SmartUnit: Empirical Evaluations for Automated Unit Testing of Embedded Software in Industry

In this paper, we aim at the automated unit coverage-based testing for embedded software. To achieve the goal, by analyzing the industrial requirements and our previous work on automated unit testing tool CAUT, we rebuild a new tool, SmartUnit, to solve the engineering requirements that take place in our partner companies. SmartUnit is a dynamic symbolic execution implementation, which supports statement, branch, boundary value and MC/DC coverage. SmartUnit has been used to test more than one million lines of code in real projects. For confidentiality motives, we select three in-house real projects for the empirical evaluations. We also carry out our evaluations on two open source database projects, SQLite and PostgreSQL, to test the scalability of our tool since the scale of the embedded software project is mostly not large, 5K-50K lines of code on average. From our experimental results, in general, more than 90% of functions in commercial embedded software achieve 100% statement, branch, MC/DC coverage, more than 80% of functions in SQLite achieve 100% MC/DC coverage, and more than 60% of functions in PostgreSQL achieve 100% MC/DC coverage. Moreover, SmartUnit is able to find the runtime exceptions at the unit testing level. We also have reported exceptions like array index out of bounds and divided-by-zero in SQLite. Furthermore, we analyze the reasons of low coverage in automated unit testing in our setting and give a survey on the situation of manual unit testing with respect to automated unit testing in industry.Comment: In Proceedings of 40th International Conference on Software Engineering: Software Engineering in Practice Track, Gothenburg, Sweden, May 27-June 3, 2018 (ICSE-SEIP '18), 10 page

A coarse-to-fine point completion network with details compensation and structure enhancement

Abstract Point cloud completion, the issue of estimating the complete geometry of objects from partially-scanned point cloud data, becomes a fundamental task in many 3d vision and robotics applications. To address the limitations on inadequate prediction of shape details for traditional methods, a novel coarse-to-fine point completion network (DCSE-PCN) is introduced in this work using the modules of local details compensation and shape structure enhancement for effective geometric learning. The coarse completion stage of our network consists of two branches—a shape structure recovery branch and a local details compensation branch, which can recover the overall shape of the underlying model and the shape details of incomplete point cloud through feature learning and hierarchical feature fusion. The fine completion stage of our network employs the structure enhancement module to reinforce the correlated shape structures of the coarse repaired shape (such as regular arrangement or symmetry), thus obtaining the completed geometric shape with finer-grained details. Extensive experimental results on ShapeNet dataset and ModelNet dataset validate the effectiveness of our completion network, which can recover the shape details of the underlying point cloud whilst maintaining its overall shape. Compared to the existing methods, our coarse-to-fine completion network has shown its competitive performance on both chamfer distance (CD) and earth mover distance (EMD) errors. Such as, the repairing results on the ShapeNet dataset of our completion network are reduced by an average of $$35.62\%$$ 35.62 % , $$33.31\%$$ 33.31 % , $$29.62\%$$ 29.62 % , and $$23.62\%$$ 23.62 % in terms of CD error, comparing with PCN, FoldingNet, Atlas, and CRN methods, respectively; and also reduced by an average of $$15.63\%$$ 15.63 % , $$1.29\%$$ 1.29 % , $$64.52\%$$ 64.52 % , and $$62.87\%$$ 62.87 % in terms of EMD error, respectively. Meanwhile, the completion results on the ModelNet dataset of our network have an average reduction of $$28.41\%$$ 28.41 % , $$26.57\%$$ 26.57 % , $$20.65\%$$ 20.65 % , and $$18.55\%$$ 18.55 % in terms of CD error, comparing to PCN, FoldingNet, Atlas, and CRN methods, respectively; and also an average reduction of $$21.91\%$$ 21.91 % , $$19.59\%$$ 19.59 % , $$43.51\%$$ 43.51 % , and $$21.49\%$$ 21.49 % in terms of EMD error, respectively. Our proposed point completion network is also robust to different degrees of data incompleteness and model noise

Investigation of Deep Mine Shaft Stability in Alternating Hard and Soft Rock Strata Using Three-Dimensional Numerical Modeling

The problem of shaft instability has always been a major difficulty in deep mining practices. The shaft fracture has a high probability of being located near the aquifers and the soft⁻hard rock contact zone. This paper describes the deformation and stress characteristics of surrounding rock and the shaft lining under the interactive geological conditions under soft and hard rock strata in Anju coal mine, Shandong Province, China. Using the Method of Geological Strength Index (GSI ) and considering the rock-softening characteristics of water, the parameters of rock mass are calibrated. By means of the 3DEC-trigon method, the variation characteristics of surrounding rock and the shaft lining are simulated. After shaft excavation, under the condition of no support, shear failure and tensile failure occur in shallow surrounding rock shafts, and a pressure relief zone is formed. Shear failure is the main destruction mode in deep surrounding rock. Because of the different strengths of the surrounding rock, the deformation of the surrounding rock is significantly different. After the surrounding rock is softened by water absorption, the difference is magnified. The maximum shear stress and plastic zone appear near the interface between soft and hard rock. Under the condition of shaft lining support, uneven deformation of surrounding rock surely leads to nonlinear variation of pressure on the shaft lining. Under the action of an inhomogeneous pressure field, partial shear failure occurs in the shaft lining, and the shear failure area increases after the surrounding rock is softened by water. Because of the nonlinear deformation of the shaft lining, it is easy to produce stress concentration and bending moment near the interface between hard and soft strata. The control methods of advance grouting and pressure relief excavation are proposed to improve the stability of the shaft, and a good effect is gained

Electrochemical analysis of Ca2+ based on DNAzyme catalyzed degradation of DNA hydrogel

Calcium ion is a type of indispensable metal elements in biology, which participates in processes like maintaining the excitability of neuromuscular muscles. However, calcium content should be monitored in a safety range. Herein, a novel electrochemical method is developed for Ca2+ assay by monitoring electrochemical response after DNAzyme catalyzed DNA hydrogel degradation. Pure DNA hydrogel is first built with three-way junction scaffolds and linkers containing Ca2+-dependent DNAzyme sequence. In the presence of target Ca2+, the substrates in linkers are cleaved and DNA hydrogel can be degraded gradually. The encapsulated electrochemical species thus facilely interact with the electrode, leading to the increase of electrochemical responses. This electrochemical method for Ca2+ quantification is selective and sensitive, which also performs satisfactorily challenging biological samples like sweat and urine

Transfer Learning Models for Detecting Six Categories of Phonocardiogram Recordings

Background and aims: Auscultation is a cheap and fundamental technique for detecting cardiovascular disease effectively. Doctors’ abilities in auscultation are varied. Sometimes, there may be cases of misdiagnosis, even when auscultation is performed by an experienced doctor. Hence, it is necessary to propose accurate computational tools to assist auscultation, especially in developing countries. Artificial intelligence technology can be an efficient diagnostic tool for detecting cardiovascular disease. This work proposed an automatic multiple classification method for cardiovascular disease detection by heart sound signals. Methods and results: In this work, a 1D heart sound signal is translated into its corresponding 3D spectrogram using continuous wavelet transform (CWT). In total, six classes of heart sound data are used in this experiment. We combine an open database (including five classes of heart sound data: aortic stenosis, mitral regurgitation, mitral stenosis, mitral valve prolapse and normal) with one class (pulmonary hypertension) of heart sound data collected by ourselves to perform the experiment. To make the method robust in a noisy environment, the background deformation technique is used before training. Then, 10 transfer learning networks (GoogleNet, SqueezeNet, DarkNet19, MobileNetv2, Inception-ResNetv2, DenseNet201, Inceptionv3, ResNet101, NasNet-Large, and Xception) are used for comparison. Furthermore, other models (LSTM and CNN) are also compared with our proposed algorithm. The experimental results show that four transfer learning networks (ResNet101, DenseNet201, DarkNet19 and GoogleNet) outperformed their peer models with an accuracy of 0.98 to detect the multiple heart diseases. The performances have been validated both in the original heart sound and the augmented heart sound using 10-fold cross validation. The results of these 10 folds are reported in this research. Conclusions: Our method obtained high classification accuracy even under a noisy background, which suggests that the proposed classification method could be used in auxiliary diagnosis for cardiovascular diseases

Review of enhancing boiling and condensation heat transfer: surface modification

Data centers have tended to develop towards large scale and high density, with overall power consumption reaching up to 3 % of the total national electricity consumption. It is vital to establish energy-efficient electronic cooling devices for data center improvement. Phase-change heat transfer has emerged as a highly efficient method for addressing the heat dissipation problem. As the demand for micro-electronic cooling devices grows, enhancing the phase-change heat transfer has been a key focus of engineering research for several decades. Surface modification can effectively facilitate heat transfer favored by the surface area expansion and free energy transition. This review delved into the multiple processes involved in phase-change heat transfer, containing boiling and condensation. Considering the surface roughness and free energy, the wettability theories and manipulations of hydrophilic and hydrophobic surfaces were presented. The fabrication techniques available for modified surfaces mainly comprise coating, etching, template, sol-gen, and layer-by-layer assembly methods. The effects of patterned surface, wettability gradient surface, electrowetting surface, and wettability controllable surface on phase-change heat transfer enhancement were elaborated, particularly for the critical heat flux and heat transfer coefficients. This review of experimental and simulation results showed that surface wettability modification possesses a promising prospect in improving heat transfer performance. In this review, recommendations for the design of surface modification to promote the development of energy-efficient technologies in specific artificial environments were proposed. Further theoretical and experimental efforts need to create novel surfaces that can facilitate high-performance phase-change heat transfer across a range of applications.This work was supported by the National Natural Science Foundation of China (52376073), Key Research and Development Program of Shaanxi (2023-GHZD-54), and Shaanxi Qinchuangyuan "Scientist + Engineer" Team Construction Project (2022KXJ-049)

Numerical Investigation of Gob-Side Entry Retaining through Precut Overhanging Hard Roof to Control Rockburst

Gob-side entry retaining through precut overhanging hard roof (GERPOHR) method is one of the commonly used methods for nonpillar mining. However, feasibility studies of controlling rockburst by this method are few. Rockburst occurs in hard thick strata with a higher probability, larger scale, and higher risk. To better understand the GERPOHR method is beneficial for rockburst mitigation. In this paper, the design of GERPOHR was first introduced. And the layout of the working face was optimized. Then, based on the numerical simulation, the stress and displacement distribution characteristics were compared under the condition of conventional mining and GERPOHR method. The research shows that the intervals of main roof weighting could be decreased through the precut overhanging hard roof method. And the peak value of abutment pressure decreased. Meanwhile, the energy accumulation and the stress fluctuation could be alleviated in roadway surrounding rock