MLSE is an initiative in Japan to tackle the emerging challenges in engineering systems built using machine-learning techniques. Since April 2018, MLSE is run as a Special Interest Group (SIG) in Japan Society for Software Science and Technology (JSSST).

There is increasing interest in machine learning (ML) techniques and their applications. Although it is facilitated for the industry to construct ML models by using libraries and frameworks, engineering disciplines have not been established. The source of emerging difficulties is the shift of the development paradigm. Classically, we have constructed software systems in a deductive way, or by writing down the rules that govern the system behaviors as program code. With machine learning techniques, we generate such rules in an inductive way from training data. This shift does not only simply require new tools that intensively deal with data but also introduces unique characteristics. The resulting system behaviors are uncertain: black-box and unexplainable. They are intrinsically imperfect and it is practically impossible to reason their correctness in a deductive way. Thus, many of existing disciplines in software engineering do not work for ML-based systems.

MLSE has been providing venues where researchers and practitoners, from different areas of SE and ML/AI as well as the academia and industry, meet and discuss together to tackle the challenges and establish new disciplines.

Although most of the MLSE activities are Japanese local , there have been also international activities.

Events

• iMLSE 2018 (in conjunction with APSEC 2018)
• Joint Event with SEMLA in May 2019

Publications

• How do Engineers Perceive Difficulties in Engineering of Machine-Learning Systems? - Questionnaire Survey (by Fuyuki Ishikawa and Nobukazu Yoshioka, a preprint of a paper in CESSER-IP 2019 at ICSE 2019) (pdf)

More information on Japanese local activities are found here.