The Artificial Intelligence Tools in Software and Data Engineering (AITSDE) is an international, scientific, peer-reviewed, and open-access e-journal on all aspects of theoretical background and advanced engineering approaches in machine learning, data science and their application in software engineering. It is published quarterly and accepts only manuscripts written in English. The aim of AITSDE is to bring together interdisciplinary research in the fields of data science and software engineering.
Three types of papers will be published:
- Research papers and research notes reporting original research results
- Technology trend reviews reviewing an area of research in software engineering and data engineering
- Survey articles surveying a broad area in software engineering and data engineering
- Tool reviews and book reviews are also welcome.
The journal publishes papers in the following areas but are not restricted to these areas:
A central theme of this journal is the interplay between software engineering and Data engineering: how Data engineering methods can be applied to software engineering, and vice versa.
Software Engineering Methods and Practices such as
- ambiguity in software development
- cleanroom software engineering
- formal methods of specification
- impact of CASE on software development life cycle
- object-oriented systems
- rapid prototyping
- software reuse
- stepwise refinement/enhancement
- Process and workflow management
- Program understanding and system maintenance
- Reflection and metadata approaches
- Software engineering techniques and production perspectives
- Software analysis, design and modelling
- Software Engineering Methodologies
- Software design patterns
- Software domain modelling and analysis
- Software engineering case study and experience reports
- Software engineering tools and environments
- Software maintenance and evolution
- Software product lines
- Reverse engineering
- Search-based software engineering
Artificial Intelligence
- Artificial intelligent methods, models and techniques
- Artificial life and societies
- Smart spaces
- Swarm intelligence
Data Modelling, Mining and Data Analytics
- Data analytics modelling and algorithms
- Data mining methods, techniques and tools
- Data modelling, aggregation, integration and transformation
- Data visualization
- Patterns and frameworks
- Web and text mining
Artificial intelligence and data Science application in following topics
- SOA and Service-Oriented Systems
- Discovery and composition service level agreements
- Middleware for service based systems
- Runtime service management
- Service oriented architectures service
- Service oriented requirements engineering
- Software & System Quality of Service
- Quality assurance process, and systems
- Soft computing
- Software and system testing methods
- Software dependability, reliability, scalability
- Software safety systems
- Software test automation and tools
- Software Engineering
- Artificial intelligence approaches to software engineering
- Enterprise software, middleware and tools
- Requirements engineering
Software engineering decision support