Construção de um classificador automático de severidade de bugs para sistemas open source

Software bug analysis is one of the most important activities in Software Quality. The rapid and correct implementation of the necessary repair influence both developers, who must leave the fully functioning software, and users, who need to perform their daily tasks. In this context, if there is an incorrect classification of bugs, there may be unwanted situations. One of the main factors to be assigned bugs in the act of its initial report is severity, which lives up to the urgency of correcting that problem. In this scenario, we identified in datasets with data extracted from five open source systems (Apache, Eclipse, Kernel, Mozilla and Open Office), that there is an irregular distribution of bugs with respect to existing severities, which is an early sign of misclassification. In the dataset analyzed, exists a rate of about 85% bugs being ranked with normal severity. Therefore, this classification rate can have a negative influence on software development context, where the misclassified bug can be allocated to a developer with little experience to solve it and thus the correction of the same may take longer, or even generate a incorrect implementation. Several studies in the literature have disregarded the normal bugs, working only with the portion of bugs considered severe or not severe initially. This work aimed to investigate this portion of the data, with the purpose of identifying whether the normal severity reflects the real impact and urgency, to investigate if there are bugs (initially classified as normal) that could be classified with other severity, and to assess if there are impacts for developers in this context. For this, an automatic classifier was developed, which was based on three algorithms (Näive Bayes, Max Ent and Winnow) to assess if normal severity is correct for the bugs categorized initially with this severity. The algorithms presented accuracy of about 80%, and showed that between 21% and 36% of the bugs should have been classified differently (depending on the algorithm), which represents somewhere between 70,000 and 130,000 bugs of the dataset.

Mecanismos protetores induzidos pelo tratamento prévio com antígeno solúvel de taquizoítas (STAg) no intestino delgado de camundongos BALB/c e C57BL/6 infectados oralmente por Toxoplasma gondii

T. gondii can infect the gut mucosa by direct invasion of epithelial cells in the small intestine and these cells may respond directly to infection promoting a local immune response. C57BL/6 mice orally infected with a high parasitic load of T.gondii are highly susceptible, presenting a lethal ileitis. Recently, it was demonstrated that pretreatment with STAg protects C57BL/6 mice against intestinal pathology in oral T. gondii infection. To investigate the mechanisms induced by STAg in the small intestine in oral T.gondii infection, BALB/c and C57BL/6 mice were treated with STAg 48 hours before oral infection with 30 ME-49 cysts and sacrificed at 8 days of infection. Previous treatment with STAg were able of decrease parasitism and pathology in peripheral organs of BALB/c and C57BL/6 mice and induced a increase in amounts of goblet cells, IgA positive cells, Paneth cells and expression of cryptidin in the small intestine of both lineages of mice, moreover BALB/c mice presented higher amount of these cells comparing with C57BL/6 mice. The results suggests that STAg is able of promoting protective mechanisms in both lineages of mice, although these protection is more evidenced in BALB/c mice, and these mechanisms could be in part mediated by increase in goblet, Paneth and local secretion of IgA in the small intestine of mice orally infected with T.gondii.

Tratamento tópico para xerostomia pós-radioterapia para câncer de cabeça e pescoço – Revisão Sistemática

The purpose of this systematic review was to compare the effectiveness of topical treatments to minimize post-radiotherapy xerostomia. PubMed, Cochrane Library (CENTRAL) and LILACS databases were searched without restriction on date or language until the 6thAugust, 2015. Key-wordsused for searching were radiotherapy, xerostomia and saliva. Two independent reviewers screened titles and abstracts, carried out data extraction and assessed risk of bias. The first search identified 429 articles. From these, 117 studies were selected for full-text reading, from which 18 were included in the qualitative synthesis. From the eighteen articles included, seven were non- controlled clinical trial, one article was controlled clinical trial and ten studies were randomized clinical trials (three clinical trials were placebo controlled and seven were crossover). By the assessment of the quality of the studies included, ten showed high risk of bias, four showed moderate risk of bias and four presented low risk of bias. All interventions were considered effective in treating xerostomia (mucin, polysaccharides, aloe vera, rape oil, linseed oil, carboxymethylcellulose, polyethylene oxide, pilocarpine and systems of care for xerostomia - gel, paste and mouthwash). Meta-analysis could not be performed due to heterogeneity between thestudiesand interventions. This systematic review showed that a single and general protocol for topical treatment of xerostomia post-radiotherapy does not exist and that follow-up visits should be performed to validate the individualized treatment plan.