ACM COMPUTING SURVEYS
Scope & Guideline
Navigating the Landscape of Computing Discourses
Introduction
Aims and Scopes
- Comprehensive Surveys:
The journal publishes extensive surveys that synthesize and analyze significant research areas, offering insights into the methodologies, challenges, and future research directions. - Interdisciplinary Research:
ACM CSUR encourages submissions that span across various disciplines within computing, integrating insights from areas such as artificial intelligence, cybersecurity, software engineering, and data science. - Emerging Technologies:
The journal focuses on emerging technologies and trends, providing critical evaluations and discussions on their potential impacts and applications. - Methodological Rigor:
Papers published in ACM CSUR are expected to demonstrate methodological rigor, ensuring that the surveys are not only informative but also grounded in established research practices. - Community Engagement:
The journal aims to facilitate discourse within the research community by highlighting ongoing debates, proposing future research trajectories, and addressing gaps in existing literature.
Trending and Emerging
- Artificial Intelligence and Machine Learning:
There is a significant increase in surveys regarding AI and machine learning applications across various domains, highlighting their transformative impact on industries and research. - Cybersecurity and Privacy:
The growing concern over data breaches and cyber threats has led to a surge in publications focusing on cybersecurity measures, privacy-preserving technologies, and resilience against attacks. - Edge Computing and IoT:
Research on edge computing and the Internet of Things (IoT) is gaining momentum, driven by advancements in distributed computing and the need for real-time processing. - Blockchain and Decentralization:
Emerging trends in blockchain technology, particularly in its applications beyond cryptocurrency, are increasingly covered, reflecting its potential in various sectors. - Explainable AI and Fairness:
With the rise of AI applications, there is an expanding focus on explainability, interpretability, and fairness in machine learning algorithms to ensure ethical and transparent practices.
Declining or Waning
- Traditional Software Engineering Practices:
There has been a noticeable decrease in surveys focusing on conventional software engineering practices, possibly due to the shift towards more agile and DevOps methodologies. - Legacy Systems and Technologies:
Research related to legacy systems is becoming less prominent as newer technologies and systems architecture gain traction in both academic and industrial contexts. - Static Analysis Tools:
Surveys on static analysis tools have seen a decline, which may indicate a shift towards more dynamic, real-time analysis methods in software development. - Hardware-Centric Research:
There is a waning interest in traditional hardware-centric research topics as the focus shifts increasingly towards software-defined solutions and cloud-based architectures.
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