PROGRAMMING AND COMPUTER SOFTWARE

Scope & Guideline

Pioneering Research in Programming and Software Solutions

Introduction

Welcome to your portal for understanding PROGRAMMING AND COMPUTER SOFTWARE, featuring guidelines for its aims and scope. Our guidelines cover trending and emerging topics, identifying the forefront of research. Additionally, we track declining topics, offering insights into areas experiencing reduced scholarly attention. Key highlights include highly cited topics and recently published papers, curated within these guidelines to assist you in navigating influential academic dialogues.
LanguageEnglish
ISSN0361-7688
PublisherPLEIADES PUBLISHING INC
Support Open AccessNo
CountryUnited States
TypeJournal
Convergefrom 1978 to 1992, from 1996 to 2024
AbbreviationPROGRAM COMPUT SOFT+ / Program. Comput. Softw.
Frequency6 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
AddressPLEIADES HOUSE, 7 W 54 ST, NEW YORK, NY 10019, UNITED STATES

Aims and Scopes

The journal 'Programming and Computer Software' focuses on the intersection of theoretical foundations and practical applications in computer science. It aims to publish high-quality research that advances the field of programming and software engineering through innovative methodologies and techniques.
  1. Software Development and Engineering:
    The journal emphasizes research in software development methodologies, tools, and practices, including agile development, software testing, and requirements engineering.
  2. Algorithms and Computational Methods:
    A significant focus is placed on the design, analysis, and implementation of algorithms, particularly in the context of optimization, numerical methods, and computational complexity.
  3. Artificial Intelligence and Machine Learning:
    Research in AI and ML is prominent, covering topics like neural networks, deep learning, and machine learning applications in various domains including image processing and data analysis.
  4. Computer Algebra Systems:
    The journal publishes work related to computer algebra, symbolic computation, and their applications in solving complex mathematical problems.
  5. Data Science and Analytics:
    There is a growing emphasis on data science, including methods for data mining, machine learning applications, and statistical analysis techniques.
  6. Cybersecurity and Cryptography:
    Research on software security, vulnerabilities, and cryptographic methods is a core area, reflecting the increasing importance of secure software systems.
Recent years have seen the emergence of several trending research themes within the journal, reflecting shifts in technology and research focus areas.
  1. Machine Learning and Deep Learning Applications:
    There is a substantial increase in research related to machine learning and deep learning, particularly their applications in image processing, natural language processing, and predictive analytics.
  2. Cybersecurity Innovations:
    With the growing concern over data breaches and cyber threats, innovative research in cybersecurity practices, including secure coding and cryptographic techniques, has gained traction.
  3. Cloud Computing and Distributed Systems:
    Research focusing on cloud computing architectures, distributed ledger technologies, and edge computing solutions is on the rise, driven by the demand for scalable and efficient systems.
  4. Human-Computer Interaction and Usability:
    Emerging studies on user experience, usability testing, and human-computer interaction design are becoming increasingly significant, as software applications prioritize user-centered design.
  5. Quantum Computing and Advanced Algorithms:
    There is a growing interest in quantum computing, with research exploring its implications for algorithms and software development, reflecting a frontier in computational capabilities.

Declining or Waning

While the journal continues to evolve, some themes have shown a decline in publication frequency or relevance. This indicates a shift in research focus or a saturation of previous topics.
  1. Traditional Software Engineering Models:
    There has been a noticeable decrease in the number of publications focusing on traditional software engineering models, as newer methodologies such as agile and DevOps gain prominence.
  2. Static Analysis Techniques:
    Although static analysis remains important, the volume of research dedicated to basic static analysis methods has diminished, possibly due to advancements in dynamic analysis and machine learning techniques.
  3. Classic Database Management Systems:
    Research on classical database systems and their optimization techniques is less frequent, overshadowed by the rise of NoSQL databases and big data frameworks.
  4. Basic Computer Graphics Techniques:
    Publications on fundamental computer graphics techniques have declined, as the field has moved towards more complex and advanced rendering techniques.
  5. Legacy Programming Languages:
    There is a waning interest in research focused on legacy programming languages, as newer languages and paradigms become more relevant in current software development practices.

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