The concurrent development of applications requires reconciling conflicting code updates by different developers. Recent research on the nature of merge conflicts in open source projects shows that a significant fraction of merge conflicts have limited size (one or two lines of code) and are resolved with simple strategies that use code present in the merged versions. Thus the opportunity arises of supporting the resolution of merge conflicts automatically by learning the way in which developers fix them. In this paper we propose a framework for automating the resolution of merge conflicts which learns from the resolutions made by developers and encodes such knowledge into conflict resolution rules applicable to conflicts not seen before. The proposed approach is text-based, does not depend on the programming languages of the merged files and exploits a well-known and general language (search and replacement regular expressions) to encode the conflict resolution rules. Evaluation results on 14,872 conflicts from 25 projects show that the system can synthesize a resolution for$\approx$49% of the conflicts occurred during the merge process ($\approx$89% if one considers conflicts that have at least one similar conflict in the data set) and can reproduce exactly the same solution that human developers have applied in$\approx$55% of the cases ($\approx$62% for single line conflicts).

Gamification is defined as the injection of game elements in applications with non-gaming purposes.This technique has shown outstanding results in promoting the engagement and activity on communities of users, in both business and non-for-profits fields.Often, gamification features are added late in the application life-cycle and must be weaved into the existing functions.In this paper, we present a model-driven approach to the design of gamified applications, which accelerates the introduction of gamification elements in pre-existing or new applications.The approach relies on a data model of gamification features and on design patterns for the front-end, which encode the essential elements of gamification in a platform independent way.

Model Driven Development (MDD) requires proper tools to derive the implementation code from the application models. However, the integration of handwritten and generated code is a long-standing issue that affects the adoption of MDD in the industry. This article presents a model and code co-evolution approach that addresses such a problem a posteriori , using the standard collision detection capabilities of Version Control Systems to support the semi-automatic merge of the two types of code. We assess the proposed approach by contrasting it with the more traditional template-based, forward-engineering process, adopted by most MDD tools.