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Configuration errors are some of the main reasons for software failures. Some configuration options may even negatively impact the software's security, so that if a user sets the options inappropriately, there may be a huge security risk for the software. Recent studies have proposed mapping option read points to configuration options as the first step in alleviating the occurrence of configuration errors. Sadly, most available techniques use humans, and the rest require additional input, like an operation manual. Unfortunately, not all software is standardized and friendly. We propose a technique based on program and static analysis that can automatically map all the configuration options of a program just by reading the source code. Our evaluation shows that this technique achieves 88.6%, 97.7%, 94.6%, 94.8%, and 92.6% success rates with the Hadoop modules Common, Hadoop distributed file system, MapReduce, and YARN, and also PX4, when extracting configuration options. We found 53 configuration options in PX4 that were not documented and submitted these to the developers. Compared with published work, our technique is more effective in mapping options, and it may lay the foundation for subsequent research on software configuration security. [ABSTRACT FROM AUTHOR]

Configuration errors are some of the main reasons for software failures. Some configuration options may even negatively impact the software's security, so that if a user sets the options inappropriately, there may be a huge security risk for the software. Recent studies have proposed mapping option read points to configuration options as the first step in alleviating the occurrence of configuration errors. Sadly, most available techniques use humans, and the rest require additional input, like an operation manual. Unfortunately, not all software is standardized and friendly. We propose a technique based on program and static analysis that can automatically map all the configuration options of a program just by reading the source code. Our evaluation shows that this technique achieves 88.6%, 97.7%, 94.6%, 94.8%, and 92.6% success rates with the Hadoop modules Common, Hadoop distributed file system, MapReduce, and YARN, and also PX4, when extracting configuration options. We found 53 configuration options in PX4 that were not documented and submitted these to the developers. Compared with published work, our technique is more effective in mapping options, and it may lay the foundation for subsequent research on software configuration security. [ABSTRACT FROM AUTHOR]

The fault diagnosis of early failure bearing can discover the potential danger in the mechanical equipment in time. It remains a great challenge due to the noise interference. Although many diagnosis methods have been proposed, the characteristics of signal have not yet been fully investigated, which leads to unsatisfactory diagnosis results. To solve this problem, a weak fault detection method with a two-stage key frequency focusing model is designed. Translation invariance in time domain and translation variance in frequency domain are systematically considered. The effectiveness is verified on four constructed datasets. The results show that the designed network has the best comprehensive performance comparing to the state-of-the-art methods. • The attributes of TITD and TIFD are considered simultaneously • A model is proposed to solve the challenge of considering TITD and TVFD • Both the accuracy and the lightness of the model have been improved • The validity of the method is verified by four datasets [ABSTRACT FROM AUTHOR]

The selection of the filter band for demodulation is crucial to extract the weak repetitive transients of fault rolling element bearing (REB). However, when the signal to noise is low, traditional methods for finding a suitable filter band are susceptible to the cyclostationary (CS) interference and the abnormal shock. In order to solve this problem, a new extraction method with reweighted singular value decomposition and improved Fast_kurtogram, namely RWSVD_IFK, is proposed. Firstly, by combining the new weight factors with singular components, a novel denoised strategy is presented to preprocess the original signal for reducing the CS interference. Secondly, considering that the kurtosis index is sensitive to the abnormal shock, the proposed method introduces the autocorrelation function into Fast_kurtogram to weaken the interference of the abnormal shock. And then, the squared envelope is applied to extract the weak repetitive transients from the optimal filtered signal. The simulated data and measured data of the fault REB are used to verify the validity of the proposed RWSVD_IFK. The results show that the proposed method can overcome the CS interference and the abnormal shock in finding the optimal filter band and effectively extract the weak repetitive transients of fault REB. • RWSVD-IFK is proposed for extracting weak repetitive transients of fault bearing. • A novel strategy for decreasing cyclostationary noise is proposed by using RWSVD. • Improved Fast_kurtogram (IFK) overcomes the influence of the abnormal shock. • Simulation and experiment highlight the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]