The SZZ algorithm is used to connect bug-fixing commits to the earlier commits that introduced bugs. This algorithm has many applications and many variants have been devised. However, there are some ...types of commits that cannot be traced by the SZZ algorithm, referred to as "ghost commits". The evaluation of how these ghost commits impact the SZZ implementations remains limited. Moreover, these implementations have been evaluated on datasets created by software engineering researchers from information in bug trackers and version controlled histories.
Since Oct 2013, the Linux kernel developers have started labelling bug-fixing patches with the commit identifiers of the corresponding bug-inducing commit(s) as a standard practice. As of v6.1-rc5, 76,046 pairs of bug-fixing patches and bug-inducing commits are available. This provides a unique opportunity to evaluate the SZZ algorithm on a large dataset that has been created and reviewed by project developers, entirely independently of the biases of software engineering researchers.
In this paper, we apply six SZZ implementations to 76,046 pairs of bug-fixing patches and bug-introducing commits from the Linux kernel. Our findings reveal that SZZ algorithms experience a more significant decline in recall on our dataset (↓ 13.8%) as compared to prior findings reported by Rosa et al., and the disparities between the individual SZZ algorithms diminish. Moreover, we find that 17.47% of bug-fixing commits are ghost commits. Finally, we propose Tracing-Commit SZZ (TC-SZZ), that traces all commits in the change history of lines modified or deleted in bug-fixing commits. Applying TC-SZZ to all failure cases, excluding ghost commits, we found that TC-SZZ could identify 17.7% of them. Our further analysis based on git log found that 34.6% of bug-inducing commits were in the function history, 27.5% in the file history (but not in the function history), and 37.9% not in the file history. We further evaluated the effectiveness of ChatGPT in boosting the SZZ algorithm's ability to identify bug-inducing commits in the function history, in the file history and not in the file history.
The purpose of this article is to organize the concepts related to the digitization of the modern enterprise and to identify potential digitization directions for process automation using the ...integration of RPA and GPT technologies. As research methods, the article uses a literature review of the past 20 years and presents a case study. The first part of the article reviews the concepts of digitization and process automation. A distinction was made in the understanding of the terms, which became the basis for describing the possibilities of integrating ChatGPT with RPA. The key prospects for using ChatGPT were then identified, and limitations were discussed. The possibility of using ChatGPT integration with RPA was illustrated with a case study of a service company form green energy sector.
To assess the ability of ChatGPT to answer common patient questions regarding hip arthroscopy, and to analyze the accuracy and appropriateness of its responses.
Ten questions were selected from ...well-known patient education websites, and ChatGPT (version 3.5) responses to these questions were graded by two fellowship-trained hip preservation surgeons. Responses were analyzed, compared to the current literature, and graded from A to D (A being the highest, and D being the lowest) in a grading scale based on the accuracy and completeness of the response. If the grading differed between the two surgeons, a consensus was reached. Inter-rater agreement was calculated. The readability of responses was also assessed using the Flesch-Kincaid Reading Ease Score (FRES) and Flesch-Kincaid Grade Level (FKGL).
Responses received the following consensus grades: A (50%, n=5), B (30%, n=3), C (10%, n=1), D (10%, n=1) (Table 2). Inter-rater agreement based on initial individual grading was 30%. The mean FRES was 28.2 (SD± 9.2), corresponding to a college graduate level, ranging from 11.7 to 42.5. The mean FKGL was 14.4 (SD±1.8), ranging from 12.1 to 18, indicating a college student reading level.
ChatGPT can answer common patient questions regarding hip arthroscopy with satisfactory accuracy graded by two high-volume hip arthroscopists, however, incorrect information was identified in more than one instance. Caution must be observed when using ChatGPT for patient education related to hip arthroscopy.
Given the increasing number of hip arthroscopies being performed annually, ChatGPT has the potential to aid physicians in educating their patients about this procedure and address any questions they may have.
Patients and healthcare professionals extensively rely on the internet for medical information. Low-quality videos can significantly impact the patient-doctor relationship, potentially affecting ...consultation efficiency and decision-making process. Chat Generative Pre-Trained Transformer (ChatGPT) is an artificial intelligence application with the potential to improve medical reports, provide medical information, and supplement orthopedic knowledge acquisition. This study aimed to assess the ability of ChatGPT-4 to detect deficiencies in these videos, assuming it would be successful in identifying such deficiencies.
YouTube was searched for 'rotator cuff surgery' and 'rotator cuff surgery clinic' videos. A total of 90 videos were evaluated, with 40 included in the study after exclusions. Using the Google Chrome extension '' YouTube Summary with ChatGPT & Claude'', transcripts of these videos were accessed. Two senior orthopedic surgeons and ChatGPT-4 evaluated the videos using the rotator cuff surgery YouTube score (RCSS) system and DISCERN criteria.
ChatGPT-4's RCSS evaluations were comparable to those of the observers in 25% of instances, and 40% for DISCERN. The interobserver agreement between human observers and ChatGPT-4 was fair (AC1: 0.575 for DISCERN and AC1: 0.516 for RCSS). Even after correcting ChatGPT-4's incorrect answers, the agreement did not change significantly. ChatGPT-4 tended to give higher scores than the observers, particularly in sections related to anatomy, surgical technique, and indications for surgery.
The use of ChatGPT-4 as an observer in evaluating rotator cuff surgery-related videos and identifying deficiencies is not currently recommended. Future studies with trained ChatGPT models may address these deficiencies and enable ChatGPT to evaluate videos at a human observer level.
ChatGPT, along with its applications, possibilities, limitations and future development, is currently one of the most often discussed topics worldwide. One of the issues raised in those discussions ...is its ethically questionable role in science and education.
The goal of this paper is to assess the accuracy and correctness of the responses given by ChatGPT, using climate change in Poland as an example. Eight questions related to this topic were posed to ChatGPT, and each answer was subsequently verified and assigned a grade on a scale of 0–10. The overall grade obtained was 3.8, indicating that only 30–40% of the information provided by ChatGPT was accurate. This poor result can be attributed to fake references, inaccurate data, overgeneralizations and simplification. Nevertheless, with proper training and development, ChatGPT has tremendous potential to serve as a valuable tool for ethically sound applications in the field of science.
ChatGpt: Open Possibilities Mohammad Aljanabi; Mohanad Ghazi; Ahmed Hussein Ali ...
Iraqi Journal for Computer Science and Mathematics,
2023, Letnik:
4, Številka:
1
Journal Article
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Odprti dostop
ChatGPT-3 is a powerful language model developed by OpenAI that has the potential to revolutionize the way we interact with technology. This model has been trained on a massive amount of data, ...allowing it to understand and generate human-like text with remarkable accuracy. One of the most exciting possibilities of ChatGPT-3 is its potential to improve natural language processing (NLP) and natural language understanding (NLU) in a wide range of applications. In particular, ChatGPT-3 can be used to power chatbots, virtual assistants, and other conversational interfaces. These types of systems are becoming increasingly important as more and more people use voice and text to interact with technology, we list ChatGpt role in each of the follwoing sections
This article explores ethical issues raised by generative conversational AI systems like ChatGPT. It applies established approaches for analysing ethics of emerging technologies to undertake a ...systematic review of possible benefits and concerns. The methodology combines ethical issues identified by Anticipatory Technology Ethics, Ethical Impact Assessment, and Ethical Issues of Emerging ICT Applications with AI-specific issues from the literature. These are applied to analyse ChatGPT's capabilities to produce humanlike text and interact seamlessly. The analysis finds ChatGPT could provide high-level societal and ethical benefits. However, it also raises significant ethical concerns across social justice, individual autonomy, cultural identity, and environmental issues. Key high-impact concerns include responsibility, inclusion, social cohesion, autonomy, safety, bias, accountability, and environmental impacts. While the current discourse focuses narrowly on specific issues such as authorship, this analysis systematically uncovers a broader, more balanced range of ethical issues worthy of attention. Findings are consistent with emerging research and industry priorities on ethics of generative AI. Implications include the need for diverse stakeholder engagement, considering benefits and risks holistically when developing applications, and multi-level policy interventions to promote positive outcomes. Overall, the analysis demonstrates that applying established ethics of technology methodologies can produce a rigorous, comprehensive foundation to guide discourse and action around impactful emerging technologies like ChatGPT. The paper advocates sustaining this broad, balanced ethics perspective as use cases unfold to realize benefits while addressing ethical downsides.
•Applies established ethics of emerging technology methods to analyse ChatGPT.•Uncovers broad range of high-impact ethical issues beyond current narrow focus.•Provides a comprehensive overview of ethics of large language models.•Analysis consistent with emerging research and industry priorities on ethics.•Advocates sustaining broad, balanced ethics perspective as applications develop.
ChatGPT is an AI tool that has sparked debates about its potential implications for education. We used the SWOT analysis framework to outline ChatGPT's strengths and weaknesses and to discuss its ...opportunities for and threats to education. The strengths include using a sophisticated natural language model to generate plausible answers, self-improving capability, and providing personalised and real-time responses. As such, ChatGPT can increase access to information, facilitate personalised and complex learning, and decrease teaching workload, thereby making key processes and tasks more efficient. The weaknesses are a lack of deep understanding, difficulty in evaluating the quality of responses, a risk of bias and discrimination, and a lack of higher-order thinking skills. Threats to education include a lack of understanding of the context, threatening academic integrity, perpetuating discrimination in education, democratising plagiarism, and declining high-order cognitive skills. We provide agenda for educational practice and research in times of ChatGPT.
El libro Artificial aborda fundamentalmente el concepto de inteligencia humana, partiendo de la definición de Inteligencia como todo aquello que no hacen las máquinas. La IA es la primera máquina que ...sale de lo rutinario y ocupa el lugar de las grandes ideas. Y en este sentido, el primer capítulo, titulado la Génesis de la Inteligencia, trae el juego del ajedrez como el mejor ejemplo de uso de la IA. Éste fue el primer paso en emular la inteligencia humana cuando Turing se preguntó, “¿cómo se diseña un programa capaz de analizar una posición de ajedrez y con criterio para tomar buenas decisiones?” AlphaGo, y AlphaZero después, pudieron responder a la pregunta. La IA indefectiblemente está relacionada con lo humano, y constituye así, el eje vertebrador de esta obra. En palabras de sus autores, “la inteligencia artificial, como la humana, construye también su propia cultura”. A lo largo de los 2 primeros capítulos, los autores presentan el recorrido en la evolución de la IA desde el año 1938, hasta la aparición en la segunda década de este siglo de los modelos LLM (Large Language Models), es decir, grandes modelos de lenguaje, basados en transformers, entrenados con grandes volúmenes de datos. Los restantes capítulos presentan las posibilidades que emergen a partir de la IA alternando los cambios cuantitativos y cualitativos en lo que respecta a los ámbitos educativo, laboral, ético e intelectual.
