2018年机器学习软件质量评估技术研讨会

[基本信息]

会议名称:2018年机器学习软件质量评估技术研讨会

International Workshop on Machine Learning Techniques for Software Quality Evaluation

所属学科:计算机软件,人工智能

开始日期:2018-03-20

所在国家:意大利

所在城市:意大利

具体地点:意大利 Campobasso, Italy

主办单位:IEEE Computer Society 、University of Molise

[会务组联系方式]

联系电话:+39 0874 404159

E-MAIL:rocco.oliveto@unimol.it

会议网站:https://maltesque.github.io/

[会议背景介绍]

The assessment of software quality is one of the most multifaceted (e.g., structural quality, quality-in-use, product quality, process quality, etc.) and subjective aspects of software engineering (since in many cases is substantially based on expert judgement). Such assessments can be performed at all almost of phases of software development (from project inception to maintenance) and at different levels of granularity (from source code to architecture). However, human judgement is: (a) inherently biased by implicit, subjective criteria applied in the evaluation process, and (b) its economical effectiveness is limited compared to automated or semi-automated 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 favor of automated systems, which are able to make informed decisions based on available data and evaluated with objective criteria. The aim of the workshop is to provide a forum for researchers and practitioners to present and discuss new ideas, trends and results concerning the application of ML to software quality assessment. We expect that the workshop will help in: (a) validation of existing and exploring new applications of ML, (b) comparing their efficiency and effectiveness, both among other automated approaches and the human judgement, and (c) adapting ML approaches already used in other areas of science to software engineering problems.

[征文范围及要求]

Topics of interest include, but are not limited to: - 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