Soft Computing Approaches to Continuous Software Engineering
1China University of Petroleum, Beijing, China
2North China University of Technology, Beijing, China
3Namal Institute, Mianwali, Pakistan
Soft Computing Approaches to Continuous Software Engineering
Description
Software processes are progressively distributed and are becoming dynamic component-based, and complex. Numerous current challenges in the field are mainly based on continuous delivery, continuous integration, automation, infrastructure-as-code, etc. Different intelligent approaches and techniques are needed to cope with these challenges. Soft computing is an approach to computing that parallels the remarkable ability of the human mind to learn and reason in imprecision and in uncertain environments. Soft computing approaches acknowledge the existence of uncertainty and imprecision present in the software process. Soft computing approaches have emerged as a contributing means to address various applied modern software process management and improvement challenges including effort estimation, defect prediction, defect classification, and software reengineering. In intelligent continuous software process management and improvement, artificial intelligence techniques have been frequently applied to build intelligent tools from software artifacts.
Unfortunately, the applications of soft computing approaches in modern continuous software development are far away from being advanced. Major soft computing approaches applied to continuous software process management and improvement are currently fuzzy sets, fuzzy logic, neural networks, genetic algorithms, case-based reasoning, simulated annealing, evolutionary computation, swarm, and ant colony optimization. These techniques could provide a new avenue to manage and improve software processes.
The aim of this Special Issue is to attract original research articles and review articles presenting strategies and evidence of software engineering using soft computing approaches. Submissions can suggest new tools, methods, approaches, and frameworks. We hope both researchers and practitioners can discuss the suitability of soft computing approaches to continuous software processes.
Potential topics include but are not limited to the following:
- Application of multi-criteria decision making to continuous software engineering
- Profiling pre-release software products and organizational performance using soft computing
- Application of soft computing to modern continuous process improvement
- Industry best practices and case studies of continuous software engineering
- Application of fuzzy set optimization in continuous software development
- Artificial intelligence for industrial self-healing measurement systems
- Process management in global and outsourced software development
- Continuous integration and data-driven software development
- Scaling agile mechatronics using soft computing techniques
- Application of soft computing techniques to enterprise agile
- Managing agile processes using soft computing techniques
- Information processing in continuous software processes
- Kaizen continuous improvement
- Lean start-ups and lean thinking
- DevOps pipeline automation