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A least squares straight line regression gives Expected No of Lunches = 886266 + 004577 No of People A statistical test indicates that the t is almost perfect for the calculated points

2 A list of which locks certain threads are currently waiting to acquire So, the first step in enabling creation of a wait graph is to track this information Once a deadlock is suspected, we can use these two things to build a graph Building a graph is not cheap, as it requires tracking the aforemen tioned information, inspecting many shared data structures (depending on the specific mechanisms you've used to track the information), and involves a loop that is O(N) where N is the size of the longest possible wait chain in your system Common approaches include doing this on demand

when a debugger is attached, for debug builds only, or to run the algorithm in response to an acquisition timeout Here is some C# code that implements the general algorithm

A few states maintain disability insurance funds, from which payments are made to employees who are unable to work due to illness or injury This tax is sometimes a joint payment by both employees and employers, and in other cases is borne only by employees Exhibit 116 shows the range of employer tax rates, employee withholding rates, taxable wage limits, and employee coverages for each state where a disability fund is used

void Det e c t Dea d l o c k ( o b j e c t t a rget Loc k ) { D i c t i o n a ry< obj e c t , Thread > loc kOwn e r s D i c t i o n a ry<Threa d , obj e c t > wa i t i n g F o r s

A manufacturer has a lot of 400 items, 50 of which are special The items are inspected one at a time until 10 of the special items have been found If the inspected items are not replaced in the lot, the random variable representing the number of special items found leads to the negative hypergeometric distribution The problem here is our nal example of a waiting time problem Had the inspected items been replaced, a questionable quality control procedure to say the least, we would encounter the negative binomial distribution, which we have seen when waiting for the rth success in a binomial process Recall that if Y is the waiting time for the rth success then P(Y = y) = y 1 r 1 p (1 p)y r p, y = r, r + 1, r 1

I I C reate a q u e u e t o cont a i n t h re a d s wa i t i n g for loc k s : Qu e u e < Wa i t Pa i r > waitG r a p h new Queue<WaitPa i r > ( ) j

I I Add the c u r rent t h read to t h e l i s t of t h re a d s a l ready s e e n WaitPa i r c u rrent new WaitPa i r ( Thread C u rrentThrea d , t a rget Loc k ) j

Specifics of State Disability Funds Employee Withholding Rate 09% 05% 05% 05% (2) 03% 17% Taxable Wage Limit $56,916 $36,524 $23,900 $6,240 $9,000 $45,300

.

We showed previously that the expected value of Y is E(Y ) = r/p, a fact we will return to later Now we de ne the negative hypergeometric random variable To be speci c, suppose the lot of N items contains k special items We want to sample, without replacement, until we nd c of the special items Then the sampling process stops Again Y is the random variable denoting the number of trials necessary Since the rst