Automated program repair recently received considerable attentions, and many techniques on this research area have been proposed. Among them, two genetic-programmingbased techniques, GenProg and Par, have shown the promising results. In particular, GenProg has been used as the baseline technique to check the repair effectiveness of new techniques in much literature. Although GenProg and Par have shown their strong ability of fixing real-life bugs in nontrivial programs, to what extent GenProg and Par can benefit from genetic programming, used by them to guide the patch search process, is still unknown.To address the question, we present a new automated repair technique using random search, which is commonly considered much simpler than genetic programming, and implement a prototype tool called RSRepair. Experiment on 7 programs with 24 versions shipping with real-life bugs suggests that RSRepair, in most cases (23/24), outperforms GenProg in terms of both repair effectiveness (requiring fewer patch trials) and efficiency (requiring fewer test case executions), justifying the stronger strength of random search over genetic programming. According to experimental results, we suggest that every proposed technique using optimization algorithm should check its effectiveness by comparing it with random search.

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BackgroundPulmonary tuberculosis (TB) is a highly lethal infectious disease and early diagnosis of TB is critical for the control of disease progression. The objective of this study was to profile a panel of serum microRNAs (miRNAs) as potential biomarkers for the early diagnosis of pulmonary TB infection.MethodsUsing TaqMan Low-Density Array (TLDA) analysis followed by quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) validation, expression levels of miRNAs in serum samples from 30 patients with active tuberculosis and 60 patients with Bordetella pertussis (BP), varicella-zoster virus (VZV) and enterovirus (EV) were analyzed.ResultsThe Low-Density Array data showed that 97 miRNAs were differentially expressed in pulmonary TB patient sera compared with healthy controls (90 up-regulated and 7 down-regulated). Following qRT-PCR confirmation and receiver operational curve (ROC) analysis, three miRNAs (miR-361-5p, miR-889 and miR-576-3p) were shown to distinguish TB infected patients from healthy controls and other microbial infections with moderate sensitivity and specificity (area under curve (AUC) value range, 0.711-0.848). Multiple logistic regression analysis of a combination of these three miRNAs showed an enhanced ability to discriminate between these two groups with an AUC value of 0.863.ConclusionsOur study suggests that altered levels of serum miRNAs have great potential to serve as non-invasive biomarkers for early detection of pulmonary TB infection.

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Many techniques on automated fault localization (AFL) have been introduced to assist developers in debugging. Prior studies evaluate the localization technique from the viewpoint of developers: measuring how many benefits that developers can obtain from the localization technique used when debugging. However, these evaluation approaches are not always suitable, because it is difficult to quantify precisely the benefits due to the complex debugging behaviors of developers. In addition, recent user studies have presented that developers working with AFL do not correct the defects more efficiently than ones working with only traditional debugging techniques such as breakpoints, even when the effectiveness of AFL is artificially improved.In this paper we attempt to propose a new research direction of developing AFL techniques from the viewpoint of fully automated debugging including the program repair of automation, for which the activity of AFL is necessary. We also introduce the NCP score as the evaluation measurement to assess and compare various techniques from this perspective. Our experiment on 15 popular AFL techniques with 11 subject programs shipping with real-life field failures presents the evidence that these AFL techniques performing well in prior studies do not have better localization effectiveness according to NCP score. We also observe that Jaccard has the better performance over other techniques in our experiment.

Altered circulating microRNA (miRNA) profiles have been noted in patients with microbial infections. We compared host serum miRNA levels in patients with hand-foot-and-mouth disease (HFMD) caused by enterovirus 71 (EV71) and coxsackievirus 16 (CVA16) as well as in other microbial infections and in healthy individuals. Among 664 different miRNAs analyzed using a miRNA array, 102 were up-regulated and 26 were down-regulated in sera of patients with enteroviral infections. Expression levels of ten candidate miRNAs were further evaluated by quantitative real-time PCR assays. A receiver operating characteristic (ROC) curve analysis revealed that six miRNAs (miR-148a, miR-143, miR-324-3p, miR-628-3p, miR-140-5p, and miR-362-3p) were able to discriminate patients with enterovirus infections from healthy controls with area under curve (AUC) values ranged from 0.828 to 0.934. The combined six miRNA using multiple logistic regression analysis provided not only a sensitivity of 97.1% and a specificity of 92.7% but also a unique profile that differentiated enterovirial infections from other microbial infections. Expression levels of five miRNAs (miR-148a, miR-143, miR-324-3p, miR-545, and miR-140-5p) were significantly increased in patients with CVA16 versus those with EV71 (p<0.05). Combination of miR-545, miR-324-3p, and miR-143 possessed a moderate ability to discrimination between CVA16 and EV71 with an AUC value of 0.761. These data indicate that sera from patients with different subtypes of enteroviral infection express unique miRNA profiles. Serum miRNA expression profiles may provide supplemental biomarkers for diagnosing and subtyping enteroviral HFMD infections.

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A novel avian-origin influenza A (H7N9) virus recently occurred in China and caused 137 human infection cases with a 32.8% mortality rate. Although various detection procedures have been developed, the pathogenesis of this emerging virus in humans remains largely unknown. In this study, we characterized serum microRNA (miRNA) profile in response to H7N9 virus infection using TaqMan Low Density Arrays. Upon infection, a total of 395 miRNAs were expressed in the serum pool of patients, far beyond the 221 in healthy controls. Among the 187 commonly expressed miRNAs, 146 were up-regulated and only 7 down-regulated in patients. Further analysis by quantitative RT-PCR revealed that the serum levels of miR-17, miR-20a, miR-106a and miR-376c were significantly elevated in patients compared with healthy individuals (p < 0.05). Receiver operating characteristic (ROC) curves were constructed to show that each miRNA could discriminate H7N9 patients from controls with area under the curve (AUC) values ranging from 0.622 to 0.898, whereas a combination of miR-17, miR-20a, miR-106a and miR-376c obtained a higher discriminating ability with an AUC value of 0.96. Our findings unravel the significant alterations in serum miRNA expression following virus infection and manifest great potential of circulating miRNAs for the diagnosis of viral diseases.