RSL autonomous rover

Autonomous vehicles are useful for a variety of applications such as military, urban, and agricultural environments. This paper discusses adding an autonomous navigation system to an all-terrain vehicle by implementing controllers that interface with its current system, installing sensors on the vehicle for obstacle detection, and developing effective safety mechanisms to prevent injury to others. The result is a vehicle capable of waypoint navigation and obstacle avoidance. Testing the vehicle showed that the LIDAR and the autonomous navigation system were integrated seamlessly, and that the sensor output signals were successfully translated into vehicle commands the existing system uses. This system could be improved with further tuning of the PID controller to prevent a large deviation from the defined path. The LIDAR could also be programmed to allow the vehicle to navigate around the obstacle instead of stopping in front of it

Unity is Strength: Enhancing Precision in Reentrancy Vulnerability Detection of Smart Contract Analysis Tools

Reentrancy is one of the most notorious vulnerabilities in smart contracts, resulting in significant digital asset losses. However, many previous works indicate that current Reentrancy detection tools suffer from high false positive rates. Even worse, recent years have witnessed the emergence of new Reentrancy attack patterns fueled by intricate and diverse vulnerability exploit mechanisms. Unfortunately, current tools face a significant limitation in their capacity to adapt and detect these evolving Reentrancy patterns. Consequently, ensuring precise and highly extensible Reentrancy vulnerability detection remains critical challenges for existing tools. To address this issue, we propose a tool named ReEP, designed to reduce the false positives for Reentrancy vulnerability detection. Additionally, ReEP can integrate multiple tools, expanding its capacity for vulnerability detection. It evaluates results from existing tools to verify vulnerability likelihood and reduce false positives. ReEP also offers excellent extensibility, enabling the integration of different detection tools to enhance precision and cover different vulnerability attack patterns. We perform ReEP to eight existing state-of-the-art Reentrancy detection tools. The average precision of these eight tools increased from the original 0.5% to 73% without sacrificing recall. Furthermore, ReEP exhibits robust extensibility. By integrating multiple tools, the precision further improved to a maximum of 83.6%. These results demonstrate that ReEP effectively unites the strengths of existing works, enhances the precision of Reentrancy vulnerability detection tools

Turn the Rudder: A Beacon of Reentrancy Detection for Smart Contracts on Ethereum

Smart contracts are programs deployed on a blockchain and are immutable once deployed. Reentrancy, one of the most important vulnerabilities in smart contracts, has caused millions of dollars in financial loss. Many reentrancy detection approaches have been proposed. It is necessary to investigate the performance of these approaches to provide useful guidelines for their application. In this work, we conduct a large-scale empirical study on the capability of five well-known or recent reentrancy detection tools such as Mythril and Sailfish. We collect 230,548 verified smart contracts from Etherscan and use detection tools to analyze 139,424 contracts after deduplication, which results in 21,212 contracts with reentrancy issues. Then, we manually examine the defective functions located by the tools in the contracts. From the examination results, we obtain 34 true positive contracts with reentrancy and 21,178 false positive contracts without reentrancy. We also analyze the causes of the true and false positives. Finally, we evaluate the tools based on the two kinds of contracts. The results show that more than 99.8% of the reentrant contracts detected by the tools are false positives with eight types of causes, and the tools can only detect the reentrancy issues caused by call.value(), 58.8% of which can be revealed by the Ethereum's official IDE, Remix. Furthermore, we collect real-world reentrancy attacks reported in the past two years and find that the tools fail to find any issues in the corresponding contracts. Based on the findings, existing works on reentrancy detection appear to have very limited capability, and researchers should turn the rudder to discover and detect new reentrancy patterns except those related to call.value().Comment: Accepted by ICSE 2023. Dataset available at https://github.com/InPlusLab/ReentrancyStudy-Dat

A Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends

General large language models (LLMs), represented by ChatGPT, have demonstrated significant potential in tasks such as code generation in software engineering. This has led to the development of specialized LLMs for software engineering, known as Code LLMs. A considerable portion of Code LLMs is derived from general LLMs through model fine-tuning. As a result, Code LLMs are often updated frequently and their performance can be influenced by the base LLMs. However, there is currently a lack of systematic investigation into Code LLMs and their performance. In this study, we conduct a comprehensive survey and analysis of the types of Code LLMs and their differences in performance compared to general LLMs. We aim to address three questions: (1) What LLMs are specifically designed for software engineering tasks, and what is the relationship between these Code LLMs? (2) Do Code LLMs really outperform general LLMs in software engineering tasks? (3) Which LLMs are more proficient in different software engineering tasks? To answer these questions, we first collect relevant literature and work from five major databases and open-source communities, resulting in 134 works for analysis. Next, we categorize the Code LLMs based on their publishers and examine their relationships with general LLMs and among themselves. Furthermore, we investigate the performance differences between general LLMs and Code LLMs in various software engineering tasks to demonstrate the impact of base models and Code LLMs. Finally, we comprehensively maintained the performance of LLMs across multiple mainstream benchmarks to identify the best-performing LLMs for each software engineering task. Our research not only assists developers of Code LLMs in choosing base models for the development of more advanced LLMs but also provides insights for practitioners to better understand key improvement directions for Code LLMs

Health-related quality of life and its association with socioeconomic status and diet diversity in Chinese older adults

ObjectivesThe study aimed at examining the combined association of socioeconomic status (SES) and diet diversity (DD) with health-related quality of life (HRQoL) and exploring whether DD played a mediating role in the relationship between varied SES and HRQoL among Chinese older persons.MethodA multi-stage random sampling method was conducted in Shanxi Province of China, with 3,250 older adults participating in this cross-sectional survey. SES was divided into groups by quartiles and DD by means, and these variable groups were combined in pairs to generate a total of eight combinations. The PROCESS macro developed by Hayes was employed for the simple mediation analysis.ResultsCompared with the reference group (those with both high SES and high DD), older adults who were classified to have lower SES or DD had elevated odds of having worse HRQoL: low SES/ low DD (OR = 1.65, 95% CI 1.41–2.92); low SES/ high DD (OR = 1.45, 95% CI 1.17–1.80); middle low SES/ low DD (OR = 1.43, 95% CI 1.24–1.65); middle low SES/ high DD (OR = 1.23, 95% CI 1.03–1.47); upper high SES/ low DD (OR = 1.41, 95% CI 1.21–1.65); and high SES/ low DD (OR = 1.30, 95%CI 1.10–1.53). The mediation analysis revealed that DD mediated the relationship between SES and HRQoL (B=0.011, 95% CI 0.008–0.013), with its indirect effects accounting for 39.29% of the total effects.ConclusionsThese findings highlighted the role of DD as a mediator of the relationship between SES and HRQoL. As DD could be protective, modifiable, and easy for older adults to understand and implement, village clinics and community health stations should work collaboratively to design proper DD intervention measures for better HRQoL

The role and effect of damping on the response of a flexible shaft in the region of a critical speed

An experimental study concerned with the role and effect of damping for a rotating flexible shaft in the region of a critical speed is conducted. The existing theory (1) is reviewed for a rotating system with an unbalanced disk in the center of a flexible shaft. The effect of damping on the system is discussed. The experimental results reveal that the external damping plays a role which is taken properly into account by the existing theory. In contract, internal damping does not affect the rotating system in the region of the critical speed.Mechanical Engineering, Department o