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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 Due to missing, informal or outdated design documentation, developers often have to rely on the source code to identify design problems.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.

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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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