Minyan Lu

TL;DR: Experimental results showed that the improved CNN model proposed was comparable to the existing CNN model, and it outperformed the state-of-the-art machine learning models significantly for WPDP.

TL;DR: An approach is proposed to assess the confidence in assurance cases (mainly arguments) quantitatively by using Hitchcock's evaluative criteria for solo-verb-reasoning to analyze and quantify the Toulmin model instances into Bayesian Belief Network (BBN).

TL;DR: Empirical studies are performed using various CodeBERT models targeting software defect prediction to investigate if using a neural language model like CodeberT could improve prediction performance and the effects of different prediction patterns in software defects prediction.

TL;DR: The experimental results show that the proposed IS-TEF is more suitable and flexible for describing the consumption of TE than the previous TEFs and incorporating TEFs into the inflected S-shaped NHPP SRGM may be more effective and appropriate compared with the exponential-type and the delayed S- shaped NHPPSRGMs.

TL;DR: This approach which makes the analysis process of FMEA more operable and the failure modes obtained from analysis more comprehensive improves the efficiency of Software FME a.