Abstract-Regression testing assures changed programs against unintended amendments. Rearranging the execution order of test cases is a key idea to improve their effectiveness. Paradoxically, many test case prioritization techniques resolve tie cases using the random selection approach, and yet random ordering of test cases has been considered as ineffective. Existing unit testing research unveils that adaptive random testing (ART) is a promising candidate that may replace random testing (RT). In this paper, we not only propose a new family of coverage-based ART techniques, but also show empirically that they are statistically superior to the RT-based technique in detecting faults. Furthermore, one of the ART prioritization techniques is consistently comparable to some of the best coverage-based prioritization techniques (namely, the "additional" techniques) and yet involves much less time cost.

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Coverage-based fault-localization techniques find the fault-related positions in programs by comparing the execution statistics of passed executions and failed executions. They assess the fault suspiciousness of individual program entities and rank the statements in descending order of their suspiciousness scores to help identify faults in programs. However, many such techniques focus on assessing the suspiciousness of individual program entities but ignore the propagation of infected program states among them. In this paper, we use edge profiles to represent passed executions and failed executions, contrast them to model how each basic block contributes to failures by abstractly propagating infected program states to its adjacent basic blocks through control flow edges. We assess the suspiciousness of the infected program states propagated through each edge, associate basic blocks with edges via such propagation of infected program states, calculate suspiciousness scores for each basic block, and finally synthesize a ranked list of statements to facilitate the identification of program faults. We conduct a controlled experiment to compare the effectiveness of existing representative techniques with ours using standard benchmarks. The results are promising.

Laparoscopic surgery for rectal cancer is as safe and effective as open surgery in terms of oncology outcomes. Long-term survival for patients with rectal cancer undergoing laparoscopic surgery were similar to those undergoing conventional open surgery, thus supporting the continued use of laparoscopic surgery in Chinese patients with rectal cancer.

The hospitalization rate for CRC has increased in Guangdong in recent years. The characteristics of CRC from the five hospitals located in the four different areas of Guangdong Province are also different. Further studies are needed to assess more recent trend in the incidence and prevalence of CRC as well as the respective roles of genetic and environmental factors in CRC.

Abstract-In continuous integration, a tight integration of test case prioritization techniques and fault-localization techniques may both expose failures faster and locate faults more effectively. Statistical fault-localization techniques use the execution information collected during testing to locate faults. Executing a small fraction of a prioritized test suite reduces the cost of testing, and yet the subsequent fault localization may suffer. This paper presents the first empirical study to examine the impact of test case prioritization on the effectiveness of fault localization. Among many interesting empirical results, we find that coverage-based techniques and random ordering can be more effective than distribution-based techniques in supporting statistical fault localization. Furthermore, the integration of random ordering for test case prioritization and statistical fault localization can be effective in locating faults quickly and economically.

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