Abstract
This paper provides evidences on the correspondence between mutations and static warnings. We used mutation operators as a fault model to evaluate the direct correspondence between mutations and static warnings. The main advantage of using mutation operators is that they generate a large number of programs containing faults of different types, which can be used to decide the ones most probable to be detected by static analyzers. Since static analyzers, in general, report a substantial number of false positive warnings, the intention of this study is to define a prioritization approach of static warnings based on the probability they correspond to a true positive and lead to detect software faults. The results obtained for a set of open-source programs indicate that a correspondence exist when considering specific mutation operators such that static warnings may be prioritized based on their correspondence level with mutations.

Abstract
Humans are hunters and love the chase - they hunt for food, they hunt for bugs in software. In the last decade, testing research has gone deeper and broader to help with the challenging task of catching bugs. Much of the literature approaches the problem from a theoretical-technical perspective and is often oriented to automated solutions. Yet, there is a gap between industry testing problems and research testing solutions. We take a different perspective and consider the human component as a major part of the solution for practical testing problems. Many of these human-related issues are reported in academic surveys of practitioners. We highlight the importance of human factors in testing by introducing a hunting metaphor. We also bring attention to evidence on cognitive support demands in unit test practices. An initial framework is proposed as an effort to bring understanding of cognitive support demands, and provides direction for further research on unit testing tools which support tester skill improvement.

Abstract
Many countries today are attempting to move into digital transformation to try to improve the efficiency of Government activities and reduce unnecessary costs. This is how the concept of the Digital Government has come to the fore. All agree on the need to guarantee the quality of digitalized services that are provided to the taxpayer. Based on this scenario, this work adapts a validation process for digitalized services, providing a systematic way for test case generation, to guarantee the quality of software products delivered to the public. Amongst the challenges met in this research work, we highlight the lack of requirements for the services analyzed and the impossibility of accessing their source code, which requires a black-box testing process. We observed, based on the results, that the adapted process allowed the validation activity to be done efficiently and systematically, given the peculiarities of the context involved. We report the experience gained after the use of the adapted test process when compared to the previous ad-hoc testing process. Moreover, based on our experience, we identified a subset of tours from exploratory testing more suitable to test web based services, considering the restrictions we have, for improving the quality in the process of digital transformation. Other lessons learned are also presented and we think the results can be useful for testing systems with similar constraints.

Abstract
Learning difficulties in computing courses is a situation perceived in diverse universities from different countries, cultures and backgrounds. These difficulties directly affect achievement rates and increase course evasion. We believe in the existence of a foundation of cognitive processes, that without it, even the most motivated student would have trouble to transform the received information into knowledge. This work has focused mainly on the research of candidate methods for cognitive processes assessment with a strong background theory. With this kind of information would be possible to devise cognitive interventions, in order to evolve students cognitive level, and consequently, raise their success rates. A systematic review was conducted and among the many researched methods we selected Lawson Classroom Test of Scientific Reasoning – LCTSR. Authorized by its author, we conducted the first translation of LCTSR to Brazilian Portuguese and administered to students of three undergraduate computing courses: Information Systems, Computer Science and Software Engineering. We also present results of its administration that we consider important to reinforce the above suggested strategy.

Abstract
In the previous edition of ISSRE we used a straightforward hunting metaphor to call the attention of the research community to the importance of considering human aspects in software testing - in particular, to research challenges that affect practitioners in the industry. Our focus was on the unit testing level. As a result, we proposed a framework to indicate research directions in three cognitive support dimensions defined to this level of testing. In the present work, we advance in this area considering the visualization domain. We demonstrate an immediate application of our framework to help derive information on how visualizations for unit testing are currently addressing each cognitive support dimension. Our results demonstrate the lack of concern with adequate procedures for both planning and validation of the visualizations regarding cognitive support aspects. These issues affect the capacity of the proposals to support users and put under risk the solutions' reliability.

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.