Abstract
Flexibility requirements can appear in the middle of a software development, perceived by several client requests to change the application. A flexible domain model, usually implemented with using the adaptive object model (AOM) architectural style, required custom-made components to handle the current implementation of the domain entities. The problem is that by evolving an AOM model, the components need to be evolved as well, which generates constant rework. This work studied the possible AOM evolution paths, in order to provide support in the components for model changing. An evolution of the Esfinge AOM RoleMapper framework were developed to provide this functionality, allowing AOM models in different stages to be mapped to a single structure. The study was evaluated using a set of tests that were applied in each possible structure for the model.

Abstract
Application frameworks are a powerful technique for large-scale reuse, but require a considerable effort to understand them. Good documentation is costly, as it needs to address different audiences with disparate learning needs. When code and documentation prove insuficient, developers turn to their network of experts. Nevertheless, this proves difficult, mainly due to the lack of expertise awareness (who to ask), wasteful interruptions of the wrong people and unavailability ( either due to intrusion or time constraints). The DRIVER platform is a collaborative learning environment where framework users can, in a non-intrusive way, store and share their learning knowledge while following the best practices of framework understanding (patterns). Developed by the authors, it provides a framework documentation repository, mounted on a wiki, where the learning paths of the community of learners can be captured, shared, rated, and recommended. Combining these social activities, the DRIVER platform promotes collaborative learning, mitigating intrusiveness, unavailability of experts and loss of tacit knowledge. This paper presents the assessment of DRIVER using a controlled academic experiment that measured the performance, effectiveness and framework knowledge intake of MSc students. The study concluded that, especially for novice learners, the platform allows for a faster and more effective learning process.

Abstract
Code replication has significant drawbacks in system maintenance. Code replication can have its origins in the composition limitations of the language. Several proposals have tried to overcome these limitations. A popular one is traits. However, traits do not support state or visibility control. Static roles are also a way of composing classes that has the benefits of traits and offers state, visibility control and other advantages as block renaming. We compare both approaches on how they are used to compose classes, and how they can be used to reduce code replication caused by composition limitations. As a case study we will compare how both approaches can reduce code replication by detecting and removing code clones within the JHotDraw framework. Results show that roles are capable of reducing a larger amount of replicated code than traits.

Abstract
By designing systems as sets of modules that can be composed into larger applications, developers unleash a multitude of advantages. The promise of AOP (Aspect-Oriented Programming) is to enable developers to organize crosscutting concerns into separate units of modularity making it easier to accomplish this vision. However, AOP does not allow unit tests to be untangled, which impairs the development of properly tested independent modules. This paper presents a technique that enables developers to encapsulate crosscutting concerns using AOP and still be able to develop reusable unit tests. Our approach uses incremental testing and invasive aspects to modify and adapt tests. The approach was evaluated in a medium scale project with promising results. Without using the proposed technique, due to the presence of invasive aspects, some unit tests would have to be discarded or modified to accommodate the changes made by them. This would have a profound impact on the overall modularity and, in particular, on the reusability of those modules. We will show that this technique enables proper unit tests that can be reused even when coupled with aspect-oriented code.

Abstract
Software business continues to expand globally, highly motivated by the reachability of the Internet and possibilities of Cloud Computing. While widely adopted, development for the cloud has some intrinsic properties to it, making it complex to any newcomer. This research is capturing those intricacies using a pattern catalog, with this paper contributing with three of those patterns: Messaging System, a message bus for abstracting service placement in a cluster and orchestrating messages between multiple services; Preemptive Logging, a design principle where services and servers continuously output relevant information to log files, making them available for later debugging failures; and Log Aggregation, a technique to aggregate logs from multiple services and servers in a centralized location, which indexes and provides them in a queryable, user friendly format. These patterns are useful for anyone designing software for the cloud, either to guide or validate their design decisions. © 2017 Copyright is held by the owner/author(s).

Abstract
Misinformation became pervasive on social media applications. The companies behind this kind of system have launched tools to avoid the problem, but some issues regarding the user behavior and proper software quality still need a forceful approach. First attempts to mitigate misinformation did not take into account user behavior and softwares requirements like learnability and accuracy, furthermore the characteristics of actors and artifacts from social media applications ecosystem has not been explored. This research aims to evaluate the usability of available tools made to combat the spread of misinformation and to verify the interrelationship between actors and artifacts from social media applications ecosystem for suggesting improvements on development of these tools.