Full Description
This book constitutes the refereed proceedings of the 21st International Conference on Product-Focused Software Process Improvement, PROFES 2020, held in Turin, Italy, in November 2020. Due to COVID-19 pandemic the conference was held virtually.
The 19 revised full papers and 3 short papers presented were carefully reviewed and selected from 68 submissions. The papers cover a broad range of topics related to professional software development and process improvement driven by product and service quality needs. They are organized in topical sections on Agile Software Development.
Contents
A Systematic Literature Review on Agile Coaching and the Role of the Agile Coach.- Agile Leadership and Agile Management on Organizational Level - A Systematic Literature Review.- A Study of the Agile Coach's Role.- impediment Management of Agile Software Development Teams.- How to integrate Security Compliance Requirements with Agile Software Engineering at Scale.- A Portfolio-Driven Development Model and its Management Method of Agile Product Line Engineering .- Lean R&D: An Agile Research and Development Approach for Digital Transformation.- Success and Failure Factors for Adopting a Combined Approach: A Case Study of Two Software Development Teams.- Sentiment Polarity and Bug Introduction.- A Practice-informed Conceptual Model for a Combined Approach of Agile, User-Centered Design, and Lean Startup.- Exploring the Microservice Development Process in Small and Medium-Sized OrganizationsIntegration of Security Standards in DevOps Pipelines.- An Industry Case StudyAn Empirical Investigation into Industrial Use of Software Metrics ProgramSoftware Startup Practices: .- Software Development in Software Startups through the Lens of the Essence Theory of Software Engineering.- Kuksa*: Self-Adaptive Microservices in Automotive Systems.- Improving a Software Modernisation Process by Differencing Migration Logs.- A Systematic-Oriented Process for Tool Selection: The Case of Green and Technical Debt Tools in Architecture Reconstruction.- From a Data Science Driven Process to Continuous Delivery Process for Machine Learning.- SystemsDemystifying Data Science Projects: a Look on the People and Process of Data Science.
