Abstract
The grown adoption of mobile devices makes the development of applications a very attractive market. On top of it, run tests is a crucial activity and a big challenge due to the high fragmentation on Android ecosystem. In this paper, we discuss how a new platform based on Collaborative Economy could be used to create a new alternative to software testing. We present an analysis of using this platform and we confirm its advantages over existing cloud solutions, from a scalability and cost viewpoints. Our solution can provide an average cost reduction upper to 85% and a potential increasing in scalability.

Abstract
Poorly executed requirements engineering activities profoundly affect the deliverables’ quality and project’s budget and schedule. High-quality requirements reuse through requirement patterns has been widely discussed to mitigate these adverse outcomes. Requirement patterns aggregate similar applications’ behaviors and services into well-defined templates that can be reused in later specifications. The abstraction capabilities of metamodeling have shown promising results concerning the improvement of the requirement specifications’ quality and professionals’ productivity. However, there is a lack of research on requirement patterns beyond requirements engineering, even using metamodels as the underlying structure. Besides, most companies often struggle with the cost, rework, and delay effects resulting from a weak alignment between requirements and testing. In this paper, we present a novel metamodeling approach, called Software Pattern MetaModel (SoPaMM), which aligns requirements and testing through requirement patterns and test patterns. Influenced by well-established agile practices, SoPaMM describes functional requirement patterns and acceptance test patterns as user stories integrated with executable behaviors. Another novelty is the evaluation of SoPaMM’s quality properties against a metamodel quality evaluation framework. We detail the evaluation planning, discuss evaluation results, and present our study’s threats to validity. Our experience with the design and evaluation of SoPaMM is summarized as lessons learned.

Abstract
Cloud computing promises high dynamism, flexibility, and elasticity of applications at lower infrastructure costs. However, resource management, portability, and interoperability remain a challenge for cloud application users, since the current major cloud application providers have not converged to a standard interface, and the deployment supporting tools are highly heterogeneous. Besides, by their very nature, cloud applications bring serious traceability, security and privacy issues. This position paper describes a research thread on an extensible Domain Specific Language (DSL), a platform for the automated deployment, and a generic architecture of an ops application manager for self-adaptive distributed applications on hybrid cloud infrastructures. The idea is to overcome the cited limitations by empowering the cloud applications with self-configuration, self-healing, and self-protection capabilities. Such autonomous governance can be achieved by letting cloud users define their policies concerning security, data protection, dependability and functional compliance behavior using the proposed DSL. Real world trials in different application domains are discussed.

Abstract
Fault localization has been one of the most expensive activity in the whole debugging process. The spectrum-based fault localization (SBFL) is the most studied and evaluated technique. Other approach is the mutation-based fault localization technique (MBFL) that needs to execute the test suite on a large amount of mutants increasing its cost. Efforts from research community have been performed in order to achieve solutions reducing such cost and keeping a minimum quality. Current mutation execution strategies are evaluated considering artificial faults. However, recent researches show that some MBFL techniques exhibit low efficacy fault localization when evaluated on real faults. In this paper, we propose a new mutation execution strategy based on failed tests’ mutation score, called (FTScMES), aiming to increase the efficacy on fault localization reducing the cost of mutants execution. FTScMES uses only the set of failed test cases to execute mutants and bases on mutation score concept to compute the suspiciousness statements. The experiments were conducted considering 221 real faults, comparing the efficacy of localization of FTScMES against 5 baselines from the literature. We found that FTScMES outperforms the baselines reducing the cost in 90% on average with a high efficacy of ranking defective code.

Abstract
Conducting systematic studies during a postgraduate program, such as systematic review, systematic mapping, and tertiary review, can benefit the project’s success. They provide an overview of the literature considering currently available research findings, establish baselines for other research activities, and support decisions made throughout the research project. However, there is a shortage of research that presents systematic studies experiences in supporting academic projects. This paper’s main contribution is reporting our experience on how the evidence found in tertiary and secondary studies positively influenced a PhD project’s decisions. Initially, a tertiary study was conducted, followed by a systematic mapping. The evidence returned by the tertiary study led to the definition of the PhD research proposal in the Requirement Engineering field. Moreover, a systematic mapping contributed to the definition of the PhD research problem. From this experience in undertaking systematic studies to support a PhD project, the paper also presents lessons learned and recommendations to guide PhD students’ decisions.

Abstract