Detection of type-3 and type-4 clones remains a difficult task. Current methods are complex, both on a conceptual and computational level. Similarly, their usage requires substantial implementation efforts. Instead of creating yet another method, it might be more productive to combine the simplicity of syntactic approaches with the abstractions granted by intermediate representations (IR). To this end, we devised a c-like IR based on LLVM and ran NiCad on it (LLNiCad). To establish whether the clone detection capabilities of syntactic approaches can be improved through an IR, we compared NiCad and LLNiCad on three open source projects taken from Krutz's benchmark and a subset of Google code jam solutions. In our results, the f1score of LLNiCad consistently outperforms NiCad. Indeed, for all clone types in Krutz's benchmark, LLNiCad has a f1-score that is 37% higher than NiCad; with both better precision and recall. For type-4 clones in our GCJ benchmark, the f1-score of LLNiCad also outperforms CCCD (a semantic clone detector) by 44%. These findings suggest that IRs are beneficial for improving clone detection and that they have a larger impact on type-3 and type-4 clones.

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It has been revealed that SARS-CoV-2 can be efficiently isolated from clinical specimens such as nasal/nasopharyngeal swabs or saliva in cultured cells. In this study, we examined the efficiency of viral isolation including SARS-CoV-2 mutant strains between nasal/nasopharyngeal swab or saliva specimens. Furthermore, we also examined the comparison of viral isolation rates by sample species using simulated specimens for COVID-19. As a result, it was found that the isolation efficiency of SARS-CoV-2 in the saliva specimens was significantly lower than that in the nasal/nasopharyngeal swab specimens. In order to determine which component of saliva is responsible for the lower isolation rate of saliva specimens, we tested the abilities of lactoferrin, amylase, cathelicidin, and mucin, which are considered to be abundant in saliva, to inhibit the infection of SARS-CoV-2 pseudotyped viruses (SARS-CoV-2pv). Lactoferrin and amylase were found to inhibit SARS-CoV-2pv infection. In conclusion, even if the same number of viral genome copies was detected by the real-time RT-PCR test, infection of SARS-CoV-2 present in saliva is thought to be inhibited by inhibitory factors such as lactoferrin and amylase, compared to nasal/nasopharyngeal swab specimens.