Edge of Death: Deadlock

I am sure that this is not a deliberate strategy that any company would employ, but it is rather a side effect of a schedule that does not allow enough time for formal analysis. In order to explain the invariant way, let us go back to the GOOFY example that we looked at earlier.

Even without running GOOFY, we can determine right away that it may deadlock; all we need to do is to provide a scenario in which a deadlock occurs—which is exactly what happens when Thread 1 owns Critical Section 1 and waits for Critical Section 2, while Thread 2 owns Critical Section 2 and waits for Critical Section 1. It is easy to prove that an application has a deadlock by describing it, but the converse—namely, proving that an application is deadlock-free —is difficult. This does not make sense from a programming point of view, but it serves to illustrate the point. Possibly even without using a lot of Greek letters and reasoning that qualifies you for a graduate degree in Space Technology?

First, the definition of a critical section requires that either Critical Section 1 is free or that either Thread 1 or Thread 2 has claimed it. Now the only scenario in which a deadlock could occur will be if one thread A is suspended for a critical section that the other thread B owns while A, in turn, owns a critical section that B waits for. However, as soon as any thread owns any critical section, from our intuitive statements above, we can conclude that the other thread must be waiting for Critical Section 1. Thus, the thread that owns one critical section has either both or none, and thus, a scenario in which both threads own one resource each a necessary condition for a deadlock cannot occur.

Yes, except that we have to prove that our intuitive statements are correct. We will come back to that. Will it help if I promise that later on we'll see something that expresses the same but looks more intuitive? You might not be aware of it, but the above discussion is actually something fairly scholarly called "invariant analysis"—which, you remember, is the second approach to detecting deadlocks in multithreaded applications.

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What happens is that we determine some statements about the application that always hold true, no matter what states the two threads are in. Because of this property, those statements are called "invariants" which is Latin for "does not change". Invariants qualify for the top ten list of computer scientists' favorite toys because there are many cool things you can do with them.

In the case of multithreaded applications, you can use them to, well, detect deadlocks: What we did when discussing GOOFY2 was basically describe what a deadlock looks like and then argue that such a deadlock would violate some of the invariants and cannot, therefore, occur. Wouldn't it be great if we could simply feed our application into a computer program that returns all of the invariants and then tells us outright if there is an inherent deadlock in the application?

That way, we would not have to search for invariants and also risk forgetting some of them or misinterpreting others and spend pages and pages arguing why the application could or could not deadlock. You may think you are a good programmer, but I hate to tell you, the program that you just fed me will blow up into smithereens faster than you can say, 'Wazoo!! Yes, that would be great.

I say "in part" because some of the questions involved in detecting deadlocks can effectively be answered by computer programs, whereas others are either not decidable or not effectively computable. Let me list and comment on some of the theorems that theoretical Computer Science has derived for this purpose. Please recall that a system may appear to be deadlocked when it is not. Using what is called a resource allocation graph RAG for any given state, it can be determined whether that state constitutes a deadlock or not.

We will look at resource allocation graphs later. We will look at techniques to compute invariants later in this paper. The problem here is that the computation may not be effective. It should be noted that the invariants of single-threaded applications cannot be computed. This sounds strange at first—we would expect that a multithreaded application, because it is more complex than a single-threaded one, would make statements about the application more difficult, not easier! What is going on here?

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The catch is that an invariant in a multithreaded application is something slightly different from an invariant in a single-threaded application. In the latter one, we are concerned with invariants regarding the state of memory such as "the value of variable i is always 2 greater than the value of variable j , and the respective values of variable p and variable q always add up to 7" , whereas the invariants in a multithreaded application refer to the state of threads such as "if Thread 1 owns Resource 2, then the other threads are in their respective code sections, 3 and 4".

If we wanted the invariants in our multithreaded application to incorporate information about their respective computational states as well such as the values of some of their variables , the problem would be undecidable again. In the next section, I will take you on a journey to the wonderful world of Petri nets and hope to convince you that it pays to view your application slightly different than you did before—namely, as a collection of circles, squares, and arrows. According to the edition of the Encyclopedia of Computer Science , Carl Adam Petri currently works for the Gesellschaft fuer Mathematik und Datenverarbeitung in Bonn, Germany, and, I suspect, probably spends a lot of time wondering why his formalism does not have the attention in the scholarly and business world that it deserves.

Petri nets have been researched in depth since the early s, and in my humble opinion, they provide an excellent framework to analyze and study concurrent systems.

The best and most comprehensive discussion of Petri nets can be found in T. Murata's paper "Petri Nets: In this section, I will summarize the most important aspects of Petri nets, and in the next section, we will see how they can be put to work in applications written for Windows. Petri nets are very general and can be employed to model much more than multithreaded applications; for example, computer hardware or industrial processes may be depicted as Petri nets.

In this paper, I restrict the discussion to those aspects of Petri nets that are applicable to multithreaded applications. A Petri net is a directed graph whose nodes are either places generally drawn as circles , which roughly describe states that a thread can be in, or transitions generally drawn as squares , which roughly describe actions that transform states into one another. Edges may only exist between places and transitions that is, two transitions can never be directly connected to each other, nor can two places.

It is permissible, however, for two or more places to be connected to the same transition important to model synchronization and for one transition to connect to more than one place important to model nondeterminism.

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In order to simulate the dynamic behavior of an application, individual places can be marked this is generally indicated in the Petri net by drawing a black dot into the circle that represents that place , meaning that the thread currently executes code that corresponds to that state.

There is a simple firing rule: A transition can fire if all the places that lead into it called the predecessor or input places are marked and all the places that it connects to called the successor or output places are not marked. If a transition can fire, it may remove all the marks from its predecessor nodes and put marks into all of its successor nodes. Note that the general framework of Petri nets is more flexible: In unrestricted Petri nets, each place is associated with a capacity that describes how many marks at most may be in a place simultaneously, and each edge is associated with an integer that describes how many marks are removed from or inserted into a place when the edge is traversed, respectively.

In this paper, though, I will restrict the discussion to so-called "1-conservative" Petri nets, in which the capacity of each place is assumed to be 1, and each edge will remove exactly one mark from a net if it leads from a place to a transition and add exactly one when it leads from a transition to a place.

This net represents only the while loops that the two threads can be in. The net consists of ten places, four places for each of the two threads, corresponding to the four "states" that each thread can be in:.

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The remaining two places depict Critical Sections 1 and 2, respectively. A mark in one of the places that correspond to thread states implies that the thread executes that particular section of code, and a mark on one of the "critical section" places implies that that critical section is free.

As Figure 2 shows, when transition "ecs1" fires, the marks from p11 and cs2 are removed and a mark is placed into p We see that the transitions labeled "ecs1" or "ecs2" can only fire if the thread is in a state where it is waiting for the critical section and the corresponding critical section is free.

The marks on the net characterize the "initial markings" of the application; that is, both threads are on the top of their respective while loops, ready to claim their respective first critical sections, and both critical sections are unowned.

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Note that we are not interested in what exactly happens during the time a thread owns a critical section. In the version of GOOFY that we presented earlier, the threads do some output to the screen, but the places may represent an arbitrary amount of computation. For example, a multithreaded application is required to serialize output to a device context via a critical section or a mutex object, but what it does while it owns the critical section is of no interest to the Petri net that models it. As long as the code in the critical section does not request any other synchronization resource or does not do any work that requires interaction with other threads, we may depict all of it by just one place.

This is fairly important. A Petri net is an abstraction of an application; that is, it hides some information from us. It would theoretically be possible to take any application statement and transform it 1: But we use the Petri net to model only the interaction and the synchronization between threads, so a lot of those "intermediate" places and transitions may as well be omitted because they make the net less overseeable and do not change anything in the concurrent aspects of the application.

Despite technology being the driver behind digital transformation, people are the true agents of change, so making sure they are engaged and bought into the vision behind such moves is critical to improving the working environment. These findings suggest IT departments may be detached from the experiences of those using them.

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Ison is sure to please older readers with a taste for the quaint. No one's rated or reviewed this product yet. Skip to main content. A serial killer is at large. One item ties the victims together: On a hot Tuesday morning in June, Detective Chef Inspector Harry Brock is called to Richmond Park in south-west London, where the body of a young woman has been found, strangled and half-naked, in the Isabella Plantation. The discovery of further bodies, all women in their twenties, and all with missing bras, suggests a serial killer is at loose. But can he break the deadlock to catch a determined killer?

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