Journal Information
Journal of Systems and Software (JSS)
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Call For Papers
The Journal of Systems and Software publishes papers covering all aspects of programming methodology, software engineering, and related hardware-software-systems issues. Topics of interest include, but are not limited to, software development environments and tools, techniques for developing, validating, and maintaining software systems, software architecture and design, global software development, service orientation, agile approaches, mobile, multiprocessing, real-time, distributed, concurrent, and telecommunications systems, software metrics, reliability models for software, performance issues, and management concerns. The journal publishes research papers, state-of-the-art surveys, and reports of practical experience. All articles should consider the practical application of the idea advanced through case studies, experiments, or systematic comparisons with other approaches already in practice. Occasionally, special issues are devoted to topics of particular interest; proposals for such issues are invited.

Last updated by Dou Sun in 2018-07-23
Special Issues
Special Issue on Machine Learning Techniques for Software Quality Evaluation
Submission Date: 2019-11-15

The assessment of software quality is one of the most multifaceted (e.g., structural quality, product quality, process quality, etc.) and subjective aspects of software engineering (since in many cases it is substantially based on expert judgement). Such assessments can be performed at almost all phases of software development (from project inception to maintenance) and at different levels of granularity (from source code to architecture). However, human judgment is: (a) inherently biased by implicit, subjective criteria applied in the evaluation process, and (b) its economical effectiveness is limited compared to automated or semiautomated approaches. To this end, researchers are still looking for new, more effective methods of assessing various qualitative characteristics of software systems and the related processes. In recent years, we have been observing a rising interest in adopting various approaches to exploiting machine learning (ML) and automated decision-making processes in several areas of software engineering. These models and algorithms help to reduce effort and risk related to human judgment in favour of automated systems, which are able to make informed decisions based on available data and evaluated with objective criteria. Thus, the adoption of machine learning techniques seems to be one of the most promising ways to improve software quality evaluation. Conversely, learning capabilities are increasingly often embedded within software, including in critical domains such as automotive and health. This calls for the application of quality assurance techniques to ensure the reliable engineering of ML-based software systems. As such, the special issue invites submissions on new and innovative research results and industrial experience papers in the area of machine learning applications for software quality evaluation. We especially encourage submission of extended papers from the 3rd International Workshop on Machine Learning Techniques for Software Quality Evaluation (MaLTeSQuE 2019). Submissions could deal with all aspects of the problem, including, but not limited to, the following topics of interest: • Application of machine-learning in software quality evaluation, • Analysis of multi-source data, • Knowledge acquisition from software repositories, • Adoption and validation of machine learning models and algorithms in software quality, • Decision support and analysis in software quality, • Prediction models to support software quality evaluation, • Validation and verification of learning systems, • Automated machine learning, • Design of safety-critical learning software, • Integration of learning systems in software ecosystems.
Last updated by Dou Sun in 2019-07-27
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