes the management level and factor allocation be attached importance.

Early Detection of Hard-Coded Secrets in Software Development: A Multi-Method Approach Integrating Static Analysis, Entropy-Based Detection, and Machine Learning

The inadvertent inclusion of hard-coded secrets—such as API keys, passwords, and tokens—within source code poses significant security risks, potentially leading to unauthorized access and data breaches. Recent studies have highlighted the prevalence of this issue; for instance, GitGuardian's 2023 report revealed a 67% increase in detected hard-coded secrets compared to the previous year, with 10 million new secrets discovered in public GitHub commits in 2022. To address this escalating concern, our research proposes a comprehensive, multi-method approach that integrates static code analysis, entropy-based detection, and machine learning techniques to enhance the early identification of hard-coded secrets during the software development lifecycle. By combining these methodologies, the proposed approach improves detection accuracy, reduces false positives, and provides developers with actionable insights to mitigate security vulnerabilities proactively. This integrated strategy not only strengthens the security posture of software applications but also fosters a culture of secure coding practices among development teams. Keywords Shift-Left Security, Secrets Detection, Static Analysis, Entropy-Based Detection, Machine Learning, Hard-Coded Secrets, Secure Development Lifecycle

Simplified Procedure for Estimating Seismic Displacement Capacity of Concrete Piles in Wharves

The procedure of estimating the seismic displacement capacity of piles under each performance level in current wharf practices involves monitoring the material strains specified in the design criteria during nonlinear static pushover analysis with a complex numerical model. Thus, a simplified procedure for concrete piles is proposed by developing closed-form formulas for displacement ductility capacity and yield displacement of piles, while the displacement capacity is the product of ductility capacity and yield displacement. The ductility capacity assures that the pile material strain limits specified in the criteria are not exceeded. The basic form of the formula for ductility capacity is established by using the equivalent cantilever concept to model the pile–soil interaction. Then, large quantities of moment–curvature analyses of sections and pushover analyses of concrete piles were conducted to determine the related parameters in the formula by considering numerous influencing factors. The results show that the ductility capacity can be expressed as a function of the curvature ductility capacity of pile sections at the selected performance level and parameter ψ. Based on the outcomes of curvature and pushover analyses, a set of practical formulas are proposed to determine the curvature ductility capacity, which depends on the longitudinal or transverse reinforcement ratios and axial force level, along with ψ, which depends on the aforementioned factors as well as the unsupported length of the pile.

Assessing the problems of the shadow economy in Russia

The purpose of writing the article is to systematize the problems of the shadow sector in Russia. The methodological basis was: static analysis, scientific works and periodicals in the field of the shadow sector. The article evaluates and analyzes the reasons for the existence of shadow financial flows. The author examines informal employment in more detail as one of the main problems of the shadow sector. The author points out that the shadow economy is not able to create attractive conditions for entrepreneurs. A static analysis of the shadow market was conducted. The article provides recommendations for solving the problems of the shadow market, which will help reduce this sector.

A Comparative study on Static, Free Vibration and Energy Absorption Analysis of Thick Truncated Cones Reinforced with GOri or GPLs

A Comparative study on Static, Free Vibration and Energy Absorption Analysis of Thick Truncated Cones Reinforced with GOri or GPLs

ANALYSIS AND COMPARISON OF MACHINE LEARNING METHODS FOR MALWARE DETECTION

Our study aims to analyze and evaluate modern machine learning methods for detecting malware, a critical challenge given the increasing complexity and volume of cyber threats. We explore various algorithms, including Support Vector Machines, Random Forest, Logistic Regression, Decision Trees, and K-Means Clustering, comparing their effectiveness in identifying and classifying malware. Our methodology combines static, dynamic, and memory-based analysis techniques, offering a comprehensive approach to understanding malware behavior. Key findings reveal that Decision Trees and Random Forests demonstrate impressive accuracy in both binary and multi-class classification tasks. We also highlight novel methods such as the Self-Organizing Incremental Neural Network (SOINN), which effectively handles evolving malware threats. The integration of static and dynamic analysis methods deepens insights into malware behavior. This research underscores the importance of advancing machine learning techniques to enhance cybersecurity measures against evolving global malware threats, offering valuable insights for future research directions.

Shear Failure Assessment of a G+3 RC Framed Building via Nonlinear Static Pushover Analysis using SAP2000

Accurately modelling shear behaviour in reinforced concrete (RC) structures is essential for seismic evaluation, as shear failure can lead to catastrophic outcomes. Current industry practices often emphasize nonlinear flexural analysis while underestimating the critical role of shear behaviour. This study aims to develop a nonlinear force-deformation model specifically for shear in RC sections to bridge the gap in existing literature. Standards like IS-456:2000 and ACI-318:2008 provide ultimate strength estimates but may inadequately consider the contribution of concrete under seismic loads. Insights from models by Priestley et al. (1996) and Park and Pauley (1975) are integrated to improve the calculation of shear hinge properties. A comparative nonlinear static (pushover) analysis of an RC framed building, with and without shear hinges, demonstrates the impact of shear modelling. Results show that neglecting shear hinges overestimates base shear and roof displacement capacity, masking non-ductile failure modes. Incorporating shear hinges provides a more realistic assessment of structural strength and ductility, emphasizing their necessity in seismic analysis and design. Keywords: Shear behaviour, Reinforced concrete (RC) structures, Seismic evaluation, Shear failure, Nonlinear analysis, Force-deformation model, Shear hinge.

Comparison of Seismic and Structural Parameters of Settlements in the East Anatolian Fault Zone in Light of the 6 February Kahramanmaraş Earthquakes

On 6 February 2023, two very large destructive earthquakes occurred in the East Anatolian Fault Zone (EAFZ), one of Türkiye’s primary tectonic members. The fact that these earthquakes occurred on the same day and in the same region increased the extent of the destruction. Within the scope of this study, twenty different settlements affected by earthquakes and located directly on the EAFZ were taken into consideration. Significant destruction and structural failure at different levels were induced in reinforced concrete (RC) structures, the dominant urban building stock in these regions. To determine whether the earthquake hazard is adequately represented, the PGA values predicted in the last two earthquake hazard maps used in Türkiye for these settlements were compared with the measured PGAs from actual earthquakes. Subsequently, the damage to reinforced concrete structures in these settlements was evaluated within the scope of construction and earthquake engineering. In the final part of the study, static pushover analyses were performed on a selected example of a reinforced concrete building model, and target displacement values for different performance levels were determined separately for each earthquake. For the 20 different settlements considered, the displacements were also derived based on the values predicted in the last two earthquake hazard maps, and comparisons were made. While the target displacements were exceeded in some settlements, there was no exceedance in the other settlements. The realistic presentation of earthquake hazards will enable the mentioned displacements predicted for different performance levels of structures to be determined in a much more realistic manner. As a result, the performance grades predicted for the structures will be estimated more accurately.

ANALYSIS & DESIGN OF G+20 BUILDING ON A SLOPY GROUND BY USING STAAD PRO

This study focuses on the analysis and design of RCC multi-storeyed G+14 framed buildings with both regular and irregular plans, using STAAD Pro software. The objective is to model and analyze the buildings under seismic loads through equivalent static analysis. Key areas of study include the comparison of regular and irregular building configurations and the impact of shear walls on seismic performance. The research investigates the structural behavior, including displacement, stress distribution, and stability of buildings subjected to lateral seismic loads, with a focus on buildings with and without shear walls. The findings reveal significant differences in the structural responses between the two configurations, highlighting the importance of shear walls in improving seismic resistance. The study concludes that shear walls enhance the structural integrity and reduce lateral displacements, providing recommendations for designing safer buildings in seismic zones. The research aims to offer valuable insights for effective design strategies to ensure safety and minimize seismic damage in multi-storeyed RCC buildings. Keywords: RCC, multi-storeyed, G+14 framed buildings, regular and irregular plans, STAAD Pro, seismic loads, equivalent static analysis, shear walls, structural behavior, displacement, stress distribution, stability, seismic resistance, seismic zones, structural integrity, effective design strategies.

EFFECT OF MECHANICAL PROPERTIES OF FILLING MATERIAL ON STATIC AND DYNAMIC BEHAVIOR OF MASONRY ARCH BRIDGES

The present study examined the impacts of the mechanical properties of the filling material on the seismic behaviour of masonry arch bridges (MAB). A bridge model that did not exist was selected to achieve this objective. Using this model, bridge models with different filling material properties were created in the SAP2000 computer program. Modal analysis and linear time history analysis (THA) were conducted on the aforementioned models to ascertain the filling material's influence on the bridge's dynamic behavior. The findings of the modal analysis indicated that an increase in the density of the filling material increased in the period, while an increase in the elasticity modulus led to a decrease in the period. As a result of linear THA, it was determined that as the density of the filling material increases, the displacements and stresses increase, and as the elastic modulus increases, the displacements and stresses decrease. As a result of static analysis, it was determined that as the density of the filling material increases, the displacement and stress values increase, and as the elastic modulus increases, these values decrease.

BLESS Behavior Correctness Proof as ConvincingVerification Artifact

Safety-critical cyber-physical systems require evidence they are indeed safe. In practice, such evidence is results of system tests. Unfortunately, tests can only demonstrate the presence of software errors, not their absence, and can practically cover a tiny fraction of system state space. Valiant efforts to formally verify program correctness have either been excruciatingly difficult (theorem proving) or incomplete (static analysis, model checking, SAT or SMT solving). The BLESS Methodology was created specifically for engineers in industry to formally verify software controlling machines. The BLESS Methodology transforms programs that control machines, annotated with assertions to form proof outlines, into deductive proofs that every possible program execution will conform to its specification. To the extent that cyber-physical system specifications have been validated to express system safety and performance, a deductive proof can be a convincing argument to a person of program correctness. This paper uses a simple safety-critical system to argue that behavior correctness proof under the BLESS Methodology is a convincing verification artifact in addition to customary testing.

Structural Analysis of Latticed Steel Transmission Towers Subjected to Nondeterministic Wind Loads

Lattice steel towers are commonly used to support overhead power transmission lines. However, the dynamic behavior of these structures is often overlooked in current design practices. Given that many accidents involving these towers occur even at basic wind speeds lower than those specified in the project, it is likely that dynamic actions play a significant role in these failures. This study proposes a method to accurately simulate the interaction between transmission line cables and towers under non-deterministic wind loads to assess displacements and forces in the steel towers. The study examines a transmission line system consisting of towers, conductors, shield wires, and insulators, featuring a central suspension tower of 32.86 m in height, flanked by two end towers with 450 m spans. Finite element modeling was developed to account for the dynamic characteristics of the wind. Wind loads were modeled as a random process based on their statistical properties. The results revealed significant differences in displacement and force values when comparing the results provided by static and dynamic analyses. The structural design of a base leg member indicated potential failure at higher wind velocities, highlighting the importance of considering the wind dynamic effects in the design.

Bank Liquidity and Financial Performance of Deposit Money Banks in Nigeria

Due to the importance of the deposit money bank to the Nigerian Economy that liquidity level and status of this sector is not only important to the investors, the bank itself but also to the economy at large. Based on this challenge this study examines into the impact of bank liquidity on financial performance of deposit money banks in Nigeria. The secondary data was sourced from the audited financial statement of deposit money banks from 2018 to 2022. The study employed the static panel regression analysis to determine the relationship between liquidity ratio, loan-to-deposit ratio and bank size and financial performance measures. The findings from model one reveals that loan-to-deposit ratio and liquidity ratio has negative and positive significant effect on earnings per share, while loan-to-deposit ratio, liquidity ratio and bank size has negative significant effect on net interest margin. It is therefore recommended that deposit money banks should carefully manage their loan-to-deposit ratios to avoid excessive lending that could negatively impact earnings per share. Institutions should focus on improving their liquidity ratios by maintaining sufficient liquid assets to meet short-term obligations. Enhancing liquidity management practices can positively affect earnings per share, boosting overall financial performance and shareholder value. Regularly monitoring and adjusting these ratios will ensure a balanced approach to lending and liquidity, supporting sustainable growth and profitability. Additionally, financial institutions should provide ongoing training and resources to their teams to strengthen risk management and financial planning.

Insights Into the Thermal Stability and Proton Transport Mechanism of PTFE‐Nafion Composite Membranes

ABSTRACTThe controllable design of proton exchange membranes (PEMs) with outstanding temperature resistance and efficient proton conduction is essential for high‐temperature PEM fuel cells. In this study, a polytetrafluoroethylene (PTFE)‐Nafion composite PEM was prepared using immersion and high‐temperature heat treatment methods. To understand the thermal stability, the glass transition temperatures of the PTFE‐Nafion and Nafion membranes were tested using static thermomechanical analysis. The PTFE‐Nafion membrane had a higher glass transition temperature than the Nafion membrane. In terms of the microstructure, the PTFE‐Nafion composite membrane exhibited a slightly larger ion domain structure than the Nafion membrane, and the first scattering peak of the PTFE‐Nafion composite membrane appeared at q ≈ 0.018 nm−1, while the pure Nafion membrane peak was located at q ≈ 0.022 nm−1. The PTFE‐Nafion composite membrane also exhibited higher proton conductivity than the Nafion membrane, and the activation energy of the Nafion membrane was approximately 3.5 times higher than that of the PTFE‐Nafion composite membrane. These results demonstrated the difference in proton transport mechanism for the PTFE‐Nafion composite and pure membranes, which may help guide the rational design of PEMs for fuel cells operating in high‐temperature and low‐humidity environments.

Static and Dynamic Analysis of Automated Car Parking Tower Systems

Background: Our country has dramatically evolved over the decades, and now we have a large number of well-connected roads, public buildings and a rising number of automobiles. With the passage of time, the manual car parking system in commercial spaces has become a stumbling block and wastes time. As a result, it requires a solution that can address these issues. Automated car parking systems are the answer to these issues. Methods: In this study, the static and dynamic response spectrum approach was used to analyze G+13 storey automated car parking by using ETABS-2018 systems Results: The storey displacement, storey stiffness, storey shear and overturning moment of steel and Reinforced cement concrete (RCC) automated car parking tower subjected to static and dynamic load for seismic zone III and zone IV in India have been determined. Conclusion: The RCC automated car parking tower was found to be not only stiffer but also lowered the displacement of construction.

Security analysis and evaluation of mobile banking applications in Nigeria

Rapid fintech adoption across the world is so ubiquitous. To facilitate more adoption in Nigeria, recently the Central Bank of Nigeria (CBN) introduced several policies that support cashless banking. Nowadays, Nigerian banks users could perform most of their daily transactions from any desired location using mobile banking applications. In the literature, there are insufficient studies that comprehensively evaluate the security strength or risks of these applications. Generally, insecure mobile banking applications could lead to financial fraud, violations of privacy, identity theft and eroded user confidence. Considering the situation, there is need to conduct research which comprehensively assess security of the applications. Consequently, in this paper we analyzed and evaluated the security of identified popular mobile banking applications in Nigeria. We conducted the analysis work using automated and manual static analysis methods. Then, we evaluated the security of the applications using multi-criteria decision-making technique. Our results revealed that most of the applications have several security challenges in form of vulnerabilities and insecure coding practices. Hence, our findings have shown the applications need further improvements for better security and safety.