Software Engineering (cs.SE)

Abstract: Scenario-based testing is considered state-of-the-art to verify and validate Advanced Driver Assistance Systems or Automated Driving Systems. Due to the official launch of the SOTIF-standard (ISO 21448), scenario-based testing becomes more and more relevant for releasing those Highly Automated Driving Systems. However, an essential missing detail prevent the practical application of the SOTIF-standard: How to practically generate scenarios for scenario-based testing? In this paper, we perform a Systematic Literature Review to identify techniques that generate scenarios complying with requirements of the SOTIF-standard. We classify existing scenario generation techniques and evaluate the characteristics of generated scenarios wrt. SOTIF requirements. We investigate which details of the real-world are covered by generated scenarios, whether scenarios are specific for a system under test or generic, and whether scenarios are designed to minimize the set of unknown and hazardous scenarios. We conclude that scenarios generated with existing techniques do not comply with requirements implied by the SOTIF-standard; hence, we propose directions for future research.

Abstract: Q&A platforms have been an integral part of the web-help-seeking behavior of programmers over the past decade. However, with the recent introduction of ChatGPT, the paradigm of web-help-seeking behavior is experiencing a shift. Despite the popularity of ChatGPT, no comprehensive study has been conducted to evaluate the characteristics or usability of ChatGPT's answers to software engineering questions. To bridge the gap, we conducted the first in-depth analysis of ChatGPT's answers to 517 Stack Overflow (SO) questions and examined the correctness, consistency, comprehensiveness, and conciseness of ChatGPT's answers. Furthermore, we conducted a large-scale linguistic analysis, and a user study to understand the characteristics of ChatGPT answers from linguistic and human aspects. Our analysis shows that 52\% of ChatGPT answers are incorrect and 77\% are verbose. Nonetheless, ChatGPT answers are still preferred 39.34\% of the time due to their comprehensiveness and well-articulated language style. Our result implies the necessity of close examination and rectification of errors in ChatGPT, at the same time creating awareness among its users of the risks associated with seemingly correct ChatGPT answers.

Abstract: In this paper, we present a novel algorithm called the Hybrid Search algorithm that integrates the Zermelo's Navigation Initial Value Problem with the Ferraro-Mart\'in de Diego-Almagro algorithm to find the optimal route for a vessel to reach its destination. Our algorithm is designed to work in both Euclidean and spherical spaces and utilizes a heuristic that allows the vessel to move forward while remaining within a predetermined search cone centred around the destination. This approach not only improves efficiency but also includes obstacle avoidance, making it well-suited for real-world applications. We evaluate the performance of the Hybrid Search algorithm on synthetic vector fields and real ocean currents data, demonstrating its effectiveness and performance.