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Memory thrashing is repeated costly cycling of memory pages out of and back into computer memory, leaving little useful computation between page faults. Active demand can exceed the available page frames, especially when multiprogramming admits too many operating-system processes. A high page fault rate during initial loading alone does not establish memory thrashing. ^[ref]

Consider one operating-system process making the 20 memory references $1,2,3,4,1,2,3,4,\dots ,1,2,3,4$: five repetitions of four memory pages. Start with an empty resident set, use demand paging and exact LRU replacement, and assume no prefetching or competing operating-system processes. A hit finds the requested memory page resident; a miss requires a nonresident page fault. With three page frames, references 1–3 load pages 1–3. Reference 4 evicts page 1, reference 5 reloads page 1 and evicts page 2, and the cycle continues: every return finds its memory page evicted. With four page frames, only the first four references miss; all four memory pages then remain resident.

The four initial misses with four page frames are compulsory first-use misses from the empty resident set. They are startup work; the three-page frame case keeps faulting after startup. This makes the difference between memory thrashing and loading a new working set visible. For the three-page frame trace, each reused memory page has three distinct intervening memory pages, so LRU replacement has already evicted it before its next use.

To quantify the cost, assume each hit takes 100 nanoseconds and each miss incurs an additional 1 millisecond of page fault service, followed by the same 100-nanosecond memory access. These are toy latencies, not measurements. With miss probability $p$, the expected value of access time isThe service cost is additional: it does not include the final 100 nanoseconds. Thus $p=1$ gives $1,000,100\mathrm{ns}$ and $p=0.2$ gives $200,100\mathrm{ns}$, approximately a fivefold ratio over the complete trace. Over references 5–20, the corresponding ratio is $1,000,100/100=10,001$: repeated page faults dominate the useful accesses. The expected value model follows the additive miss-penalty convention of OSTEP chapter 22, section 22.1. ^[ref]

Not every page fault performs disk input-output: demand paging can allocate zero-filled memory pages, and copy-on-write can copy an existing page frame. The toy service cost models expensive misses; the miss trace alone establishes residency behavior, while memory thrashing additionally concerns repeated costly cycling. ^[ref]

Possible remedies are more resident page frames, less multiprogramming, or reorganizing accesses to improve temporal locality. For this toy sequence, one extra page frame suffices under LRU replacement; that is not a universal threshold or policy. Page replacement alone cannot make every simultaneously needed memory page fit.

// Target: computer-science.bigb

An operating-system process's working set is the set of distinct memory pages used in a declared recent window. Here the window counts memory references, not clock time: let $r_i$ identify the memory page accessed by the $i$th memory reference, and let the positive integer $\Delta$ be the window length. Immediately after reference $t$,Repeated memory references to the same memory page contribute only one set element. The working set size is the cardinality $|W(t,\Delta )|$. This recent footprint estimates current demand; it cannot guarantee which memory pages future memory references will need. The resident set instead records which memory pages are actually present in computer memory.

For the 20-reference sequence in memory thrashing and $\Delta =4$, the successive working sets begin $\{1\}$, $\{1,2\}$, $\{1,2,3\}$ and $\{1,2,3,4\}$. At $t=5$, the window is references 2–5, namely $2,3,4,1$, so $W(5,4)=\{1,2,3,4\}$ again. Every later four-reference window contains all four memory pages. Under three-page frame LRU replacement, however, the resident set at $t=5$ is $\{1,3,4\}$: page 2 was evicted. Consequently the working set size is four even though only three memory pages are resident. Under four-page frame LRU replacement, the resident set contains the complete working set after reference 4.

Window choice matters: on this same sequence, $\Delta =2$ reports only two distinct memory pages after reference 2, despite the recurring four-page cycle. A short window forgets useful memory pages sooner; a long window retains evidence from older phases. Enlarging the window can only enlarge or preserve the working set at fixed $t$, because the shorter window is contained in the longer one. No single window is best for every workload.

For a concrete multiprogramming budget, suppose three operating-system processes each have a four-page working set, no shared page frames, and only eight page frames are available for their data. Their combined demand is 12 page frames; all three working sets cannot be resident together. Letting two operating-system processes run while the third waits makes their eight-page demand fit in this simplified model. Real budgets also reserve computer memory for the operating system and other uses; shared memory pages must not be counted repeatedly as different physical copies.

Peter J. Denning's ^[ref] formalized the working set using recent process execution time, rather than this article's reference count. Its central insight connected memory demand to process scheduling: deciding which operating-system processes run also decides which working sets need room. Temporal locality makes recent use informative, without making it a promise about the future. The beautiful distinction is between a large possible address space and the smaller footprint of the current activity.