Partition testing is one of the most fundamental and popularly used software testing techniques.It first divides the input domain of the program under test into a set of disjoint partitions,and then creates test cases...Partition testing is one of the most fundamental and popularly used software testing techniques.It first divides the input domain of the program under test into a set of disjoint partitions,and then creates test cases based on these partitions.Motivated by the theory of software cybernetics,some strategies have been proposed to dynamically select partitions based on the feedback information gained during testing.The basic intuition of these strategies is to assign higher probabilities to those partitions with higher fault-detection potentials,which are judged and updated mainly according to the previous test results.Such a feedback-driven mechanism can be considered as a learning processit makes decisions based on the observations acquired in the test execution.Accordingly,advanced learning techniques could be leveraged to empower the smart partition selection,with the purpose of further improving the effectiveness and efficiency of partition testing.In this paper,we particularly leverage reinforcement learning to enhance the state-of-the-art adaptive partition testing techniques.Two algorithms,namely RLAPT_Q and RLAPT_S,have been developed to implement the proposed approach.Empirical studies have been conducted to evaluate the performance of the proposed approach based on seven object programs with 26 faults.The experimental results show that our approach outperforms the existing partition testing techniques in terms of the fault-detection capability as well as the overall testing time.Our study demonstrates the applicability and effectiveness of reinforcement learning in advancing the performance of software testing.展开更多
Test data compression and test resource partitioning （TRP） are essential to reduce the amount of test data in system-on-chip testing. A novel variable-to-variable-length compression codes is designed as advanced fre...Test data compression and test resource partitioning （TRP） are essential to reduce the amount of test data in system-on-chip testing. A novel variable-to-variable-length compression codes is designed as advanced fre- quency-directed run-length （AFDR） codes. Different [rom frequency-directed run-length （FDR） codes, AFDR encodes both 0- and 1-runs and uses the same codes to the equal length runs. It also modifies the codes for 00 and 11 to improve the compression performance. Experimental results for ISCAS 89 benchmark circuits show that AFDR codes achieve higher compression ratio than FDR and other compression codes.展开更多
In social mammals, kinship is an important factor that often affects the interactions among individuals within groups. In primates that live in a multilevel society, kinship may affect affiliative patterns be- tween i...In social mammals, kinship is an important factor that often affects the interactions among individuals within groups. In primates that live in a multilevel society, kinship may affect affiliative patterns be- tween individuals at different scales within the larger group. For this study, we use field observations and molecular methods to reveal the profiles of how kinship affects affiliative behaviors between indi- viduals in a breeding band of wild golden snub-nosed monkeys （Rhinopithecus roxellana）. We use a novel nonparametric test, the partition Mantel test, to measure independently the correlation between kinship and each of three affiliative behaviors. Our results show that more closely related females are more likely to groom each other. Average relatedness between adult females within the same onemale unit （OMU） is higher than that between adult females from different OMUs. We suggest that closely related females may reside in the same OMU in order to attain inclusive fitness benefits, and that kinship plays an important role in maintaining the social structure of this species.展开更多
This paper presents a test resource partitioning technique based on anefficient response compaction design called quotient compactor(q-Compactor). Because q-Compactor isa single-output compactor, high compaction ratio...This paper presents a test resource partitioning technique based on anefficient response compaction design called quotient compactor(q-Compactor). Because q-Compactor isa single-output compactor, high compaction ratios can be obtained even for chips with a small numberof outputs. Some theorems for the design of q-Compactor are presented to achieve full diagnosticability, minimize error cancellation and handle unknown bits in the outputs of the circuit undertest (CUT). The q-Compactor can also be moved to the load-board, so as to compact the outputresponse of the CUT even during functional testing. Therefore, the number of tester channelsrequired to test the chip is significantly reduced. The experimental results on the ISCAS ''89benchmark circuits and an MPEG 2 decoder SoC show that the proposed compaction scheme is veryefficient.展开更多
基金supported by the National Natural Science Foundation of China under Grant Nos.62272037 and 61872039the Beijing Natural Science Foundation under Grant No.4162040+2 种基金the Aeronautical Science Foundation of China under Grant No.2016ZD74004the Fundamental Research Funds for the Central Universities of China under Grant No.FRF-GF-19-B19the Australian Research Council Discovery Project under Grant No.DP210102447.
文摘Partition testing is one of the most fundamental and popularly used software testing techniques.It first divides the input domain of the program under test into a set of disjoint partitions,and then creates test cases based on these partitions.Motivated by the theory of software cybernetics,some strategies have been proposed to dynamically select partitions based on the feedback information gained during testing.The basic intuition of these strategies is to assign higher probabilities to those partitions with higher fault-detection potentials,which are judged and updated mainly according to the previous test results.Such a feedback-driven mechanism can be considered as a learning processit makes decisions based on the observations acquired in the test execution.Accordingly,advanced learning techniques could be leveraged to empower the smart partition selection,with the purpose of further improving the effectiveness and efficiency of partition testing.In this paper,we particularly leverage reinforcement learning to enhance the state-of-the-art adaptive partition testing techniques.Two algorithms,namely RLAPT_Q and RLAPT_S,have been developed to implement the proposed approach.Empirical studies have been conducted to evaluate the performance of the proposed approach based on seven object programs with 26 faults.The experimental results show that our approach outperforms the existing partition testing techniques in terms of the fault-detection capability as well as the overall testing time.Our study demonstrates the applicability and effectiveness of reinforcement learning in advancing the performance of software testing.
基金Supported by the National Natural Science Foundation of China(61076019,61106018)the Aeronautical Science Foundation of China(20115552031)+3 种基金the China Postdoctoral Science Foundation(20100481134)the Jiangsu Province Key Technology R&D Program(BE2010003)the Nanjing University of Aeronautics and Astronautics Research Funding(NS2010115)the Nanjing University of Aeronatics and Astronautics Initial Funding for Talented Faculty(1004-YAH10027)~~
文摘Test data compression and test resource partitioning （TRP） are essential to reduce the amount of test data in system-on-chip testing. A novel variable-to-variable-length compression codes is designed as advanced fre- quency-directed run-length （AFDR） codes. Different [rom frequency-directed run-length （FDR） codes, AFDR encodes both 0- and 1-runs and uses the same codes to the equal length runs. It also modifies the codes for 00 and 11 to improve the compression performance. Experimental results for ISCAS 89 benchmark circuits show that AFDR codes achieve higher compression ratio than FDR and other compression codes.
文摘In social mammals, kinship is an important factor that often affects the interactions among individuals within groups. In primates that live in a multilevel society, kinship may affect affiliative patterns be- tween individuals at different scales within the larger group. For this study, we use field observations and molecular methods to reveal the profiles of how kinship affects affiliative behaviors between indi- viduals in a breeding band of wild golden snub-nosed monkeys （Rhinopithecus roxellana）. We use a novel nonparametric test, the partition Mantel test, to measure independently the correlation between kinship and each of three affiliative behaviors. Our results show that more closely related females are more likely to groom each other. Average relatedness between adult females within the same onemale unit （OMU） is higher than that between adult females from different OMUs. We suggest that closely related females may reside in the same OMU in order to attain inclusive fitness benefits, and that kinship plays an important role in maintaining the social structure of this species.
基金国家自然科学基金，the Sci. & Technol. Project of Beijing，中国科学院资助项目，Synopsys公司资助项目
文摘This paper presents a test resource partitioning technique based on anefficient response compaction design called quotient compactor(q-Compactor). Because q-Compactor isa single-output compactor, high compaction ratios can be obtained even for chips with a small numberof outputs. Some theorems for the design of q-Compactor are presented to achieve full diagnosticability, minimize error cancellation and handle unknown bits in the outputs of the circuit undertest (CUT). The q-Compactor can also be moved to the load-board, so as to compact the outputresponse of the CUT even during functional testing. Therefore, the number of tester channelsrequired to test the chip is significantly reduced. The experimental results on the ISCAS ''89benchmark circuits and an MPEG 2 decoder SoC show that the proposed compaction scheme is veryefficient.
