[Objective] The aim was to test the controlling effect of cleaning steriliza- tion system, material conveying system, and fermentation jar cooling system with equip- ments of fruit wine production line introduced in t...[Objective] The aim was to test the controlling effect of cleaning steriliza- tion system, material conveying system, and fermentation jar cooling system with equip- ments of fruit wine production line introduced in this study and its auto-control sys- tem field assembled and debugged. [Method] Based on controlling equipment and setting parameters on the configuration interface, the operation state of the control equipments could be real-time monitored and controlled with the help of configura- tion software. [Result] The result showed that the equipment system could reduce the temperature into 12 ℃ with the error of ＋0.5 ℃within 110 minutes when the fermentation temperature is set at 12 ℃ in real production. [Conclusion] The auto- control system of fruit wine production line was easy to be assembled and de- bugged to meet demands of different fruit wine productions.展开更多
Fault localization is an important topic in software testing, as it enables the developer to specify fault location in their code. One of the dynamic fault localization techniques is statistical debugging. In this stu...Fault localization is an important topic in software testing, as it enables the developer to specify fault location in their code. One of the dynamic fault localization techniques is statistical debugging. In this study, two statistical debugging algorithms are implemented, SOBER and Cause Isolation, and then the experimental works are conducted on five programs coded using Python as an example of well-known dynamic programming language. Results showed that in programs that contain only single bug, the two studied statistical debugging algorithms are very effective to localize a bug. In programs that have more than one bug, SOBER algorithm has limitations related to nested predicates, rarely observed predicates and complement predicates. The Cause Isolation has limitations related to sorting predicates based on importance and detecting bugs in predicate condition. The accuracy of both SOBER and Cause Isolation is affected by the program size. Quality comparison showed that SOBER algorithm requires more code examination than Cause Isolation to discover the bugs.展开更多
基金Supported by Fundamental Research Foundation of GXAAS(GNK2013YM02)~~
文摘[Objective] The aim was to test the controlling effect of cleaning steriliza- tion system, material conveying system, and fermentation jar cooling system with equip- ments of fruit wine production line introduced in this study and its auto-control sys- tem field assembled and debugged. [Method] Based on controlling equipment and setting parameters on the configuration interface, the operation state of the control equipments could be real-time monitored and controlled with the help of configura- tion software. [Result] The result showed that the equipment system could reduce the temperature into 12 ℃ with the error of ＋0.5 ℃within 110 minutes when the fermentation temperature is set at 12 ℃ in real production. [Conclusion] The auto- control system of fruit wine production line was easy to be assembled and de- bugged to meet demands of different fruit wine productions.
文摘Fault localization is an important topic in software testing, as it enables the developer to specify fault location in their code. One of the dynamic fault localization techniques is statistical debugging. In this study, two statistical debugging algorithms are implemented, SOBER and Cause Isolation, and then the experimental works are conducted on five programs coded using Python as an example of well-known dynamic programming language. Results showed that in programs that contain only single bug, the two studied statistical debugging algorithms are very effective to localize a bug. In programs that have more than one bug, SOBER algorithm has limitations related to nested predicates, rarely observed predicates and complement predicates. The Cause Isolation has limitations related to sorting predicates based on importance and detecting bugs in predicate condition. The accuracy of both SOBER and Cause Isolation is affected by the program size. Quality comparison showed that SOBER algorithm requires more code examination than Cause Isolation to discover the bugs.
