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| 1 | Metabolic engineering of Yarrowia lipolytica for scutellarin production显示文摘Scutellarin related drugs have superior therapeutic effects on cerebrovascular and cardiovascular diseases.Here,an optimal biosynthetic pathway for scutellarin was constructed in Yarrowia lipolytica platform due to its excellent metabolic potential.By integrating multi-copies of core genes from different species,the production of scutellarin was increased from 15.11 mg/L to 94.79 mg/L and the ratio of scutellarin to the main by-product was improved about 110-fold in flask condition.Finally,the production of scutellarin was improved 23-fold and reached to 346 mg/L in fed-batch bioreactor,which was the highest reported titer for de novo production of scutellarin in microbes.Our results represent a solid basis for further production of natural products on unconventional yeasts and have a potential of industrial implementation. | Yina Wang Xiaonan Liu Bihuan Chen Wei Liu Zhaokuan Guo Xiangyu Liu Xiaoxi Zhu Jiayu Liu Jin Zhang Jing Li Lei Zhang Yadi Gao Guanghui Zhang Yan Wang MIqbal Choudhary Shengchao Yang Huifeng Jiang | 2022 | Synthetic and Systems Biotechnology2022，7，3： | 1 |
| 2 | Skyfire:一种数据驱动的种子生成工具显示文摘程序深层次的漏洞一般隐藏在程序执行阶段,而对于自动化的模糊测试(Fuzzing)来说很难触发该类漏洞。论文“Skyfire:Data—Driven Seed Generation for Fuzzing”提出了一种数据驱动的种子生成方法——skyfire。 | 杨鑫 Junjie Wang Bihuan Chen Lei Wei Yang Liu | 2018 | 中国教育网络2018，，11： | 0 |
| 3 | Identifying change patterns of API misuses from code changes显示文摘Library or framework APIs are difficult to learn and use,leading to unexpected software behaviors or bugs.Hence,various API mining techniques have been introduced to mine API usage patterns about the co-occurring of API calls or pre-conditions of API calls.However,they fail to mine patterns about an API call itself(e.g.,whether the arguments of the API call are correctly set and whether the API is suitably chosen over other similar APIs).To bridge this gap,we propose Cpam to identify change patterns(in the form of a pair of APIs before and after code changes)to fix API misuses,using historical code changes.Given a set of target APIs and a corpus of open-source projects,Cpam first selects the commits that potentially fix API misuses from the corpus,then extracts changes to API misuses in each selected commit,and finally identifies change patterns of API misuses.We implement Cpam for Java,and conduct large-scale evaluation,targeting Java SE APIs and using a corpus of 1162 Java projects.Our experimental results demonstrate Cpam’s effectiveness and efficiency.By applying identified change patterns to bug detection,we find 44 new bugs,and 18 of them have been confirmed and fixed. | Wenjian LIU Bihuan CHEN Xin PENG Qinghao SUN Wenyun ZHAO | 2021 | Science China(Information Sciences)2021，64，3： | 0 |
| 4 | BATON:symphony of random testing and concolic testing through machine learning and taint analysis显示文摘Random testing is scalable but often fails to hit corner program behaviors,while systematic testing(e.g.,concolic execution)is promising to cover corner program behaviors but is not scalable to explore all program behaviors.Prior attempts to integrate random testing with systematic testing lack targeted guidance.In this paper,we propose a guided hybrid testing approach,named BATon,to synergize random testing with concolic testing.It integrates the knowledge inside test cases and their executions into a conditional execution graph,and uses such knowledge to guide test case generation.Specifically,we learn classification models for some conditionals in the conditional execution graph in a demand-driven way.These models are used to guide random testing to reach and cover partially-covered conditionals.We further employ targeted concolic testing to cover conditionals that cannot be fully covered by guided random testing.We implemented BATon for Java and evaluated it on three benchmarks.The results show that BATon improved branch coverage and mutation score over random testing by 16.2%–29.4%and 19.0%–30.0%,over adaptive random testing by 16.8%–33.8%and 19.4%–34.2%,over concolic testing by 2.3%–29.9%and 2.9%–30.1%,and over simple hybrid testing by 1.6%–14.5%and 1.4%–18.7%. | Bihuan CHEN Yang LIU Xin PENG Yijian WU Shengchao QIN | 2023 | Science China(Information Sciences)2023，66，3： | 0 |
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