Proactive Empirical Assessment of New Language Feature Adoption via Automated Refactoring: The Case of Java 8 Default Methods

Programming languages and platforms improve over time, sometimes resulting in new language features that offer many benefits. However, despite these benefits, developers may not always be willing to adopt them in their projects for various reasons. In this paper, we describe an empirical study where we assess the adoption of a particular new language feature. Studying how developers use (or do not use) new language features is important in programming language research and engineering because it gives designers insight into the usability of the language to create meaning programs in that language. This knowledge, in turn, can drive future innovations in the area. Here, we explore Java 8 default methods, which allow interfaces to contain (instance) method implementations. Default methods can ease interface evolution, make certain ubiquitous design patterns redundant, and improve both modularity and maintainability. A focus of this work is to discover, through a scientific approach and a novel technique, situations where developers found these constructs useful and where they did not, and the reasons for each. Although several studies center around assessing new language features, to the best of our knowledge, this kind of construct has not been previously considered. Despite their benefits, we found that developers did not adopt default methods in all situations. Our study consisted of submitting pull requests introducing the language feature to 19 real-world, open source Java projects without altering original program semantics. This novel assessment technique is proactive in that the adoption was driven by an automatic refactoring approach rather than waiting for developers to discover and integrate the feature themselves. In this way, we set forth best practices and patterns of using the language feature effectively earlier rather than later and are able to possibly guide (near) future language evolution. We foresee this technique to be useful in assessing other new language features, design patterns, and other programming idioms

Research Phases of University Data Mining Project Development

Educational Data Mining becomes one of the challenging new research fields where data mining methods and tools could help universities in taking timely and data analysis based management decisions, thus contributing to gaining competitive advantages in their successful policy introduction. This paper presents the research activities performed for the implementation of a data mining project initiated in one of the most prestigious Bulgarian universities. The project main goal is to reveal the high potential of data mining applications for university management, referring to the optimal usage of data mining methods and techniques to deeply analyze the collected historical data. That will lead to better understanding the student behavior and building well structured educational process that meets the university policy and supports the management decision making process

The RISCOSS platform for risk management in open source software adoption

Managing risks related to OSS adoption is a must for organizations that need to smoothly integrate OSS-related practices in their development processes. Adequate tool support may pave the road to effective risk management and ensure the sustainability of such activity. In this paper, we present the RISCOSS platform for managing risks in OSS adoption. RISCOSS builds upon a highly configurable data model that allows customization to several types of scopes. It implements two different working modes: exploration, where the impact of decisions may be assessed before making them; and continuous assessment, where risk variables (and their possible consequences on business goals) are continuously monitored and reported to decision-makers. The blackboard-oriented architecture of the platform defines several interfaces for the identified techniques, allowing new techniques to be plugged in.Peer ReviewedPostprint (author’s final draft

‘Follow the Moon’ Development: Writing a Systematic Literature Review on Global Software Engineering Education

This presentation reflects on method and practice in Computer Science Education Research, through introducing the process of conducting a Systematic Literature Review. While Systematic Literature Reviews are an established research method within the Software Engineering discipline, they are a relatively unfamiliar research approach within Computer Science Education. Yet research disciplines can be strengthened by borrowing and adapting methods from other fields. I reflect on the rationale and underlying philosophy behind Systematic Reviews, and the implications for conducting a rigorous study and the quality of the resulting outputs. This chronicle of the journey of an ITiCSE working group, outlines the process we adopted and reflects on the methodological and logistical challenges we had to overcome in producing a review titled Challenges and Recommendations for the Design and Conduct of Global Software Engineering Courses. I conclude by discussing how systematic literature reviews can be adapted to an undergraduate teaching setting