Abstract
The sports facilities that offer regular sports services have been adopting ERP and CRM systems and there are now databases with historical data of great value. In this work, we demonstrate that by applying predictive models to these data it is possible to identify abandonment profiles. Based on the profiles found, experience planning is carried out, with test and control groups, in order to find concrete actions of loyalty.

Abstract
Mutation Testing has been proved to be effective in detecting faults. However, it suffers from the large number of mutants generated and analyzed when we apply the operators to create mutants. To alleviate this problem, this paper proposes an approach to find a reduced set of mutation operators that reduces the generated mutants and maintains the test effectiveness. Our approach adapts the semantic characterization of faults in order to find this set of mutation operators that will reduce the cost of Mutation Testing. The experimental results indicate that our approach is able to find a set of operators that reduce the mutation cost while maintaining the test effectiveness.

Abstract
Unit testing is an important component of software quality improvement. Several researchers proposed automated tools to improve this activity over the years. However, these research efforts have not been sufficient to help the practitioners to address some associated mental tasks. Motivated by this gap, we conducted a qualitative study of professionals with unit testing experience. The goal was to understand how to improve the cognitive support provided by the testing tools, by considering the practitioners’ perspective on their unit testing review practices. We obtained the responses from our volunteers through a questionnaire composed both of open-ended and closed questions. Our results revealed some primary tasks which require cognitive support, including monitoring of pending and executed unit testing tasks, and navigating across unit testing related artifacts. We summarize our results in a framework, and based on it, we develop a research agenda as an actionable instrument to the community. Our study's contributions comprise practical improvement suggestions for the current tools and describe further opportunities for research in software testing. Moreover, we comprehensively explain our qualitative methods.

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
Fault localization has been one of the most manual and costly software debugging activities. The spectrum-based fault localization is the most studied and evaluated fault localization approach. Mutation-based fault localization is a promising approach but with a high computational cost. We propose a novel mutation execution strategy named Failed-Test Oriented Mutant Execution Strategy (FTMES) for improving the efficacy of fault localization techniques and also reduce the computational cost of these techniques. Our proposed approach and eight other baselines were evaluated against 221 real faults. The results show that FTMES outperformed others with respect to efficiency (computational cost) while maintaining similar accuracy.

Abstract