Pub Date : 2024-06-26DOI: 10.1109/mitp.2024.3379831
Wahyu Rahmaniar
Rapid natural language processing advances, such as OpenAI’s ChatGPT, promise profound transformations across multiple domains, including software development. This article discusses ChatGPT’s role in software engineering, including an investigation of implications and applications highlighting ChatGPT’s code-assistance capabilities. Through a series of analyses, we discuss the real impact of ChatGPT on open source software development. However, apart from offering efficiency and innovation, ChatGPT mandates a careful and well-informed approach to integration into software development paradigms.
{"title":"ChatGPT for Software Development: Opportunities and Challenges","authors":"Wahyu Rahmaniar","doi":"10.1109/mitp.2024.3379831","DOIUrl":"https://doi.org/10.1109/mitp.2024.3379831","url":null,"abstract":"Rapid natural language processing advances, such as OpenAI’s ChatGPT, promise profound transformations across multiple domains, including software development. This article discusses ChatGPT’s role in software engineering, including an investigation of implications and applications highlighting ChatGPT’s code-assistance capabilities. Through a series of analyses, we discuss the real impact of ChatGPT on open source software development. However, apart from offering efficiency and innovation, ChatGPT mandates a careful and well-informed approach to integration into software development paradigms.","PeriodicalId":49045,"journal":{"name":"IT Professional","volume":"54 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141521947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-26DOI: 10.1109/mitp.2024.3406211
{"title":"IEEE Transactions on Big Data","authors":"","doi":"10.1109/mitp.2024.3406211","DOIUrl":"https://doi.org/10.1109/mitp.2024.3406211","url":null,"abstract":"","PeriodicalId":49045,"journal":{"name":"IT Professional","volume":"22 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141531631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-26DOI: 10.1109/mitp.2024.3399485
Peter Mell, Irena Bojanova, Carlos Eduardo Galhardo
Identifying the software weaknesses exploited by attacks supports efforts to reduce developer introduction of vulnerabilities and to guide security code review efforts. A weakness is a bug or fault type that can be exploited through an operation that results in a security-relevant error. Ideally, the security community would measure the prevalence of the software weaknesses used in actual exploitation. This work advances that goal by introducing a simple metric that utilizes public data feeds to determine the probability of a weakness being exploited in the wild for any 30-day window. The metric is evaluated on a set of 130 weaknesses that were commonly found in vulnerabilities between April 2021 and March 2024. Our analysis reveals that 92% of the weaknesses are not being constantly exploited.
{"title":"Measuring the Exploitation of Weaknesses in the Wild","authors":"Peter Mell, Irena Bojanova, Carlos Eduardo Galhardo","doi":"10.1109/mitp.2024.3399485","DOIUrl":"https://doi.org/10.1109/mitp.2024.3399485","url":null,"abstract":"Identifying the software weaknesses exploited by attacks supports efforts to reduce developer introduction of vulnerabilities and to guide security code review efforts. A weakness is a bug or fault type that can be exploited through an operation that results in a security-relevant error. Ideally, the security community would measure the prevalence of the software weaknesses used in actual exploitation. This work advances that goal by introducing a simple metric that utilizes public data feeds to determine the probability of a weakness being exploited in the wild for any 30-day window. The metric is evaluated on a set of 130 weaknesses that were commonly found in vulnerabilities between April 2021 and March 2024. Our analysis reveals that 92% of the weaknesses are not being constantly exploited.","PeriodicalId":49045,"journal":{"name":"IT Professional","volume":"31 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141521957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-26DOI: 10.1109/mitp.2024.3371155
Hazim Shakhatreh, Wa’ed Malkawi, Ala Al-Fuqaha
Unlike terrestrial wireless stations, using drones as aerial wireless stations allows for improved wireless services due to their 3-D mobility. Therefore, model interactions play a pivotal role in determining the locations and trajectories of drones and their performance. In this article, we discuss the interactions between models in the Internet of Drones under different real-life scenarios. The models include channel path loss, intelligent reflecting surface placement, solar energy, wireless power transfer, and power consumption. Moreover, we discuss learned lessons and highlight future research directions relevant to these models.
{"title":"An Optimization Perspective on the Interactions Between Models in the Internet of Drones","authors":"Hazim Shakhatreh, Wa’ed Malkawi, Ala Al-Fuqaha","doi":"10.1109/mitp.2024.3371155","DOIUrl":"https://doi.org/10.1109/mitp.2024.3371155","url":null,"abstract":"Unlike terrestrial wireless stations, using drones as aerial wireless stations allows for improved wireless services due to their 3-D mobility. Therefore, model interactions play a pivotal role in determining the locations and trajectories of drones and their performance. In this article, we discuss the interactions between models in the Internet of Drones under different real-life scenarios. The models include channel path loss, intelligent reflecting surface placement, solar energy, wireless power transfer, and power consumption. Moreover, we discuss learned lessons and highlight future research directions relevant to these models.","PeriodicalId":49045,"journal":{"name":"IT Professional","volume":"134 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141521958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-26DOI: 10.1109/mitp.2024.3398871
{"title":"IEEE Computer Society Has You Covered!","authors":"","doi":"10.1109/mitp.2024.3398871","DOIUrl":"https://doi.org/10.1109/mitp.2024.3398871","url":null,"abstract":"","PeriodicalId":49045,"journal":{"name":"IT Professional","volume":"57 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141531625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-26DOI: 10.1109/mitp.2024.3399471
Nir Kshetri
This article examines the significant energy and water resources required for the training and utilization of artificial intelligence (AI) systems, which consequently result in substantial social costs. Additionally, it explores AI’s contributions to enhancing energy efficiency.
{"title":"The Environmental Impact of Artificial Intelligence","authors":"Nir Kshetri","doi":"10.1109/mitp.2024.3399471","DOIUrl":"https://doi.org/10.1109/mitp.2024.3399471","url":null,"abstract":"This article examines the significant energy and water resources required for the training and utilization of artificial intelligence (AI) systems, which consequently result in substantial social costs. Additionally, it explores AI’s contributions to enhancing energy efficiency.","PeriodicalId":49045,"journal":{"name":"IT Professional","volume":"204 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141521952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-26DOI: 10.1109/mitp.2024.3404229
George Strawn
Deep learning and generative artificial intelligence originated in 1943, which preceded our age of digital computers. These origins focused on understanding the functioning of the brain and creating an artificial model of it. The three masterminds who initiated this now very important strand of IT technology are highlighted and the elements of their inventions are outlined.
深度学习和生成式人工智能起源于 1943 年，早于我们的数字计算机时代。这些起源的重点是了解大脑的功能，并创建大脑的人工模型。本文重点介绍了开创这一当今非常重要的 IT 技术领域的三位大师，并概述了他们的发明要素。
{"title":"Where Deep Learning and Generative AI Started: Masterminds of Artificial Neural Networks—McCulloch, Pitts, and Rosenblatt","authors":"George Strawn","doi":"10.1109/mitp.2024.3404229","DOIUrl":"https://doi.org/10.1109/mitp.2024.3404229","url":null,"abstract":"Deep learning and generative artificial intelligence originated in 1943, which preceded our age of digital computers. These origins focused on understanding the functioning of the brain and creating an artificial model of it. The three masterminds who initiated this now very important strand of IT technology are highlighted and the elements of their inventions are outlined.","PeriodicalId":49045,"journal":{"name":"IT Professional","volume":"14 1","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141521955","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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