COSMIC Function Points Fundamentals for Software Effort Estimation COSMIC Function Points Fundamentals for Software Effort Estimation 8A0F73B81FE93E333D81BCB5B75FDA93 GROBID - A machine learning software for extracting information from scholarly documents

We welcome you all to the IWSM Mensura conference 2018 to be held in Beijing China on 19-20 September with the support of SPI China and Measures Inc. This year we particularly received proposals from experienced industry practitioners and researchers with COSMIC expertise and experience in the usage of COSMIC.

The main goal of this conference is to share experiences, challenges and solution approaches to facilitate technology transfers from best estimation-related practices developed by researchers and world industry experts. Software and IT measurement are keys for successfully managing and estimating software development projects: sound measurement techniques, such as COSMIC Function Points are essential for both business and engineering: they enrich technical knowledge regarding both the practice of software development, as well as empirical research in software technology.

Main theme and scope of this year's conference is "COSMIC Function Points: Fundamentals for Software Effort Estimation". Related areas and interests include topics like: • COSMIC usage in industry across the world, and the harvesting of the related benefits.

• COSMIC Measurement best practices • State of the art on COSMIC research achievements & technology transfers • Estimation improvements through COSMIC usage • Automation of COSMIC from source code • Automation of COSMIC from requirements • Earned-value management with COSMIC • How to implement COSMIC in Agile environments • Software Measurements Programs: Industry Experience reports. • Measuring and quantifying value • Decision support systems based on software measurement • Visualizations and dashboards In addition to the main theme, the scope of the conference also includes generic software measurement related topics like: • Measuring and quantifying value • Measurement processes and resources, e.g. agile or model-driven • Usage of big data analytics for improving products and processes • Empirical case studies • Software measurement data mining • Decision support systems based on software measurement • Data driven decision making • Visualizations and dashboards • Measurement-as-a-Service • Service-and product-oriented measures • Benchmarking General Chairs: Prof. Chen Zong Prof. Alain Abran Dylan Ren