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The prevalence of design problems may cause re-engineering or even discontinuation of the system. Due to missing, informal or outdated design documentation, developers often have to rely on the source code to identify design problems. Therefore, developers have to analyze different symptoms that manifest in several code elements, which may quickly turn into a complex task. Although researchers have been investigating techniques to help developers in identifying design problems, there is little knowledge on how developers actually proceed to identify design problems. In order to tackle this problem, we conducted a multi-trial industrial experiment with professionals from 5 software companies to build a grounded theory. The resulting theory offers explanations on how developers identify design problems in practice. For instance, it reveals the characteristics of symptoms that developers consider helpful. Moreover, developers often combine different types of symptoms to identify a single design problem. This knowledge serves as a basis to further understand the phenomena and advance towards more effective identification techniques.

Background: Establishing representative samples for Software Engineering surveys is still considered a challenge. Specialized literature often presents limitations on interpreting surveys' results, mainly due to the use of sampling frames established by convenience and non-probabilistic criteria for sampling from them. In this sense, we argue that a strategy to support the systematic establishment of sampling frames from an adequate source of sampling can contribute to improve this scenario. Method: A conceptual framework for supporting large scale sampling in Software Engineering surveys has been organized after performing a set of experiences on designing such strategies and gathering evidence regarding their benefits. The use of this conceptual framework based on a sampling strategy developed for supporting the replication of a survey on characteristics of agility and agile practices in software processes is depicted in this paper. Result: A professional social network (Linkedln) was established as the source of sampling and its groups of interest as the units for searching members to be recruited. It allowed to deal with a sampling frame composed by more than 110,000 members (prospective subjects) distributed over 19 groups of interest. Then, through the similarity levels observed among these groups, eight strata were organized and 7745 members were invited, from which 291 have confirmed participation and answered the questionnaire. Conclusion: The heterogeneity and number of participants in this replication contributed to improve the strength of original survey's results. Therefore, we believe the sharing of this experience, the instruments and plan can be helpful for those researchers and practitioners interested on executing large scale surveys in Software Engineering.

Dengue is a disease transmitted by the Aedes Aegypti mosquito, which also transmits the Zika virus and Chikungunya. Unfortunately, the population of different countries has been suffering from the diseases transmitted by the mosquito. The communities can play an important role in combatting and preventing the mosquito-borne diseases. However, due to the limited engagement of the population, new methods need to be used to strengthen the mosquito surveillance. VazaDengue is one of these solutions that provides services that stand out from the others solutions. Generally speaking VazaDengue is a system that offers the users a platform for preventing and combating mosquito-borne diseases. The system relies on social actions of reporting mosquito breeding sites and dengue cases, in which the reports are made available to the citizens and health agencies. In addition, the system monitors social media network Twitter to enrich the information provided. It processes the natural language text from the network to classify the tweets according to a set of the predefined categories. After the classification, the relevant tweets are provided to the users as reports. In this paper, we describe the VazaDengue features including its ability to harvest and classify tweets. Since the VazaDengue system aims at providing a dynamic and efficient environment to support rapid interventions of health agents, we present here two studies evaluating the potential contributions of the classified tweets in preventing and combating mosquito-borne diseases. The first evaluation uses a survey conducted by the Brazilian community of health agents. The goal is to evaluate the relevance of the classified tweets. The second study compares the official reports of the 2015-2016 epidemic waves in Brazil with the concentration of mosquito-related tweets found by VazaDengue. The goal is to verify if the concentration of tweets can be used for monitoring big cities. The results of these two evaluations are encouraging. We have found that the health agents tend to agree with the relevance of the classified tweets. Moreover, the concentration of tweets is likely to be effective for monitoring big cities. The results of these evaluations are helping us to further improve the VazaDengue system to make it more useful for combating and preventing the mosquito-borne diseases. VazaDengue: An Information System for Preventing and Combating Mosquito-Borne Diseases with Social Networks:

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Quantitative studies in Software Engineering are frequently dependent on primary studies in which population is usually small and established by convenience. It brings several limitations for the analysis and strength of results due sampling issues. Therefore, when these studies are reapplied, different and non-clustered populations are established, making unfeasible evidence generalization and contributing for an imbalance between research and practice. Aiming at investigating ways to overcome the absence of large sampling frames in Software Engineering studies, this short paper presents the results of an initial experience concerned with the systematic recruitment of subjects for a survey regarding software requirements effort factors by using social networks compared with recruitment by convenience. We have observed in this particular case that using social networks technology does not guarantee sample enlargement by just posting invitations in specific forums. However, its usage can contribute to increase the subjects' heterogeneity and to increase the level of confidence of the sample, which consequently improve our capacity of observing the object under study, with the probable strengthen of results.