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Submission Preparation Checklist

As part of the submission process, authors are required to check off their submission's compliance with all of the following items, and submissions may be returned to authors that do not adhere to these guidelines.
  • The submission has been prepared in accordance with the journal's Instructions for Authors and follows all the journals' policy requirements.
  • The submission file is in Microsoft Word format.
  • All co-authors must be included at the time of submission with valid e-mail addresses.
  • No part of the manuscript has been, or will be, published elsewhere nor is under consideration for publication elsewhere.

Author Guidelines

We welcome the following types of contributions:

1. Full-length and letter-length papers describing original research and/or novel applications
2. Well researched review/survey articles
3. Work-in-progress reports on promising developments
4. Case studies and best practice articles prepared by industry experts
5. Tutorials on up-and-coming technological breakthroughs

It is expected that 80% of published contents would fall under categories 1) and 2). Although categories 3)-5) should make up only 20% of published contents, category 3) is intended to be an important feature of the journal. It will be a venue for publishing ‘spot the trend’ or ‘you saw it here first’ types of contributions. This reinforces the forward looking nature of the journal

We expect readers and contributors to come from the wide spectrum of computing/IT communities including academic and industrial researchers, industrial managers and practitioners, IT consultants, educators, and employees of related government agencies, as well as policy makers in the public and private sectors.

Submitted papers are assumed to contain no proprietary material unprotected by patent or patent application; responsibility for technical content and for protection of proprietary material rests solely with the author(s) and their organizations and is not the responsibility of JAIT or its Editorial Staff. The main author is responsible for ensuring that the article has been seen and approved by all the other authors. It is the responsibility of the author to obtain all necessary copyright release permissions for the use of any copyrighted materials in the manuscript prior to the submission.

Topic: Software Design and Program Development

Software Design and Program Development play a key role in the software development process. Different methods are used for architecture design and detailed design evaluation. The topics include but are not limited to:

Computer programming languages and programming          Parallel programming
Software structure design   Software quality assessment
Software analysis methods and tools   Debugging
Software requirements analysis   Application Testing and Design
Test case design and execution   Testing Application Vulnerabilities
Software modeling and analysis   Software testing in IoT (Internet of Things)
Software design and estimation   Importance of agile and DevOps principles
Software frameworks and architectural   Security testing tool
Architectural and design patterns   Software testing, diagnosis, and validation
Software process models   Design principles
Project management   Software performance
Software testing to combat cybersecurity and risk compliance   Machine learning and artificial intelligence to enhance automated software testing

Topic: Machine Learning in computer and information systems

Machine learning is the process of a computer modeling human intelligence, and autonomously improving over time. Machines are able to make predictions about the future based on what they have observed and learned in the past. The topics include but are not limited to:

Logistic Regression   Decision Tree
k-Means       Nearest Neighbors
Principal Component Analysis   Hierarchical Naïve Bayes
Random Forest   Support Vector Machine
Reinforcement learning   Unsupervised learning
Supervised learning   Deep learning
Self-Organizing Maps   Topic model
Dimensionality reduction   Artificial Neural Networks
Deep Neural Network   K-nearest neighbor
Linear regression   Canonical correlation analysis


Privacy Statement

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Permissions for Reproducing Published Material in Your Work

Authors are responsible for obtaining permission to reproduce any published material (figures, schemes, tables or any extract of a text) which does not fall into the public domain, or for which they do not hold the copyright. Permission should be requested by the authors from the copyright holder (usually the Publisher, please refer to the imprint of the individual publications to identify the copyright holder). The copyright holder may give you instructions on the form of acknowledgment to be followed; otherwise, follow the style: "Reproduced with permission from [author], [journal title]; published by [publisher], [year], [reference number].” at the end of the caption of the Table or Figure.

In order to avoid unnecessary delays if the publication process, authors should start obtaining permission as early as possible. When submitting your article, please upload the permission together with the rest of your files.