New metrics for prioritized interaction test suites

Combinatorial interaction testing has been well studied in recent years, and has been widely applied in practice. It generally aims at generating an effective test suite (an interaction test suite) in order to identify faults that are caused by parameter interactions. Due to some constraints in practical applications (e.g. limited testing resources), for example in combinatorial interaction regression testing, prioritized interaction test suites (called interaction test sequences) are often employed. Consequently, many strategies have been proposed to guide the interaction test suite prioritization. It is, therefore, important to be able to evaluate the different interaction test sequences that have been created by different strategies. A well-known metric is the Average Percentage of Combinatorial Coverage (shortly APCCλ), which assesses the rate of interaction coverage of a strength λ (level of interaction among parameters) covered by a given interaction test sequence S. However, APCCλ has two drawbacks: firstly, it has two requirements (that all test cases in S be executed, and that all possible λ-wise parameter value combinations be covered by S); and secondly, it can only use a single strength λ (rather than multiple strengths) to evaluate the interaction test sequence - which means that it is not a comprehensive evaluation. To overcome the first drawback, we propose an enhanced metric Normalized APCCλ (NAPCC) to replace the APCCλ Additionally, to overcome the second drawback, we propose three new metrics: the Average Percentage of Strengths Satisfied (APSS); the Average Percentage of Weighted Multiple Interaction Coverage (APWMIC); and the Normalized APWMIC (NAPWMIC). These metrics comprehensively assess a given interaction test sequence by considering different interaction coverage at different strengths. Empirical studies show that the proposed metrics can be used to distinguish different interaction test sequences, and hence can be used to compare different test prioritization strategies

Tea Garden Detection from High-Resolution Imagery Using a Scene-Based Framework

Tea cultivation has a long history in China, and it is one of the pillar industries of the Chinese agricultural economy. It is therefore necessary to map tea gardens for their ongoing management. However, the previous studies have relied on fieldwork to achieve this task, which is time-consuming. In this paper, we propose a framework to map tea gardens using high-resolution remotely sensed imagery, including three scene-based methods: the bag-of-visual-words (BOVW) model, supervised latent Dirichlet allocation (sLDA), and the unsupervised convolutional neural network (UCNN). These methods can develop direct and holistic semantic representations for tea garden scenes composed of multiple sub-objects, thus they are more suitable than the traditional pixel-based or object-based methods, which focus on the local characteristics of pixels or objects. In the experiments undertaken in this study, the three different methods were tested on four datasets from Longyan (Oolong tea), Hangzhou (Longjing tea), and Puer (Puer tea). All the methods achieved a good performance, both quantitatively and visually, and the UCNN outperformed the other methods. Moreover, it was found that the addition of textural features improved the accuracy of the BOVW and sLDA models, but had no effect on the UCNN

Aggregate-strength interaction test suite prioritization

Combinatorial interaction testing is a widely used approach. In testing, it is often assumed that all combinatorial test cases have equal fault detection capability, however it has been shown that the execution order of an interaction test suite's test cases may be critical, especially when the testing resources are limited. To improve testing cost-effectiveness, test cases in the interaction test suite can be prioritized, and one of the best-known categories of prioritization approaches is based on “fixed-strength prioritization”, which prioritizes an interaction test suite by choosing new test cases which have the highest uncovered interaction coverage at a fixed strength (level of interaction among parameters). A drawback of these approaches, however, is that, when selecting each test case, they only consider a fixed strength, not multiple strengths. To overcome this, we propose a new “aggregate-strength prioritization”, to combine interaction coverage at different strengths. Experimental results show that in most cases our method performs better than the test-case-generation, reverse test-case-generation, and random prioritization techniques. The method also usually outperforms “fixed-strength prioritization”, while maintaining a similar time cost

An Analysis on the Effectiveness of 2 and 3 Terminal Capacitors in PDN Design

The Parasitic Inductance of a Capacitor Depends on its Physical Structure. Due to the Geometry of 3-Terminal Capacitors, They Boast a Lower Parasitic Inductance Compared to 2-Terminal Capacitors of the Same and Possibly Smaller Package Sizes. While the Parasitic Inductance of a Single 3-Terminal Capacitor May Be Lower, using Multiple 2-Terminal Capacitors May Result in Similar Performance. in This Work, the Inductance of 2-Terminal (0201, Nominal 2.2 UF) and 3-Terminal (0402, Nominal 4.3 UF) Capacitors is Extracted and Compared through Measurements. from Our De-Embedding Method and Characterized Capacitors, the Inductance of 2-Terminal Capacitors is Only About 20 PH Higher Than the Characterized 3terminal Capacitor. on a Power Net of a Real Product, 3-Terminal Capacitors of the Same Type as Characterized Were Replaced with 2-Terminal Capacitors of the Same Type as Characterized. from Measurement Results, the Measured Inductance at 100 MHz is Lower by Only About 3.45 PH, or 2.62%, When using 3-Terminal Capacitors

Prioritization of combinatorial test cases by incremental interaction coverage

Combinatorial testing is a well-recognized testing method, and has been widely applied in practice. To facilitate analysis, a common approach is to assume that all test cases in a combinatorial test suite have the same fault detection capability. However, when testing resources are limited, the order of executing the test cases is critical. To improve testing cost-effectiveness, prioritization of combinatorial test cases is employed. The most popular approach is based on interaction coverage, which prioritizes combinatorial test cases by repeatedly choosing an unexecuted test case that covers the largest number on uncovered parameter value combinations of a given strength (level of interaction among parameters). However, this approach suffers from some drawbacks. Based on previous observations that the majority of faults in practical systems can usually be triggered with parameter interactions of small strengths, we propose a new strategy of prioritizing combinatorial test cases by incrementally adjusting the strength values. Experimental results show that our method performs better than the random prioritization technique and the technique of prioritizing combinatorial test suites according to test case generation order, and has better performance than the interaction-coverage-based test prioritization technique in most cases

Workplace learning in China: transferring training into practice to improve performance

Purpose: The present study seeks to examine the efficacy of different training modalities on increasing workplace learning, representatives\u27 intent to transfer what they learned into their work, and importantly how training impacts actual work performance. These relationships are tested in the context of a Chinese division of a multinational pharmaceutical company, where pharmaceutical representatives are tasked with relaying relevant efficacy and safety information on pharmaceutical products to health care professionals who prescribe them to patients. Methods: The present study employed a three-group between-subjects experimental design. Representatives received varying forms of training (instruction only, instruction plus reflection, and instruction, reflection, plus direct feedback) based on experimental conditions. After three training sessions over the course of six weeks, representatives were assessed on how much they learned in the training and their actual work performance through observer assessment of meetings with health care professionals, facilitated by the representatives. Findings: In this study, it was found that the process of actively reflecting on what was learned in training led to increased learning, as well as increased performance, compared to simply studying the material. However, receiving direct feedback on training performance, combined with active reflection training, did not provide any further benefits in terms of learning or work performance. Notably, there were no differences in intent to transfer learned material to work, as all conditions reported high levels of transfer intention. Conclusion: The finding provides insightful evidence to support the benefits of fostering trainees\u27 active reflections for work-based learning in the Chinese industry training scenario. In contrast, receiving direct comments on how students performed from a manager or trainer, as well as advise on how do better in the future, had no effect on increasing learning or performance. Although the effect of direct feedback is not statistically significant in this context, further research should be done in understanding individuals\u27 thoughts and behaviors when received direct feedbacks received in workplace training. Relatively little workplace research has assessed both workplace learning and performance in the same study,specifically in the Chinese context. While training efficacy likely varies across cultures to begin with, compensation structures in China do not provide the same monetary incentives for workplace learning (i.e. chance to increase income) as Western culture. This means that any way to increase workplace learning should be of extra value, as employees otherwise may not engage in it at all. (DIPF/Orig.

Workplace Learning in China: Transferring Training Into Practice to Improve Performance

Purpose: The present study seeks to examine the efficacy of different training modalities on increasing workplace learning, representatives' intent to transfer what they learned into their work, and importantly how training impacts actual work performance. These relationships are tested in the context of a Chinese division of a multinational pharmaceutical company, where pharmaceutical representatives are tasked with relaying relevant efficacy and safety information on pharmaceutical products to health care professionals who prescribe them to patients. Methods: The present study employed a three-group between-subjects experimental design. Representatives received varying forms of training (instruction only, instruction plus reflection, and instruction, reflection, plus direct feedback) based on experimental conditions. After three training sessions over the course of six weeks, representatives were assessed on how much they learned in the training and their actual work performance through observer assessment of meetings with health care professionals, facilitated by the representatives. Findings: In this study, it was found that the process of actively reflecting on what was learned in training led to increased learning, as well as increased performance, compared to simply studying the material. However, receiving direct feedback on training performance, combined with active reflection training, did not provide any further benefits in terms of learning or work performance. Notably, there were no differences in intent to transfer learned material to work, as all conditions reported high levels of transfer intention. Conclusion: The finding provides insightful evidence to support the benefits of fostering trainees' active reflections for work-based learning in the Chinese industry training scenario. In contrast, receiving direct comments on how students performed from a manager or trainer, as well as advise on how do better in the future, had no effect on increasing learning or performance. Although the effect of direct feedback is not statistically significant in this context, further research should be done in understanding individuals' thoughts and behaviors when received direct feedbacks received in workplace training. Relatively little workplace research has assessed both workplace learning and performance in the same study, specifically in the Chinese context. While training efficacy likely varies across cultures to begin with, compensation structures in China do not provide the same monetary incentives for workplace learning (i.e. chance to increase income) as Western culture. This means that any way to increase workplace learning should be of extra value, as employees otherwise may not engage in it at all.

Response of carbon cycle to drier conditions in the mid-Holocene in central China

The effect of Asian summer monsoon hydrological changes on key biogeochemical processes remains poorly understood. Here, using a suite of biomarkers, the authors reconstruct palaeohydrological conditions during the Holocene and show that the peatland carbon cycle is strongly sensitive to paleohydrological changes