Dear Colleagues,

With the rapid advance of machine learning technologies and the growth in their applications, there is a grave challenge in the engineering of software systems that include components that are developed by employing machine learning techniques. It has been particularly active in the testing of ML models, for example, testing on their robustness through generating adversarial example test cases, testing on ML’s fairness and trustworthiness, and measuring their performances, etc. However, many research questions remain open. For example, how to ensure the quality of ML components on correctness, reliability, robustness, fairness; how to support the evolution of such systems, especially the ML components, and to improve the quality of such components based on test results and user feedbacks; what are the right process models for such systems, for example, how to integrate machine learning processes with traditional software engineering processes. We question whether it is possible to develop an integrated software development environment such as IDE so that the development of both ML components and traditional code can be supported. These are just a few examples of open research questions.

On the other hand, machine learning offers a great opportunity to revolutionize software engineering practices. For example, research has been reported in the literature on the employment of machine learning to generate program code, to locate and remove code bugs, to generate test cases, to understand user feedbacks on mobile apps, to resolve confliction in software merge, to mine software repositories, to generation comments on program code, etc. There are many potential applications of ML to software engineering to be explored.

The purpose of the Special Issue is to be a forum to publish scientific research papers that reflect the current state of the art in the research and practice of the synergy of software engineering and machine learning and to project a vision on the future directions in the subject area. The scope of the Special Issue covers both fields of applying ML to software engineering problems, and software engineering of ML applications. We welcome all original papers that report theoretical research, empirical study, reflection on practical case uses and experiences, evidence based visionary works, and survey and critical review of the current state of the art.

Prof. Dr. Hong Zhu
Guest Editor

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• software engineering of machine learning
• machine learning application to software engineering