Fault Coverage-Based Test Case Prioritization and Selection Using African Buffalo Optimization

Software needs modifications and requires revisions regularly.Owing to these revisions,retesting software becomes essential to ensure that the enhancements made,have not affected its bug-free functioning.The time and cost incurred in this process,need to be reduced by the method of test case selection and prioritization.It is observed that many nature-inspired techniques are applied in this area.African Buffalo Optimization is one such approach,applied to regression test selection and prioritization.In this paper,the proposed work explains and proves the applicability of the African Buffalo Optimization approach to test case selection and prioritization.The proposed algorithm converges in polynomial time(O(n^(2))).In this paper,the empirical evaluation of applying African Buffalo Optimization for test case prioritization is done on sample data set with multiple iterations.An astounding 62.5%drop in size and a 48.57%drop in the runtime of the original test suite were recorded.The obtained results are compared with Ant Colony Optimization.The comparative analysis indicates that African Buffalo Optimization and Ant Colony Optimization exhibit similar fault detection capabilities(80%),and a reduction in the overall execution time and size of the resultant test suite.The results and analysis,hence,advocate and encourages the use of African Buffalo Optimization in the area of test case selection and prioritization.

Method for test case selection and execution of web application regression testing

In order to improve the efficiency of regression testing in web application,the control flow graph and the greedy algorithm are adopted.This paper considers a web page as a basic unit and introduces a test case selection method for web application regression testing based on the control flow graph.This method is safe enough to the test case selection.On the base of features of request sequence in web application,the minimization technique and the priority of test cases are taken into consideration in the process of execution of test cases in regression testing for web application.The improved greedy algorithm is also raised resulting in optimization of execution of test cases.The experiments indicate that the number of test cases which need to be retested is reduced,and the efficiency of execution of test cases is also improved.

Probe Selection for Over-the-Air Test in 5G Base Stations with Massive Multiple-Input Multiple-Output

In 5G systems, massive multiple-input multiple-output (MIMO) has been adopted in base stations (BSs) to improve spectral efficiency and coverage. The traditional conductive performance test techniques are challenging due to the unaffordable cost and high complexity when testing a large number of antennas. To solve this problem, the over-the-air (OTA) test has been presented, in which probe selection is the key to reduce the number of channel emulators and probes. In this paper, a novel artificial bee colony (ABC) algorithm is introduced to enhance the efficiency and accuracy of probe selection procedure. A sectoring- based multi-probe anechoic chamber (MPAC) is built to evaluate the throughput performance of massive MIMO equipped in 5G BS. In addition, link level simulation is carried out to evaluate the proposal’s performance gain under the commercial network assumptions, where the average throughput of three velocity is given with different SNR region. The results suggest that OTA chamber and multi-probe wall are available not only for 5G BSs, but also for user equipments (UEs) with end-to-end communication.

Test selection and optimization for PHM based on failure evolution mechanism model

The test selection and optimization （TSO） can improve the abilities of fault diagnosis, prognosis and health-state evalua- tion for prognostics and health management （PHM） systems. Traditionally, TSO mainly focuses on fault detection and isolation, but they cannot provide an effective guide for the design for testability （DFT） to improve the PHM performance level. To solve the problem, a model of TSO for PHM systems is proposed. Firstly, through integrating the characteristics of fault severity and propa- gation time, and analyzing the test timing and sensitivity, a testability model based on failure evolution mechanism model （FEMM） for PHM systems is built up. This model describes the fault evolution- test dependency using the fault-symptom parameter matrix and symptom parameter-test matrix. Secondly, a novel method of in- herent testability analysis for PHM systems is developed based on the above information. Having completed the analysis, a TSO model, whose objective is to maximize fault trackability and mini- mize the test cost, is proposed through inherent testability analysis results, and an adaptive simulated annealing genetic algorithm （ASAGA） is introduced to solve the TSO problem. Finally, a case of a centrifugal pump system is used to verify the feasibility and effectiveness of the proposed models and methods. The results show that the proposed technology is important for PHM systems to select and optimize the test set in order to improve their performance level.

System level test selection based on combinatorial dependency matrix

Test selection is to select the test set with the least total cost or the least total number from the alternative test set on the premise of meeting the required testability indicators.The existing models and methods are not suitable for system level test selection.The first problem is the lack of detailed data of the units’fault set and the test set,which makes it impossible to establish a traditional dependency matrix for the system level.The second problem is that the system level fault detection rate and the fault isolation rate(referred to as"two rates")are not enough to describe the fault diagnostic ability of the system level tests.An innovative dependency matrix(called combinatorial dependency matrix)composed of three submatrices is presented.The first problem is solved by simplifying the submatrix between the units’fault and the test,and the second problem is solved by establishing the system level fault detection rate,the fault isolation rate and the integrated fault detection rate(referred to as"three rates")based on the new matrix.The mathematical model of the system level test selection problem is constructed,and the binary genetic algorithm is applied to solve the problem,which achieves the goal of system level test selection.

Application of Rollout Strategy to Test Points Selection for Integer-Coded Fault Wise Table

Test points selection for integer-coded fault wise table is a discrete optimization problem. The global minimum set of test points can only be guaranteed by an exhaustive search which is eompurationally expensive. In this paper, this problem is formulated as a heuristic depth-first graph search problem at first. The graph node expanding method and rules are given. Then, rollout strategies are applied, which can be combined with the heuristic graph search algorithms, in a computationally more efficient manner than the optimal strategies, to obtain solutions superior to those using the greedy heuristic algorithms. The proposed rollout-based test points selection algorithm is illustrated and tested using an analog circuit and a set of simulated integer-coded fault wise tables. Computa- tional results are shown, which suggest that the rollout strategy policies are significantly better than other strategies.

Selection of Minimal Test Points Set for Integer-Coded Fault Wise Table

Test points selection for integer-coded fault wise table is a discrete optimization problem. On one hand, traditional exhaustive search method is computationally expensive. On the other hand, the space complexity of traditional exhaustive is low. A tradeoff method between the high time complexity and low space complexity is proposed. At first, a new fault-pair table is constructed based on the integer-coded fault wise table. The fault-pair table consists of two columns： one column represents fault pair and the other represents test points set that can distinguish the corresponding faults. Then, the rows are arranged in ascending order according to the cardinality of corresponding test points set. Thirdly, test points in the top rows are selected one by one until all fault pair are isolated. During the test points selection process, the rows that contain selected test points are deleted and then the dimension of fault-pair table decreases gradually. The proposed test points selection algorithm is illustrated and tested using an integercoded fault wise table derived from a real analog circuit. Computational results suggest show policies are better than the exhaustive strategy.

Comparison, Selection and Progeny Test of Natural Populations of White Birch (Betula platyphylla Suk.) in Northern China

[Objectives]This study was conducted to rationally and effectively use natural genetic resources of white birch(Betula platyphylla Suk.),and improve the scientific and technological content of improved varieties.[Methods]With the progeny of the white birch populations naturally distributed in northern China as objects,based on genetic effect analysis and comprehensive evaluation,the genetic variation,heritability and genetic gain of the growth characters in the progeny forest were systematically analyzed,by which populations or individuals with good growth vigor and strong stress resistance and adaptability were finally selected.[Results]There were extremely significant differences in the growth characters between the natural populations of white birch in northern China.The variation was the smallest in tree height,followed by crown width,and largest in DBH,and the average coefficients of variation were 20.56%,32.25%and 33.00%,respectively.The differences in characters between progeny of the same population were also extremely significant.The growth characters of white birch were more controlled by genes,and the genetic gains were larger.The heritability of tree height,DBH and crown width was 0.971,0.816 and 0.576,respectively,and the genetic gains were 15.97%,21.54%and 13.87%,respectively.[Conclusions]With the growth characters as the main evaluation indexes,taking various influencing factors into account,the Shanxi[SX]population,Hebei[HB]population and Liaoning[LN]population were selected to be excellent populations,and LN305,SX516 and HB403 were excellent individuals,which are advised to be widely used in multi-generation genetic improvement breeding.

Improved Test Case Selection Algorithm to Reduce Time in Regression Testing

Regression testing(RT)is an essential but an expensive activity in software development.RT confirms that new faults/errors will not have occurred in the modified program.RT efficiency can be improved through an effective technique of selected only modified test cases that appropriate to the modifications within the given time frame.Earlier,several test case selection approaches have been introduced,but either these techniques were not sufficient according to the requirements of software tester experts or they are ineffective and cannot be used for available test suite specifications and architecture.To address these limitations,we recommend an improved and efficient test case selection(TCS)algorithm for RT.Our proposed technique decreases the execution time and redundancy of the duplicate test cases(TC)and detects onlymodified changes that appropriate to themodifications in test cases.To reduce execution time for TCS,evaluation results of our proposed approach are established on fault detection,redundancy and already executed test case.Results indicate that proposed technique decreases the inclusive testing time of TCS to execute modified test cases by,on average related to a method of Hybrid Whale Algorithm(HWOA),which is a progressive TCS approach in regression testing for a single product.

Optimal Test Points Selection Based on Multi-Objective Genetic Algorithm

A new approach to select anoptimal set of test points is proposed. The described method uses fault-wise table and multi-objective genetic algorithm to find the optimal set of test points. First, the fault-wise table is constructed whose entries are measurements associated with faults and test points. The selection of optimal test points is transformed to the selection of the columns that isolate the rows of the table. Then, four objectives are described according to practical test requirements. The multi-objective genetic algorithm is explained. Finally, the presented approach is illustrated by a practical example. The results indicate that the proposed method can efficiently and accurately find the optimal set of test points and is practical for large scale systems.

Selection of Winter Rape Varieties in the National Early Maturing Area

[Objective] This study aimed to promote the sustainable development of rape industry, and to meet the growing demand of urban and rural residents for vegetable oil. [Method] Field test was conducted for winter rape varieties in the national early maturing area in 2015, and their yield, main economic traits, growth period, consistency and stress resistance were evaluated comprehensively. [Result] Xiangyou 420, Qingza 12, Qianyouzao 3 and Yunyouza 16 could be applied in Baoshan City, Yunnan Province, and Yangguang 1418, Shengguang 127 and Qingza 10 （CK） should be further tested. [Conclusion] The results can be demonstratively applied in Baoshan City and other similar regions, so as to promote the development of rape industry.

Genetic variation and selection of introduced provenances of Siberian Pine(Pinus sibirica) in frigid regions of the Greater Xing'an Range,Northeast China

Siberian Pine （Pinus sibirica） is an ecologically and eco-nomically important species in pristine forests throughout northern Rus-sia. Four provenances of P. sibirica were introduced from Mongolia and Russia to the Greater Xing’an Range （the Daxing’anling）, northeast China in 1993. The aim of this research was to study genetic variation and selection of the introduced four Pinus sibirica provenances. Heights （H）, basal diameters （BD）, survival rates （SR） and crown lengths （CL） of different families were measured as primary outcomes in different growth years. Results of data analyses demonstrated high coefficients of phenotypic variation （PCV） and heritability （H2） for H, BD and CL at 18 years after introduction. PCV and H2 increased with age. Correlations of＆amp;nbsp;growth traits between any two growth years were all significantly positive, but the correlation coefficient was smaller when the growth year interval was larger. Correlations between H and the original environment factors decreased gradually, indicating that with long-term subsistence in the new environment, the influence of the source environment declined. Colligation of multiple traits to estimate provenances showed that Novosibirsk, Tomsk, and Altai Mountains had higher survival rates and biomass, and proved more suitable for introduction and plantation in the Greater Xing’an Range in China.

A New Approach of Feature Selection for Text Categorization

This paper proposes a new approach of feature selection based on the independent measure between features for text categorization. A fundamental hypothesis that occurrence of the terms in documents is independent of each other, widely used in the probabilistic models for text categorization （TC）, is discussed. However, the basic hypothesis is incom plete for independence of feature set. From the view of feature selection, a new independent measure between features is designed, by which a feature selection algorithm is given to ob rain a feature subset. The selected subset is high in relevance with category and strong in independence between features, satisfies the basic hypothesis at maximum degree. Compared with other traditional feature selection method in TC （which is only taken into the relevance account）, the performance of feature subset selected by our method is prior to others with experiments on the benchmark dataset of 20 Newsgroups.

A genome scan of recent positive selection signatures in three sheep populations

Domesticated sheep have been exposed to artificial selection for the production of fiber, meat, and milk as well as to natural selection. Such selections are likely to have imposed distinctive selection signatures on the sheep genome. Therefore, detecting selection signatures across the genome may help elucidate mechanisms of selection and pinpoint candidate genes of interest for further investigation. Here, detection of selection signatures was conducted in three sheep breeds, Sunite （n=66）, German Mutton （n=159）, and Dorper （n=93）, using the Illumina OvineSNP50 Genotyping BeadChip array. Each animal provided genotype information for 43 273 autosomal single nucleotide polymorphisms （SNPs）. We adopted two complementary haplotype-based statistics of relative extended haplotype homozygosity （REHH） and the cross-popu- lation extended haplotype homozygosity （XP-EHH） tests. In total, 707,755, and 438 genomic regions subjected to positive selection were identified in Sunite, German Mutton, and Dorper sheep, respectively, and 42 of these regions were detected using both REHH and XP-EHH analyses. These genomic regions harbored many important genes, which were enriched in gene ontology terms involved in muscle development, growth, and fat metabolism. Fourteen of these genomic regions overlapped with those identified in our previous genome-wide association studies, further indicating that these genes under positive selection may underlie growth developmental traits. These findings contribute to the identification of candidate genes of interest and aid in understanding the evolutionary and biological mechanisms for controlling complex traits in Chinese and western sheep.

Selection criteria for preoperative endoscopic retrograde cholangiopancreatography before laparoscopic cholecystectomy and endoscopic treatment of bile duct stones:Results of a retrospective,single center study between 1996-2002

AIM: The optimal treatment for bile duct stones (in terms of cost, complications and accuracy) is unclear. The aim of our study was to determine the predictive factors for preoperative endoscopic retrograde cholangiopancreatography (ERCP).METHODS: Patients undergoing preoperative ERCP (≤90 d before laparoscopic cholecystectomy) were evaluated in this retrospective study from the 1^st of January 1996 to the 31^st of December 2002. The indications for ERCP were elevated serum bilirubin, elevated liver function tests (LFT), dilated bile duct (≥8 mm) and/or stone at US examination, coexisting acute pancreatitis and/or acute pancreatitis or jaundice in patient's history. Suspected prognostic factors and the combination of factors were compared to the result of ERCRRESULTS: Two hundred and six preoperative ERCPs were performed during the observed period. The rate of successful cannulation for ERC was (97.1%). Bile duct stones were detected in 81 patients (39.3%), and successfully removed in 79 (97.5%). The number of prognostic factors correlated with the presence of bile duct stones. The positive predictive value for one prognostic factor was 1.2%, for two 43%,for three 72.5%, for four or more 91.4%.CONCLUSION: Based on our data preoperative ERCP is highly recommended in patients with three or more positive factors (high risk patients). In contrast, ERCP is not indicated in patients with zero or one factor (low risk patients).Preoperative ERCP should be offered to patients with two positive factors (moderate risk patients), however the practice should also be based on the local conditions (e.g.skill of the endoscopist, other diagnostic tools).

Subsurface Defect Evaluation of Selective-Laser-Melted Inconel 738LC Alloy Using Eddy Current Testing for Additive/Subtractive Hybrid Manufacturing

New materials and manufacturing technologies require applicable non-destructive techniques for quality assurance so as to achieve better performance.This study comprehensively investigated the effect of influencing factors includ-ing excitation frequency,lift-off distance,defect depth and size,residual heat,and surface roughness on the defect EC signals of an Inconel 738LC alloy produced by selective laser melting(SLM).The experimental investigations recorded the impedance amplitude and phase angle of EC signals for each defect to explore the feasibility of detecting sub-surface defects by merely analyzing these two key indicators.Overall,this study revealed preliminary qualitative and roughly quantitative relationships between influencing factors and corresponding EC signals,which provided a prac-tical reference on how to quantitively inspect subsurface defects using eddy current testing(ECT)on SLMed parts,and also made solid progress toward on-line ECT in additive/subtractive hybrid manufacturing(ASHM)for fabricating SLMed parts with enhanced quality and better performance.

STUDY ON THE HALF-SIB FAMILY SELECTION FOR THE SUPERIOR TREE OF SCOTS PINE

Investigation and rescarches are carricd out in MaocrshanForcst Farm attached to Northeast Forcstry University in 1988. Comparedwith the contrast, 29 superior familics and 21 inferior families areselected from 112 families of half sib and open pollination of seven-year old scots pine stands by using multicharacters correlations analysis and variance analysis (ANOVA) as well as principal component index (PCI) selection. This index selection which collects multicharacters information has more advantage than monocharacter selection. It is very important to select fine famiIies for buildingthe first generation seed orchard and changing from trial stand toseeding orchard.

Model selection for SVM using mutative scale chaos optimization algorithm

This paper proposes a new search strategy using mutative scale chaos optimization algorithm （MSCO） for model selection of support vector machine （SVM）. It searches the parameter space of SVM with a very high efficiency and finds the optimum parameter setting for a practical classification problem with very low time cost. To demonstrate the performance of the proposed method it is applied to model selection of SVM in ultrasonic flaw classification and compared with grid search for model selection. Experimental results show that MSCO is a very powerful tool for model selection of SVM, and outperforms grid search in search speed and precision in ultrasonic flaw classification.

Comparison and early selection of new clones in Populus tomentosa

In our study, two experimental plantations, respectively, with 24 and 32 new clones of P tomentosa, were established in Weixian County, Hebei Province and Wuzhi County, Henan Province using a completely randomized block design. A comparative study was conducted on the continuous 5-year-old height and diameter at breast height （DBH） of new clones in the two plantations. As well, based on genetic correlation over the years of testing of these clones, a preliminary study of early selection was carried out. Results indicate that the growth traits of the new clones in Weixian were better than those in Wuzhi. The traits show weak correlation between the two plantations. In some stands, the height, DBH and seedling volume of 5-year-old clones presented statistically significant differences among clones. In both plantations, the new clones showed over 0.6 repeatability of height, DBH and volume, as well as larger coefficients of variation （CV）. The fact that these clones achieved the largest repeatability and CV in the second year suggests that these traits are highly controlled by heredity. Thus, based on the growth traits of the second year, the new clones B305, B307, B303, H75, BT18, BT17 and 21J-1 were considered suitable in Weixian. In Wuzhi, the new clones had variable repeatability and CVs in various years and their correlation of growth traits among different years was not high. We conclude that early selection of new clones was not feasible in Wuzhi.

A Universal Selection Method in Linear Regression Models

In this paper we consider a linear regression model with fixed design. A new rule for the selection of a relevant submodel is introduced on the basis of parameter tests. One particular feature of the rule is that subjective grading of the model complexity can be incorporated. We provide bounds for the mis-selection error. Simulations show that by using the proposed selection rule, the mis-selection error can be controlled uniformly.