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pro vyhledávání: '"Rasheed, Zeeshan"'
Autor:
Sami, Abdul Malik, Rasheed, Zeeshan, Waseem, Muhammad, Zhang, Zheying, Tomas, Herda, Abrahamsson, Pekka
Large Language Models (LLMs) are widely used in Software Engineering (SE) for various tasks, including generating code, designing and documenting software, adding code comments, reviewing code, and writing test scripts. However, creating test scripts
Externí odkaz:
http://arxiv.org/abs/2406.07021
Autor:
Sami, Malik Abdul, Waseem, Muhammad, Rasheed, Zeeshan, Saari, Mika, Systä, Kari, Abrahamsson, Pekka
Large language models are redefining software engineering by implementing AI-powered techniques throughout the whole software development process, including requirement gathering, software architecture, code generation, testing, and deployment. Howev
Externí odkaz:
http://arxiv.org/abs/2406.05381
Autor:
Rasheed, Zeeshan, Sami, Malik Abdul, Waseem, Muhammad, Kemell, Kai-Kristian, Wang, Xiaofeng, Nguyen, Anh, Systä, Kari, Abrahamsson, Pekka
In this paper, we present a novel approach to improving software quality and efficiency through a Large Language Model (LLM)-based model designed to review code and identify potential issues. Our proposed LLM-based AI agent model is trained on large
Externí odkaz:
http://arxiv.org/abs/2404.18496
Autor:
Sami, Malik Abdul, Rasheed, Zeeshan, Waseem, Muhammad, Zhang, Zheying, Herda, Tomas, Abrahamsson, Pekka
Large Language Models (LLMs) are revolutionizing Software Engineering (SE) by introducing innovative methods for tasks such as collecting requirements, designing software, generating code, and creating test cases, among others. This article focuses o
Externí odkaz:
http://arxiv.org/abs/2405.01564
As Large Language Models (LLMs) have become integral to both research and daily operations, rigorous evaluation is crucial. This assessment is important not only for individual tasks but also for understanding their societal impact and potential risk
Externí odkaz:
http://arxiv.org/abs/2404.01023
Autor:
Sami, Abdul Malik, Rasheed, Zeeshan, Kemell, Kai-Kristian, Waseem, Muhammad, Kilamo, Terhi, Saari, Mika, Duc, Anh Nguyen, Systä, Kari, Abrahamsson, Pekka
Systematic Literature Reviews (SLRs) have become the foundation of evidence-based studies, enabling researchers to identify, classify, and combine existing studies based on specific research questions. Conducting an SLR is largely a manual process. O
Externí odkaz:
http://arxiv.org/abs/2403.08399
Large Language Models (LLMs) and Generative Pre-trained Transformers (GPTs) are reshaping the field of Software Engineering (SE). Existing LLM-based multi-agent systems have successfully resolved simple dialogue tasks. However, the potential of LLMs
Externí odkaz:
http://arxiv.org/abs/2402.01411
Autor:
Rasheed, Zeeshan, Waseem, Muhammad, Ahmad, Aakash, Kemell, Kai-Kristian, Xiaofeng, Wang, Duc, Anh Nguyen, Abrahamsson, Pekka
Recent advancements in Large Language Models (LLMs) have enabled collaborative human-bot interactions in Software Engineering (SE), similar to many other professions. However, the potential benefits and implications of incorporating LLMs into qualita
Externí odkaz:
http://arxiv.org/abs/2402.01386
Autor:
Rasheed, Zeeshan1 zshan6777@gmail.com, Zain, Atta-Ul-Mustafa1 attaulmustafazain@gmail.com, Hanif, Muhammad1 dr.mhanif@gcu.edu.pk, Amanat, Rizwan1 rizwanamanat22@gmail.com, Ali, Baber2, Khan, Muhammad Nauman3,4, Fazal, Uzma5, Almutairi, Saeedah Musaed6, Ercisli, Sezai7,8, Eldin Darwish, Doaa Bahaa7,9
Publikováno v:
Polish Journal of Environmental Studies. 2024, Vol. 33 Issue 4, p4325-4334. 10p.
The recent proliferation of real-world human mobility datasets has catalyzed geospatial and transportation research in trajectory prediction, demand forecasting, travel time estimation, and anomaly detection. However, these datasets also enable, more
Externí odkaz:
http://arxiv.org/abs/2206.15352