Current work leverages data caching and operator execution accelerations to reduce the Online Analytical Processing (OLAP) query execution time on the disaggregated architecture with computation, cache, GPU, and storage clusters.However, their optimizations rely heavily on the OLAP engine, thus have defects of passive data fetching and integrated operator executions, leading to poor OLAP query execution performance.To resolve the above problems, we propose the ORION manager to take over the data and operator management capabilities from the OLAP engine for reducing OLAP query execution time.ORION consists of * Zhixin Tong and Jiuchen Shi contributed equally to this work.

With the development of software vulnerability analysis, the evaluation of different bug-detecting tools has become quite important for selecting better-performed ones and improving existing approaches. To obtain a convincing evaluation result, a well-constructed vulnerability corpus is indispensable. However, the existing corpora are either constructed from real-world bugs or artificially designed, suffering various problems like small volume, lack of ground truth, etc. Thus, generating large-scale bug corpora through an automated way has been widely noticed. In this paper, we propose an automated vulnerability injection system to generate code samples with triggerable vulnerabilities. Specifically, the system analyzes a host program with the symbolic execution tool to generate high-coverage test cases. Meanwhile, it identifies the potential bug injection points and performs static taint analysis to mark tainted variables and their relevance to the bug injection points. Based on the variables, the system modifies the host program to vulnerable code samples that could be verified by the test cases. In conclusion, the system realizes the injection of buffer overflow vulnerabilities in $\mathrm{C}/ \mathrm{C}++$ programs. A study case is shown to demonstrate the injection processes, and the evaluation presents our advantages in the realness and magnitude of generated bug samples as well as solving highcoverage test cases.