Correct prediction of file accesses can improve system performance by mitigating the relative speed difference between CPU and disks. This paper discusses Program-based Last Successor (PLS) and presents Program-and Userbased Last Successor (PULS), file prediction algorithms that utilize information about the program and user that access the files. Our simulation results show that PLS makes 21% fewer incorrect predictions and PULS makes 24% fewer incorrect predictions than last-successor with

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... ghly the same number of correct predictions that lastsuccessor makes. The cache space wasted on incorrect predictions can be reduced accordingly. We also show that a cache using the Least Recently Used (LRU) caching algorithm can perform better when the PULS is applied. In some cases, a cache using LRU and either PLS or PULS performs better than a cache up to 40 times larger using LRU alone. ), we also need to keep track of the file (say © ), which it has most recently accessed. When accesses the next file (say ) after © , we update the metadata of the © with © , A , and the next time that accesses © on behalf of A © program name, user-successor pairs kept for each file. However, our simulation shows that the vast of majority of files are accessed by six or fewer programs and thus metadata storage is not a problem. The last one is that if a program (say © ) eventually executes another program (say ), the information of is also added to the metadata of © , and it will be predicted accordingly in the future.