The Java Virtual Machine's heap stores all objects created by a running Java application.
Objects are created by the new
, newarray
, anewarray
, and multianewarray
instructions,
but never freed explicitly by the code.
Garbage collection is the process of automatically freeing objects that are no longer referenced by the program.
Garbage collection is the process of automatically freeing objects that are no longer referenced by the program.
This chapter does not describe an official Java garbage-collected heap, because none exists. As mentioned in earlier chapters, the Java Virtual Machine specification does not require any particular garbage collection technique. It doesn't even require garbage collection at all. But until infinite memory is invented, most Java Virtual Machine implementations will likely come with garbage-collected heaps.  JVM specification并没有要求特定的GC技术
Accompanying this chapter on the CD-ROM is an applet that interactively illustrates the material presented in the chapter. The applet, named Heap of Fish, simulates a garbage-collected heap in a Java Virtual Machine. The simulation--which demonstrates a compacting, mark-and-sweep collector--allows you to interact with the heap as if you were a Java program: you can allocate objects and assign references to variables.  At the end of this chapter, you will find a description of this applet and instructions on how to use it.
The name "garbage collection" implies that objects no longer needed by the program are "garbage" and can be thrown away. A more accurate and up-to-date metaphor might be "memory recycling." When an object is no longer referenced by the program, the heap space it occupies can be recycled so that the space is made available for subsequent new objects. The garbage collector must somehow determine which objects are no longer referenced by the program and make available the heap space occupied by such unreferenced objects. In the process of freeing unreferenced objects, the garbage collector must run any finalizers of objects being freed. GC的本质就是memory recycling
In addition to freeing unreferenced objects, a garbage collector may also combat heap fragmentation. Heap fragmentation occurs through the course of normal program execution. New objects are allocated, and unreferenced objects are freed such that free portions of heap memory are left in between portions occupied by live objects. Requests to allocate new objects may have to be filled by extending the size of the heap even though there is enough total unused space in the existing heap. This will happen if there is not enough contiguous free heap space available into which the new object will fit. On a virtual memory system, the extra paging (or swapping) required to service an ever growing heap can degrade the performance of the executing program. On an embedded system with low memory, fragmentation could cause the virtual machine to "run out of memory" unnecessarily. GC也可以用来解决heap fragmentation
Garbage collection relieves you from the burden of freeing allocated memory. Knowing when to explicitly free allocated memory can be very tricky. Giving this job to the Java Virtual Machine has several advantages. First, it can make you more productive. When programming in non-garbage-collected languages you can spend many late hours (or days or weeks) chasing down an elusive memory problem. When programming in Java you can use that time more advantageously by getting ahead of schedule or simply going home to have a life. 由JVM进行GC有几个好处。第一个好处，开发更有效率。
 Garbage collection is an important part of Java's security strategy. Java programmers are unable to accidentally (or purposely) crash the Java Virtual Machine by incorrectly freeing memory. 第二个好处，程序更稳健。
A potential disadvantage of a garbage-collected heap is that it adds an overhead that can affect program performance. The Java Virtual Machine has to keep track of which objects are being referenced by the executing program, and finalize and free unreferenced objects on the fly. This activity will likely require more CPU time than would have been required if the program explicitly freed unnecessary memory. In addition, programmers in a garbage-collected environment have less control over the scheduling of CPU time devoted to freeing objects that are no longer needed. 不好的地方，在于程序的执行效率比较低。
  Second, it must reclaim the heap space used by the garbage objects and make the space available again to the program. GC算法要做两件事情，第一件事情，要检测出哪些object是“垃圾”；第二件事情，把内存空间释放。
Garbage detection is ordinarily accomplished by defining a set of roots and determining reachability from the roots. An object is reachable if there is some path of references from the roots by which the executing program can access the object. The roots are always accessible to the program. Any objects that are reachable from the roots are considered "live." Objects that are not reachable are considered garbage, because they can no longer affect the future course of program execution. 这里在讲object的reachability：从roots开始入手。
The root set in a Java Virtual Machine is implementation dependent, but would always include any object references in the local variables and operand stack of any stack frame and any object references in any class variables. Another source of roots are any object references, such as strings, in the constant pool of loaded classes. The constant pool of a loaded class may refer to strings stored on the heap, such as the class name, superclass name, superinterface names, field names, field signatures, method names, and method signatures. Another source of roots may be any object references that were passed to native methods that either haven't been "released" by the native method. (Depending upon the native method interface, a native method may be able to release references by simply returning, by explicitly invoking a call back that releases passed references, or some combination of both.) Another potential source of roots is any part of the Java Virtual Machine's runtime data areas that are allocated from the garbage-collected heap. For example, the class data in the method area itself could be placed on the garbage-collected heap in some implementations, allowing the same garbage collection algorithm that frees objects to detect and unload unreferenced classes. 这里是讲有哪些object references可以成为roots。
Any object referred to by a root is reachable and is therefore a live object. Additionally, any objects referred to by a live object are also reachable. The program is able to access any reachable objects, so these objects must remain on the heap. Any objects that are not reachable can be garbage collected because there is no way for the program to access them. Any object referred to by a root is reachable and is therefore a live object.
The Java Virtual Machine can be implemented such that
the garbage collector knows the difference between a genuine object reference and a primitive type (for example, an int
)
that appears to be a valid object reference.
(For example, an int
that would point to an object on the heap if it were interpreted as a native pointer.)
Some garbage collectors, however, may choose not to distinguish between genuine object references and look-alikes.
Such garbage collectors are called conservative because they may not always free every unreferenced object.
Sometimes a garbage object will be wrongly considered to be live by a conservative collector,
because an object reference look-alike referred to it.

这里讲GC是不是需要对genuine object reference和primitive type来进行区分。
  The count keeps track of the number of references to that object. Tracing garbage collectors actually trace out the graph of references starting with the root nodes. Objects that are encountered during the trace are marked in some way. After the trace is complete, unmarked objects are known to be unreachable and can be garbage collected. 这里讲了两种基本的方式：reference counting和tracing。
Reference counting was an early garbage collection strategy. In this approach, a reference count is maintained for each object on the heap. When an object is first created and a reference to it is assigned to a variable, the object's reference count is set to one. When any other variable is assigned a reference to that object, the object's count is incremented. When a reference to an object goes out of scope or is assigned a new value, the object's count is decremented. Any object with a reference count of zero can be garbage collected. When an object is garbage collected, any objects that it refers to have their reference counts decremented.  这里讲了reference counting实现的原理。
An advantage of this approach is that a reference counting collector can run in small chunks of time closely interwoven with the execution of the program. This characteristic makes it particularly suitable for real-time environments where the program can't be interrupted for very long. A disadvantage is that reference counting does not detect cycles: two or more objects that refer to one another. An example of a cycle is a parent object that has a reference to a child object that has a reference back to the parent. These objects will never have a reference count of zero even though they may be unreachable by the roots of the executing program. Another disadvantage of reference counting is the overhead of incrementing and decrementing the reference count each time. 这里讲了reference counting的优点和缺点。
Because of the disadvantages inherent in the reference counting approach, this technique is currently out of favor. It is more likely that the Java Virtual Machines you encounter in the real world will use a tracing algorithm in their garbage-collected heaps. 这里讲了reference counting已经不再流行。
Tracing garbage collectors trace out the graph of object references starting with the root nodes. Objects that are encountered during the trace are marked in some way. Marking is generally done by either setting flags in the objects themselves or by setting flags in a separate bitmap. After the trace is complete, unmarked objects are known to be unreachable and can be garbage collected. 这里讲了tracing实现的原理。
The basic tracing algorithm is called "mark and sweep." This name refers to the two phases of the garbage collection process. In the mark phase, the garbage collector traverses the tree of references and marks each object it encounters. In the sweep phase, unmarked objects are freed, and the resulting memory is made available to the executing program. In the Java Virtual Machine, the sweep phase must include finalization of objects. 这里讲了tracing的两个阶段。
Garbage collectors of Java Virtual Machines will likely have a strategy to combat heap fragmentation. Two strategies commonly used by mark and sweep collectors are compacting and copying. Both of these approaches move objects on the fly to reduce heap fragmentation. Compacting collectors slide live objects over free memory space toward one end of the heap. In the process the other end of the heap becomes one large contiguous free area. All references to the moved objects are updated to refer to the new location. 这里讲了Compacting Collector的原理
Updating references to moved objects is sometimes made simpler by adding a level of indirection to object references. Instead of referring directly to objects on the heap, object references refer to a table of object handles. The object handles refer to the actual objects on the heap. When an object is moved, only the object handle must be updated with the new location. All references to the object in the executing program will still refer to the updated handle, which did not move. While this approach simplifies the job of heap defragmentation, it adds a performance overhead to every object access. 这里讲了adding a level of indirection to object references
Copying garbage collectors move all live objects to a new area. As the objects are moved to the new area, they are placed side by side, thus eliminating any free space that may have separated them in the old area. The old area is then known to be all free space. The advantage of this approach is that objects can be copied as they are discovered by the traversal from the root nodes. There are no separate mark and sweep phases. Objects are copied to the new area on the fly, and forwarding pointers are left in their old locations. The forwarding pointers allow the garbage collector to detect references to objects that have already been moved. The garbage collector can then assign the value of the forwarding pointer to the references so they point to the object's new location.
A common copying collector algorithm is called "stop and copy." In this scheme, the heap is divided into two regions. Only one of the two regions is used at any time. Objects are allocated from one of the regions until all the space in that region has been exhausted. At that point program execution is stopped and the heap is traversed. Live objects are copied to the other region as they are encountered by the traversal. When the stop and copy procedure is finished, program execution resumes. Memory will be allocated from the new heap region until it too runs out of space. At that point the program will once again be stopped. The heap will be traversed and live objects will be copied back to the original region. The cost associated with this approach is that twice as much memory is needed for a given amount of heap space because only half of the available memory is used at any time. 这里讲了stop and copy
You can see a graphical depiction of a garbage-collected heap that uses a stop and copy algorithm in Figure 9-1. This figure shows nine snapshots of the heap over time. In the first snapshot, the lower half of the heap is unused space. The upper half of the heap is partially filled by objects. That portion of the heap that contains objects is painted with diagonal gray lines. The second snapshot shows that the top half of the heap is gradually being filled up with objects, until it becomes full as shown in the third snapshot. 这里讲了图中1到3
At that point, the garbage collector stops the program and traces out the graph of live objects starting with the root nodes. It copies each live object it encounters down to the bottom half of the heap, placing each object next to the previously copied object. This process is shown in snapshot four. 这里讲了图中4
Snapshot five shows the heap after the garbage collection has finished. Now the top half of the heap is unused, and the bottom half is partially filled with live objects. The sixth snapshot shows the bottom half is now becoming gradually filled with objects, until it too becomes full in snapshot seven. 这里讲了图中5到7
Once again, the garbage collector stops the program and traces out the graph of live objects. This time, it copies each live object it encounters up to the top half of the heap, as shown in snapshot eight. Snapshot nine shows the result of the garbage collection: the bottom half is once again unused space and the top half is partially filled with objects. This process repeats again and again as the program executes. 这里讲了图中8到9
One disadvantage of simple stop and copy collectors is that all live objects must be copied at every collection. This facet of copying algorithms can be improved upon by taking into account two facts that have been empirically observed in most programs in a variety of languages: 这里讲stop and copy有不足之处。
A major source of inefficiency in simple copying collectors is that they spend much of their time copying the same long-lived objects again and again.
Generational collectors address this inefficiency by grouping objects by age and garbage collecting younger objects more often than older objects. In this approach, the heap is divided into two or more sub-heaps, each of which serves one "generation" of objects. The youngest generation is garbage collected most often. As most objects are short-lived, only a small percentage of young objects are likely to survive their first collection. Once an object has survived a few garbage collections as a member of the youngest generation, the object is promoted to the next generation: it is moved to another sub-heap. Each progressively older generation is garbage collected less often than the next younger generation. As objects "mature" (survive multiple garbage collections) in their current generation, they are moved to the next older generation. 这里讲了Generational Collector的原理。
The generational collection technique can be applied to mark and sweep algorithms as well as copying algorithms. In either case, dividing the heap into generations of objects can help improve the efficiency of the basic underlying garbage collection algorithm. 分代处理的GC可以提高效率。
An adaptive garbage collection algorithm takes advantage of the fact that some garbage collection algorithms work better in some situations, while others work better in other situations. An adaptive algorithm monitors the current situation on the heap and adjusts its garbage collection technique accordingly. It may tweak the parameters of a single garbage collection algorithm as the program runs. It may switch from one algorithm to another on the fly. Or it may divide the heap into sub-heaps and use different algorithms on different sub-heaps simultaneously. 这里讲了Adaptive Collectors的原理。
With an adaptive approach, designers of Java Virtual Machine implementations need not choose just one garbage collection technique. They can employ many techniques, giving each algorithm work for which it is best suited. 这里讲了Adaptive Collectors的灵活性。
 It is in general impossible to predict exactly when (or even if) a garbage collector will be invoked and how long it will take to run.  Such garbage collection pauses can sometimes be long enough to be noticed by users. Garbage collection pauses can also prevent programs from responding to events quickly enough to satisfy the requirements of real-time systems. If a garbage collection algorithm is capable of generating pauses lengthy enough to be either noticeable to the user or make the program unsuitable for real-time environments, the algorithm is said to be disruptive. To minimize the potential disadvantages of garbage collection compared to the explicit freeing of objects, a common design goal for garbage collection algorithms is to minimize or, if possible, eliminate their disruptive nature.
One approach to achieving (or at least attempting to achieve) non-disruptive garbage collection is to use algorithms that collect incrementally. An incremental garbage collector is one that, rather than attempting to find and discard all unreachable objects at each invocation, just attempts to find and discard a portion of the unreachable objects. Because only a portion of the heap is garbage collected at each invocation, each invocation should in theory run in less time. A garbage collector that can perform incremental collections, each of which is guaranteed (or at least very likely) to require less than a certain maximum amount of time, can help make a Java virtual machine suitable for real-time environments.
A common incremental collector is a generational collector, which during most invocations collects only part of the heap. As mentioned earlier in this chapter, a generational collector divides the heap into two or more generations, each of which is awarded its own sub-heap. Taking advantage of the empirical observation that most objects have very short lifetimes, a generational collector collects the sub-heaps of younger generations more often than those of older generations. Because every sub-heap except that of the most mature generation (the mature object space) can be given a maximum size, a generational collector can in general ensure that incremental collections of all but the most mature generation will complete within a certain maximum amount of time. The reason the mature object space cannot be given a maximum size is that any objects that don't fit in the sub-heaps of the younger generations must by definition go into the mature object space.
The train algorithm, which was first proposed by Richard Hudson and Eliot Moss and is currently used by Sun's Hotspot virtual machine, specifies an organization for the mature object space of a generational collector. The purpose of the train algorithm is to provide time-bounded incremental collections of the mature object space.
The train algorithm divides the mature object space into fixed-sized blocks of memory, each of which is collected individually during a separate invocation of the algorithm. The name, "train algorithm," comes from the way the algorithm organizes the blocks. Each block belongs to one set. The blocks within a set are ordered, and the sets themselves are ordered. To help explain the algorithm in their original paper, Hudson and Moss called blocks "cars" and sets "trains." In this metaphor, the mature object space plays the role of a railway station. Blocks within the same set are ordered, just like cars within the same train are ordered. The sets are ordered within the mature object space much like trains might line up on track 1, track 2, track 3, and so on, at a railway station. This organization is shown graphically in Figure 9-2.
Figure 9-2. Heap organization for the train algorithm.
Trains (sets of blocks) are assigned numbers in the order in which they are created. At the railway station, therefore, the first train to arrive pulls into track 1 and becomes train 1. The next train to arrive pulls into track 2 and becomes train 2. The next train to arrive pulls into track 3 and becomes train 3, and so on. Given this numbering scheme, a smaller train number will always indicate an older train. Within a train, cars (blocks) are added only to the end of the train. The first car added to a train is car 1. The next car added to that same train is car 2. Within a single train, therefore, a smaller car number indicates an older car. This numbering scheme yields an overall order for blocks in the mature object space.
Figure 9-2 shows three trains, numbered 1, 2, and 3. Train 1 has four cars, labeled 1.1 through 1.4. Train 2 has three cars, labeled 2.1 through 2.3. And train 3 has five cars, labeled 3.1 though 3.5. This manner of labeling cars, in which labels are composed of the train number, a dot, and the car number, indicates the overall order of the blocks contained in the mature object space. Car 1.1 precedes car 1.2, which precedes car 1.3, and so on. The last car in train 1 also precedes the first car in train 2, so car 1.4 precedes car 2.1. Likewise, car 2.3 precedes car 3.1. Each time the train algorithm is invoked, it will garbage collect one and only one block: the lowest numbered block. Thus, the first time the train algorithm is invoked on the heap shown in Figure 9-2, it will collect block 1.1. The next time is invoked, it will collect block 1.2. After it collects the last block of train 1, the algorithm will at its next invocation collect the first block of train 2.
Objects arrive in the mature object space when they get old enough to be promoted from the sub-heap of a younger generation. Whenever objects are promoted into the mature object space from younger generations, they are either added to any existing train except the lowest-numbered train, or one or more new trains are created to hold them. Thus you can think of new objects arriving at the railway station in one of two ways. Either they roll up in cars that are shunted onto the end of any existing train except the lowest numbered train, or they pull into the railway station on a brand new train. 这里讲了new objects从younger generations进入到mature object space后，应该存放到什么位置。
Each time the train algorithm is invoked, it collects either the lowest numbered car of the lowest numbered train or it collects the entire lowest numbered train. The algorithm first checks for references into any car of the lowest numbered train. If no references exist outside the lowest numbered train that refer to objects contained inside the lowest numbered train, the entire lowest numbered train contains garbage and can be reclaimed. This first step enables the train algorithm to collect large cyclic data structures that don't fit within a single block. Because of the second step of train algorithm, which will be described next, such large cyclic data structures are guaranteed to eventually end up in the same train.
If the lowest numbered train was determined to all be garbage, the train algorithm reclaims the space occupied by all objects in all the cars of the lowest numbered train and returns. (At that point, that invocation of the train algorithm is complete.) If the lowest numbered train was not all garbage, however, the algorithm turns its attention to the lowest numbered car of the lowest numbered train. In the process, the algorithm will either move or free any object in that car. The algorithm starts by moving any object that is referenced from outside the lowest numbered car to some other car. Any objects remaining in the car after this moving process are unreferenced and can be garbage collected. The train algorithm then reclaims the space occupied by the entire lowest numbered car (thereby freeing any unreferenced objects still sitting in the lowest numbered car) and returns. 这里讲了两种情况
The key to guaranteeing that cyclic data structures all end up in the same train lies in how the algorithm moves objects. If an object sitting in the car being collected is referenced from outside the mature object space, that object is moved to any train but the one being collected. If an object is referenced from a different train within the mature object space, that object is moved to the referencing train. Moved objects are then scanned for references back into the car being collected. Any newly referenced objects are moved to the referencing train. Newly moved objects are then scanned for references back into the car being collected, and the process repeats until no more references exist from other trains into the car being collected. If a receiving train runs out of space, the algorithm will create a new car (an empty block) and append it to the end of that train.
Once no more references exist from outside the mature object space or from other trains within the mature object space into the car being collected, any objects referenced from outside the car being collected are known to be referenced from other cars of the same train. The algorithm moves such objects to the last car of the same, lowest numbered train. These objects are then scanned for references back into the car being collected. Any newly referenced objects are moved to the end of the same train and scanned. This process repeats until no more references of any kind exist into the car being collected. The algorithm then reclaims the space occupied by the entire lowest-numbered car, freeing any unreferenced objects that still happen to be sitting in that car, and returns.
At each invocation, therefore, the train algorithm either collects the lowest numbered car of the lowest numbered train, or it collects the entire lowest numbered train. One of the most important facets of the train algorithm is that it guarantees that large cyclic data structures will eventually be collected, even though they may not fit in a single block. Because objects are moved into trains from which they are referenced, related objects tend to cluster together. Eventually, all the objects of a garbage cyclic data structure, no matter how large, will end up in the same train. Increasing the size of the cyclic data structure will only increase the number of cars that ultimately form the same train. Because the train algorithm first checks for a lowest numbered train that is completely garbage before settling for just the lowest numbered car, it is able to collect cyclic data structures of any size.
As mentioned previously, the goal of the train algorithm is to provide time-bounded incremental collections of the mature object space of a generational collector. Because the blocks (cars) can be given a maximum size and only one block is collected at each invocation, the train algorithm can most often ensure that each invocation will require less than some maximum amount of time. Unfortunately, the train algorithm can't guarantee that each invocation will take less than some maximum amount of time, because the algorithm must do more than just copy the objects.
To facilitate the collection process, the train algorithm makes use of remembered sets. A remembered set is a data structure that contains information about all references that reside outside a car or train but point into that car or train. The algorithm maintains one remembered set for each car and each train in the mature object space. The remembered set for a particular car, therefore, contains information about the set of references that refer to (or "remember") the objects in that car. An empty remembered set indicates that the objects contained in the car or train are unreferenced (have been "forgotten") by any objects or variables outside the car or train. Forgotten objects are unreachable and can be garbage collected.
The remembered set is an implementation technique that helps the train algorithm do its work more efficiently. When the train algorithm discovers a car with an empty remembered set, it knows the car contains only garbage and can immediately reclaim all the memory occupied by the car. Likewise, when the train algorithm discovers a train with an empty remembered set, it can immediately reclaim all the memory occupied by the entire train. When the train algorithm moves an object to a different car or train, the information in the remembered set helps it efficiently update all references to the moved object so that they correctly refer to the objects new location.
Although the amount of bytes the train algorithm may have to copy during one invocation is limited by the size of a block, the amount of work required to move a popular object, an object that has many references to it, is impossible to limit. Each time the algorithm moves an object, it must traverse the remembered set of that object and update each reference to that object so that the reference points to the new location. Because the number of references to an object cannot be limited, the amount of time required to update the references to a moved object cannot be limited. Thus, in certain cases the train algorithm may still be disruptive. Nevertheless, despite the degenerative case of popular objects, the train algorithm for the most part does a very good job of collecting the mature object space of a generational garbage collector in an incremental, non-disruptive way.
In Java, an object may have a finalizer: a method that the garbage collector must run on the object prior to freeing the object. The potential existence of finalizers complicates the job of any garbage collector in a Java Virtual Machine. 这里讲GC在释放object占用的内存空间之前，要先调用finalize()方法。
To add a finalizer to a class, you simply declare a method in that class as follows :
begin // On CD-ROM in file gc/ex2/Example2.java class Example2 { protected void finalize() throws Throwable { //... super.finalize(); } //... } end
A garbage collector must examine all objects it has discovered to be unreferenced to see
if any include a finalize()
method.
 First, the garbage collector must in some way detect unreferenced objects (call this Pass I). Then, it must examine the unreferenced objects it has detected to see if any declare a finalizer. If it has enough time, it may at this point in the garbage collection process finalize all unreferenced objects that declare finalizers. 这里讲Pass I，先找到unreferenced objects，再调用finalizer。
After executing all finalizers, the garbage collector must once again detect unreferenced objects starting with the root nodes (call this Pass II). This step is needed because finalizers can "resurrect" unreferenced objects and make them referenced again. Finally, the garbage collector can free all objects that were found to be unreferenced in both Passes I and II. 这里讲Pass II，再接着找unreferenced objects，最后释放内存空间。
To reduce the time it takes to free up some memory, a garbage collector can optionally insert a step between the detection of unreferenced objects that have finalizers and the running of those finalizers. Once the garbage collector has performed Pass I and found the unreferenced objects that need to be finalized, it can run a miniature trace starting not with the root nodes but with the objects waiting to be finalized. Any objects that are (1) not reachable from the root nodes (those detected during Pass I) and (2) not reachable from the objects waiting to be finalized cannot be resurrected by any finalizer. These objects can be freed immediately. 这里讲了一种节省时间的方式。
If an object with a finalizer becomes unreferenced, and its finalizer is run, the garbage collector must in some way ensure that it never runs the finalizer on that object again. If that object is resurrected by its own finalizer or some other object's finalizer and later becomes unreferenced again, the garbage collector must treat it as an object that has no finalizer. 要确保finalizer只执行一次。
As you program in Java, you must keep in mind that it is the garbage collector that runs finalizers on objects. Because it is not generally possible to predict exactly when unreferenced objects will be garbage collected, it is not possible to predict when object finalizers will be run. As mentioned in Chapter 2, "Platform Independence," you should avoid writing programs for which correctness depends upon the timely finalization of objects. For example, if a finalizer of an unreferenced object releases a resource that is needed again later by the program, the resource will not be made available until after the garbage collector has run the object finalizer. If the program needs the resource before the garbage collector has gotten around to finalizing the unreferenced object, the program is out of luck. it is not possible to predict when object finalizers will be run.
In versions prior to 1.2, every object on the heap is in one of three states from the perspective of the garbage collector: reachable, resurrectable, or unreachable. An object is in the reachable state if the garbage collector can "reach" the object by tracing out the graph of object references starting with the root nodes. Every object begins its life in the reachable state, and stays reachable so long as the program maintains at least one reachable reference to the object. As soon as the program releases all references to an object, however, the object becomes resurrectable.
An object is in the resurrectable state if it is not currently reachable by tracing the graph of references starting with the root nodes,
but could potentially be made reachable again later when the garbage collector executes some finalizer.
All objects, not just objects that declare a finalize()
method, pass through the resurrectable state.
As mentioned in the previous section, the finalizer for an object may "resurrect" itself or any other resurrectable object by making the objects reachable again.
Because any object in the resurrectable state could potentially be made reachable again by its own or some other object's finalize()
method,
the garbage collector cannot reclaim the memory occupied by a resurrectable object before it makes certain the object won't be brought back to life through the execution of a finalizer.
By running the finalizers of all resurrectable objects that declare a finalize()
method,
the garbage collector will transform the state of all resurrectable objects, either back to the reachable state (for objects that get resurrected),
or forward to the unreachable state.
The unreachable state indicates not only that an object is no longer reachable, but also that the object cannot be made reachable again through the execution of some finalizer. Unreachable objects can no longer have any affect on the running program. The garbage collector, therefore, is free to reclaim the memory they occupy.
In version 1.2, the three original reachability states -- reachable, resurrectable, and unreachable -- were augmented by three new states: softly, weakly, and phantom reachable. Because these three new states represent three new (progressively weaker) kinds of reachability, the state known simply as "reachable" in versions prior to 1.2 is called "strongly reachable" starting with 1.2. Any object referenced directly from a root node, such as a local variable, is strongly reachable. Likewise, any object referenced directly from an instance variable of a strongly reachable object is strongly reachable.
The weaker forms of reachability involve an entity that was first introduced in version 1.2: the reference object.
A reference object encapsulates a reference to some other object, called the referent.
All reference objects are instances of subclasses of the abstract java.lang.ref.Reference
class.
The family of Reference
classes, which is shown in Figure 9-3,
includes three direct subclasses: SoftReference
, WeakReference
, and PhantomReference
.

The fundamental difference between a strong reference and
its three progressively weaker cousins -- soft, weak, and phantom references
-- is that whereas a strong reference prevents its referent from being garbage collected, soft, weak, and phantom references do not.
Figure 9-3. The Reference
family.
To create a soft, weak, or phantom reference,
you simply pass a strong reference to the constructor of the appropriate type of reference object.
For example, to create a soft reference to a particular Cow
object,
you pass to the constructor of a new SoftReference
object a strong reference that refers to the Cow
object.
By maintaining a strong reference to the SoftReference
object, you maintain a soft reference to the Cow
object.
Figure 9-4 shows such a SoftReference
object, which encapsulates a soft reference to a Cow
object.
The SoftReference
object is strongly referenced from a local variable, which, like all local variables, serves as a root node for the garbage collector.
As mentioned previously, references contained in garbage collection root nodes and in the instance variables of strongly reachable objects are strong references.
Because the SoftReference
object shown in Figure 9-4 is referenced by a strong reference, the SoftReference
object is strongly reachable.
Assuming that this SoftReference
object contains the only reference to the Cow
object,
the Cow
object is softly reachable.
The reason the Cow
is softly reachable is that the garbage collector can only reach the Cow
object from the root nodes by traversing a soft reference.
Figure 9-4. A reference object and its referent.
Once a reference object is created, it will continue to hold its soft, weak or phantom reference to its referent until it is cleared by the program or the garbage collector.
To clear a reference object, the program or garbage collector need only invoke clear()
,
a method defined in classReference
, on the reference object.
Clearing a reference object invalidates the soft, weak, or phantom reference contained in the reference object.
For example, if the program or garbage collector were to invoke clear()
on the SoftReference
object shown in Figure 9-4,
the soft reference to the Cow
object would be invalidated, and the Cow
object would no longer be softly reachable.
As mentioned previously, the purpose of reference objects is to enable you to hold references to objects that the garbage collector is free to collect.
Put another way, the garbage collector is allowed to change the reachability state of any object that is not strongly reachable.
Because it is often important to keep track of reachability state changes brought about by the garbage collector when you hold soft, weak, or phantom references,
you can arrange to be notified when such changes occur.
To register interest in reachability state changes, you associate reference objects with reference queues.
A reference queue is an instance of class java.lang.ref.ReferenceQueue
to which the garbage collector will append (or "enqueue") reference objects involved in reachability state changes.
By setting up and monitoring reference queues, you can stay apprised of interesting reachability state changes performed asynchronously by the garbage collector.
To associate a reference object with a reference queue,
you simply pass a reference to the reference queue as a constructor parameter when you create the reference object.
A reference object so created, in addition to holding a reference to the referent, will hold a reference to the reference queue.
When the garbage collector makes a relevant change to the reachability state of the referent,
it will append the reference object to its associated reference queue.
For example, when the WeakReference
object shown in Figure 9-5 was created,
two references were passed to the constructor: a reference to a Fox
object and a reference to a ReferenceQueue
object.
When the garbage collector decides to collect the weakly reachable Fox
object,
it will clear the WeakReference
object and either at that or some later time append the WeakReference
object to its reference queue.
Figure 9-5. A reference object associated with a reference queue.
To append a reference object to the end of its associated queue, the garbage collector invokes enqueue()
on the reference object.
The enqueue()
method, which is defined in superclass Reference
, appends the reference object to a reference queue
only if the object was associated with a queue when it was created, and only the first time enqueue()
is invoked on the object.
Programs can monitor a reference queue in two ways, either by polling with the poll()
method or by blocking with the remove()
method.
If a reference object is waiting in the queue when either poll()
or remove()
is invoked on the queue object,
the method will remove that object from the reference queue and return it.
If no reference object is waiting in the queue, however, poll()
will immediately return null
,
but remove()
will block until the next reference object gets enqueued.
Once a reference objects arrives in the queue, remove()
will remove and return it.
The garbage collector enqueues soft, weak, and phantom reference objects in different situations to indicate three different kinds of reachability state changes. The meanings of the six reachability states and the circumstances under which state changes occur are as follow:
finalize()
method itself, then its finalizer will have been run), and is reachable from the roots via one or more (uncleared) phantom reference objects.
As soon as an object referenced by a phantom reference object becomes phantom reachable, the garbage collector will enqueue it.
The garbage collector will never clear a phantom reference.
All phantom references must be explicitly cleared by the program.
 You can also see this difference in that the garbage collector clears soft and weak reference objects before enqueueing them, but not phantom reference objects. Thus, the garbage collector enqueues soft reference objects to indicate their referents have just left the softly reachable state. Likewise, the garbage collector enqueues weak reference objects to indicate their referents have just left the weakly reachable state. But the garbage collector enqueues phantom reference objects to indicate their referents have entered the phantom reachable state. Phantom reachable objects will remain phantom reachable until their reference objects are explicitly cleared by the program.
The garbage collector treats soft, weak, and phantom objects differently because each is intended to provide a different kind of service to the program. Soft references enable you to create in-memory caches that are sensitive to the overall memory needs of the program. Weak references enable you to create canonicalizing mappings, such as a hash table whose keys and values will be removed from the map if they become otherwise unreferenced by the program. Phantom references enable you to establish more flexible pre-mortem cleanup policies than are possible with finalizers.
To use the referent of a soft or weak reference, you invoke get()
on the reference object.
If the reference hasn't been cleared, you'll get a strong reference to the referent, which you can then use in the usual way.
If the reference has been cleared, you'll get null
back.
If you invoke get()
on a phantom reference object, however, you'll always get null
back,
even if the reference object hasn't yet been cleared.
Because the phantom reachable state is only attained after an object passes through the resurrectable state,
a phantom reference object provides no way to access to its referent.
Invoking get()
on a phantom reference object always returns null
,
even if the phantom reference hasn't yet been cleared,
because if it returned a strong reference to the phantom reachable object,
it would in effect resurrect the object.
Thus, once an object reaches phantom reachability, it cannot be resurrected.
Virtual machine implementations are required to clear soft references before throwing OutOfMemoryError
,
but are otherwise free to decide when or whether to clear them.
Implementations are encouraged, however, to clear soft references only when the programs demand for memory exceeds the supply,
to clear older soft references before newer ones, and to clear soft references that haven't been used recently before soft references that have been used recently.
Soft references enable you to cache in memory data that you can more slowly retrieve from an external source, such as a file, database, or network. So long as the virtual machine has enough memory to fit the softly referenced data on the heap together with all the strongly referenced data, the soft reference will in general be strong enough to keep the softly referenced data on the heap. If memory becomes scarce, however, the garbage collector may decide to clear the soft references and reclaim the space occupied by the softly referenced data. The next time the program needs to use that data, it will have to be reloaded from the external source. In the mean time, the virtual machine has more room to accommodate the strongly (and other softly) referenced memory needs of the program.
Weak references are similar to soft references, except that whereas the garbage collector is free to decide whether or not to clear soft references to softly reachable objects,
it must clear weak references to weakly reachable objects as soon as it determines the objects are weakly reachable.
Weak references enable you to create canonicalizing mappings from keys to values.
The java.util.WeakHashMap
class uses weak references to provide just such a canonicalizing mapping.
You can add key-value pairs to a WeakHashMap
instance via the put()
method,
just like you can to an instance of any class that implements java.util.Map
.
But inside the WeakHashMap
, the key objects are held via weak reference objects that are associated with a reference queue.
If the garbage collector determines that a key object is weakly reachable,
it will clear and enqueue any weak reference objects that refer to the key object.
The next time the WeakHashMap
is accessed,
it will poll the reference queue and extract all weak reference objects that the garbage collector put there.
The WeakHashMap
will then remove from its mapping any key-value pairs for keys whose weak reference object showed up in the queue.
Thus, if you add a key-value pair to a WeakHashMap
,
it will remain there so long as the program doesn't explicitly remove it with the remove()
method and
the garbage collector doesn't determine that the key object is weakly reachable.
Phantom reachability indicates that an object is ready for reclamation.
When the garbage collector determines that the referent of a phantom reference object is phantom reachable,
it appends the phantom reference object to its associated reference queue.
(Unlike soft and weak reference objects, which can optionally be created without associating them with a reference queue,
phantom reference objects cannot be instantiated without associating the reference object with a reference queue.)
You can use the arrival of a phantom reference in a reference queue to trigger some action that you wish to take at the end of an object's lifetime.
Because you can't get a strong reference to a phantom reachable object (the get()
method always returns null
),
you won't be able to take any action that requires you to have access to the instance variables of the target.
Once you have finished the pre-mortem cleanup actions for a phantom reachable object,
you must invoke clear()
on the phantom reference objects that refer to it.
Invoking clear()
on a phantom reference object is the coup de gras for its referent,
sending the referent from the phantom reachable state to its final resting place: unreachability.
The Heap of Fish applet, shown in Figures 9-6 through 9-9, demonstrates a compacting, mark and sweep, garbage-collected heap. To facilitate compaction, this heap uses indirect handles to objects instead of direct references. It is called Heap of Fish because the only type of objects stored on the heap for this demonstration are fish objects, defined as follows:
begin // On CD-ROM in file gc/ex1/YellowFish.java class YellowFish { YellowFish myFriend; } // On CD-ROM in file gc/ex1/BlueFish.java class BlueFish { BlueFish myFriend; YellowFish myLunch; } // On CD-ROM in file gc/ex1/RedFish.java class RedFish { RedFish myFriend; BlueFish myLunch; YellowFish mySnack; } end
As you can see, there are three classes of fish: red, yellow, and blue. The red fish is the largest as it has three instance variables. The yellow fish, with only one instance variable, is the smallest fish. The blue fish has two instance variables and is therefore medium- sized. 这里讲三条鱼：red fish（大鱼）、blue fish（中鱼）和yellow fish（小鱼）。
The instance variables of fish objects are references to other fish objects.
BlueFish.myLunch
, for example, is a reference to a YellowFish
object.
In this implementation of a garbage-collected heap, a reference to an object occupies four bytes.
Therefore, the size of the instance data of a RedFish
object is twelve bytes,
a BlueFish
object is eight bytes, and
a YellowFish
object is four bytes.
这里讲三条鱼占用空间大小：red fish（大鱼-12 byte）、blue fish（中鱼-8 byte）和yellow fish（小鱼-4 byte）。
Heap of Fish has five modes, which can be selected via radio buttons at the bottom left of the applet. When the applet starts it is in swim mode. Swim mode is just a gratuitous animation, vaguely reminiscent of the familiar image of a big fish about to eat a medium-sized fish, which is about to eat a small fish.  In the allocate fish mode, you can instantiate new fish objects. In the assign references mode, you can build a network of local variables and fish that refer to other fish. In garbage collect mode, a mark and sweep operation will free any unreferenced fish. The compact heap mode allows you to slide heap objects so that they are side by side at one end of the heap, leaving all free memory as one large contiguous block at the other end of the heap. 这里讲了5种mode
The allocate fish mode, shown in Figure 9-6, allows you to allocate new fish objects on the heap. In this mode you can see the two parts that make up the heap: the object pool and handle pool. The object pool is a contiguous block of memory from which space is taken for new objects. It is structured as a series of memory blocks. Each memory block has a four-byte header that indicates the length of the memory block and whether or not it is free. The headers are shown in the applet as black horizontal lines in the object pool. 这里讲了heap分成object pool和handle pool两个部分。先来介绍object pool，谈了一下header。
Figure 9-6. The allocate fish mode of the Heap of Fish applet.
The object pool in Heap of Fish is implemented as an array of int
s.
The first header is always at objectPool[0]
.
The object pool's series of memory blocks can be traversed by hopping from header to header.
Each header gives the length of its memory block, which also reveals where the next header is going to be.
The header of the next memory block will be the first int
immediately following the current memory block.
这里再着讲headers
When a new object is allocated, the object pool is traversed until a memory block is encountered with enough space to accommodate the new object.
Allocated objects in the object pool are shown as colored bars.
YellowFish
objects are shown in yellow, BlueFish
in blue, and RedFish
in red.
Free memory blocks, those that currently contain no fish, are shown in white.
不同类型的鱼用不同的颜色表示
The handle pool in Heap of Fish is implemented as an array of objects of a class named ObjectHandle
.
An ObjectHandle
contains information about an object, including the vital index into the object pool array.
The object pool index functions as a reference to the object's instance data in the object pool.
The ObjectHandle
also reveals information about the class of the fish object.
As mentioned in Chapter 5, "The Java Virtual Machine," every object on the heap must in some way be associated with its class information stored in the method area.
In Heap of Fish, the ObjectHandle
associates each allocated object with information such as its class--whether
it is a RedFish
, BlueFish
, or YellowFish
--and some data used in displaying the fish in the applet user interface.
这里开始讲handle pool。首先，handle pool中包含的元素是ObjectHandle；接着ObjectHandle包含的信息有哪些：object reference和class information。
The handle pool exists to make it easier to defragment the object pool through compaction.
References to objects, which can be stored in local variables of a stack or the instance variables of other objects, are not direct indexes into the object pool array.
They are instead indexes into the handle pool array.
When objects in the object pool are moved for compaction, only the corresponding ObjectHandle
must be updated with the object's new object pool array index.
这里讲了handle pool的作用。
Each handle in the handle pool that refers to a fish object is shown as a horizontal bar painted the same color as the fish to which it refers. A line connects each handle to its fish instance variables in the object pool. Those handles that are not currently in use are drawn in white. 这里讲handle pool和object pool的关联关系。
The assign references mode, shown in Figure 9-7, allows you to build a network of references between local variables and allocated fish objects. A reference is merely a local or instance variable that contains a valid object reference. There are three local variables which serve as the roots of garbage collection, one for each class of fish. If you do not link any fish to local variables, then all fish will be considered unreachable and freed by the garbage collector.
Figure 9-7. The assign references mode of the Heap of Fish applet.
The assign references mode has three sub-modes: move fish, link fish, and unlink fish. You can select the sub-mode via radio buttons at the bottom of the canvas upon which the fish appear. In move fish mode, you can click on a fish and drag it to a new position. You might want to do this to make your links more visible or just because you feel like rearranging fish in the sea.
In link fish mode, you can click on a fish or local variable and drag a link to another fish. The fish or local variable you initially drag from will be assigned a reference to the fish you ultimately drop upon. A line will be shown connecting the two items. A line connecting two fish will be drawn between the nose of the fish with the reference to the tail of the referenced fish.
Class YellowFish
has only one instance variable, myFriend
, which is a reference to a YellowFish
object.
Therefore, a yellow fish can only be linked to one other yellow fish.
When you link two yellow fish, the myFriend
variable of the "dragged from" fish will be assigned the reference to the "dropped upon" fish.
If this action were implemented in Java code, it might look like:
begin // Fish are allocated somewhere YellowFish draggedFromFish = new YellowFish(); YellowFish droppedUponFish = new YellowFish(); // Sometime later the assignment takes place draggedFromFish.myFriend = droppedUponFish; end
Class BlueFish
has two instance variables, BlueFish myFriend
and YellowFish myLunch
.
Therefore, a blue fish can be linked to one blue fish and one yellow fish.
Class RedFish
has three instance variables, RedFish myFriend
, BlueFish myLunch
, and YellowFish mySnack
.
Red fish can therefore link to one instance of each class of fish.
In unlink fish mode, you can disconnect fish by moving the cursor over the line connecting two fish. When the cursor is over the line, the line will turn black. If you click a black line the reference will be set to null and the line will disappear.
The garbage collect mode, shown in Figure 9-8, allows you to drive the mark and sweep algorithm. The Step button at the bottom of the canvas takes you through the garbage collection process one step at a time. You can reset the garbage collector at any time by clicking the Reset button. However, once the garbage collector has swept, the freed fish are gone forever. No manner of frantic clicking of the Reset button will bring them back.
Figure 9-8. The garbage collect mode of the Heap of Fish applet.
The garbage collection process is divided into a mark phase and a sweep phase. During the mark phase, the fish objects on the heap are traversed depth-first starting from the local variables. During the sweep phase, all unmarked fish objects are freed.
At the start of the mark phase, all local variables, fish, and links are shown in white. Each press of the Step button advances the depth-first traversal one more node. The current node of the traversal, either a local variable or a fish, is shown in magenta. As the garbage collector traverses down a branch, fish along the branch are changed from white to gray. Gray indicates the fish has been reached by the traversal, but there may yet be fish further down the branch that have not been reached. Once the terminal node of a branch is reached, the color of the terminal fish is changed to black and the traversal retreats back up the branch. Once all links below a fish have been marked black, that fish is marked black and the traversal returns back the way it came.
At the end of the mark phase, all reachable fish are colored black and any unreachable fish are colored white. The sweep phase then frees the memory occupied by the white fish.
The compact heap mode, shown in Figure 9-9, allows you to move one object at a time to one end of the object pool. Each press of the Slide button will move one object. You can see that only the object instance data in the object pool moves; the handle in the handle pool does not move.
Figure 9-9. The compact heap mode of the Heap of Fish applet.
The Heap of Fish applet allows you to allocate new fish objects, link fish, garbage collect, and compact the heap. These activities can be done in any order as much as you please. By playing around with this applet you should be able to get a good idea how a mark and sweep garbage-collected heap works. There is some text at the bottom of the applet that should help you as you go along. Happy clicking.
The CD-ROM contains the source code examples from this chapter in the gc
directory.
The Heap of Fish applet is contained in a web page on the CD-ROM in file applets/HeapOfFish.html
.
The source code for this applet is found alongside its class files,
in the applets/HeapOfFish
directory.
For more information about the material presented in this chapter, visit the resources page: http://www.artima.com/insidejvm/resources.


{% extends "base.html" %} {% load static from staticfiles %} {% block extrahead %} {% endblock %} {% block title %}Worlds at War - New Trade{% endblock %} {% block content %}
Please correct the error{{ form.errors | pluralize }} below.
{% endif %} {% if message %} {% endif %} Each trade accepted will cost you {{cost}} GEU.{% if warprotection != None %} Warning: you are under protection! If you send ships, your protection will end.
{% endif %} {% if indefwar != None %} Warning: you are in a defensive war! If you send ships, you will suffer approval and stability losses.
{% endif %}


--- layout: post title: ESP8266 with Web Server using Arduino IDE date: '2015-12-10 05:38:15 -0500' categories: - Electronics - Programming tags: [] comments: ---
I saw a talk about internet of things today. Got me thinking about the ESP8266. I've messed with them a little bit before, but I never really got one working, I don't think.
I gave it another try tonight and I've got a simple web server running on one. Here's how I did it:
First, I bought one of these usb to serial adapters. Previously I had been trying to use and Arduino as the usb to serial adapter. I think this could probably work, but it added that unnecessary level of complexity and doubt that can get in the way. Also, I only had an Uno on hand, so I was using 5V. The ESP is a 3.3V device and I wasn't doing any level shifting or anything. Again, maybe it would have just worked.
Next, I wired the ESP up to the serial adapter like this:
That GPIO0 pin functions both as an I/O pin, and as the pin that tells the microcontroller to get ready to have its firmware flashed. To write new firmware, you have to hold that pin down, I'm told.
Next, I installed a new copy of the Arduino IDE. I had been using the one in the Ubuntu repository (which is an older version) and I was having trouble. Now I'm using 1.6.6. To install the ESP8266 package, I basically followed the "Using Git Version" section of this Github.
I cd'd into the new Arduino directory and then followed these instructions:
{% highlight bash %} cd hardware mkdir esp8266com cd esp8266com git clone https://github.com/esp8266/Arduino.git esp8266 cd esp8266/tools python get.py {% endhighlight %}
Then I restarted the IDE.
I chose the HelloServer example from the ESP8266WebServer folder. It looks like this:
{% highlight c %}
#include Next, I selected "Generic ESP8266 Module" as the board and USBasp as the programmer, and uploaded. After the upload was successful, I unplugged GPIO0 and let it float. I used my router's configuration page to figure out which IP had been assigned to my ESP8266. It was easy to find it in the list of connected devices, since it was called ESP_something. I pointed my browser at the ESP's IP and it worked!


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REGoth
Contents:
Extending the Documentation
Setting up a Test-Application
World
Waynet
Characters
Creating a new Component
Case-Study: Kinds of Objects in Gothic
Case-Study: Scene Structure
Case-Study: Character Statemachine
Case-Study: Daedalus VM
REGoth
Docs
»
Welcome to REGoth’s documentation!
View page source
Welcome to REGoth’s documentation!
¶
Contents:
Extending the Documentation
Modifying an existing chapter
Adding a new chapter
Setting up a Test-Application
World
Loading a World
Using the world
Waynet
What is the Waynet?
The Waynet-Components
How Pathfinding works
Characters
Inserting a Character
Inserting the Hero
Shrinking and Un-Shrinking
Components making up a Character
Creating a new Component
Files to create
Header File
Source File
RTTI File
RTTI Type ID
CMake
Case-Study: Kinds of Objects in Gothic
Vob
NPC (Non-Player-Character)
MOB (Interactive Objects)
Case-Study: Scene Structure
Logic
Visuals
Case-Study: Character Statemachine
Buttons and AI
Priorities
States
Animation naming
Standing-Substate description
Architecture
Case-Study: Daedalus VM
DaedalusVM in ZenLib
Design decisions
Parts of a DaedalusVM
Indices and tables
¶
Index
Module Index
Search Page
-. doxygenindex:


In 1998 while in college, I experienced my first panic attack. It happened actually in a very calm and serene moment, I was very happy and was about to go to bed with my girlfriend. That’s when it hit me, my mind was racing faster then I could handle it, I started sweating, feeling nauseous, like I had lost my mind. I was convinced I went insane. I couldn’t sit still so I got up and drove over 100 miles to one of my work sites just to try and shake it off. After an exhausting night I got home and was mentally paralyzed at what had just happened to me. My grades were horrible that quarter as you can imagine.
After about 2 years trying to do research and learning about my illness – The hardest part was trying to figure out what I exactly had, and to un train my natural aversion to mental illness. I bought books, read articles on the internet, tried to exercise, eat healthy, sleep adequately etc. I also tried to take alternative drugs to heal myself (St. John’s Wort, Tea, meditation, breathing exercises etc) Eventually after 2 years of painful bouts of panic attacks – it seem to go away.
One day at work during a meeting I had this uncontrollable urge to urinate, and no matter what I did it seemed to not go away. I had to excuse myself from work numerous times and I knew people were confused. Embarrassed I just told them that I was taking allergy medication and it made me have bowel problems. At this point I knew that I had to seek professional help.
I went to see a Doctor and he prescribed me Paxil. Thank God, it worked immediately – all the problems went away.
The biggest problem about it is I may very well be on it for life. It’s not cheap either $133 for 30 25mg pills. I have been on it now for 3 years and I think I might be on it for life. Anytime I stop taking it, I start to feel the panic come back. Also if you miss a dose I get bad headaches and nausea. But considering this drug probably saved my life – I will not complain.
Thanks
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


This course will cover the following aspects of computer programming:
All course materials are available online at http://vknight.org/cfm/. You can also find all the source files that create that website at http://github.com/drvinceknight/cfm/.
The course notes are in the form of lab sheets and are all available to you. These are written using Jupyter notebooks (a tool you will learn to use yourself). You will see mathematics and explanations as well as computer code. For example here is some code to raise $2$ to the power of $10$:
2 ** 10
The structure of the course is 3 hours of contact time:
The lab sheets include optional exercises, solutions to them are in the notebooks that you can download from the class site. I recommend you work on those exercises without looking at the solutions. You can ask for feedback and advice in lab sessions and I will also go over specific solutions if required in the post class meeting.
Note that this class requires you to work on the course content outside of contact time. I will not be going over the lab sheets directly in class so I recommend you do those in your own time. At any time you are welcome to view my personal notes for the various meetings we will be having: http://vkcfm.readthedocs.io/
If you would like some information about the pedagogic approach: you can find my "teaching philosophy" here: https://vknight.org/tch-phi/
It is possible that the course notes will change: for things like typos and clarifications, all of the notes are hosted openly on github and if you're interested you can find a list of all changes here: https://github.com/drvinceknight/cfm/commits/master
There are various distributions of Python, we will use Anaconda which comes packaged with a variety of other useful tools (including the notebooks I mentioned above).
To install it on your personal machine follow these steps:
We will use a Jupyter notebook which runs in your browser. To open a local server find the Continuum navigator and click on Jupyter. You do not need to be connected to the internet to use this.
This video is a demo of using a notebook.
Please use whatever resources you need to be successful in this class. Let me know if I can help with anything.
In class activities will often involve you writing some code: if you have a laptop you can use it but it is not required.
I will hold 2-3 hours a week for office hours during which you may come and get help. Specific hours will be determined collaboratively as a class during the first class meeting.
This module is assessed using an individual piece of coursework. After week 7, this will be the main focus of our work.
Source code: @drvinceknight Powered by: Python Jupyter Mathjax Github pages Skeleton css


Before proceeding, you will need to check the box confirming you agree to the updated terms and conditions, (opens in a new window) of the service.
You will be required to do this each time we update our terms and conditions.


We aim to not only make your pizza experience delicious but also memorable with our great customer service and friendly ambiance.
Enjoy our Funky Furahiday offer where you get two large pizzas for the price of one. We also offer delivery services at an additional fee of sh.200
Our prices range from sh.600 for regular, sh.800 for medium to sh.1000 for large. Visit us today for the ultimate pizza experience!
Deluxe Pizza
Classic Pizza


--- title: New to church bodyclass: new --- {{> base.header}} {{> site-blocks.header-block-new}} {{> site-blocks.block-service}}
We have Liberty Kids, which is for children from nursery year through to Year 6. The children are generally in the main service for praise and worship and then will have opportunity to go out and have crazy with their kids church leaders.
You can register your child before the service starts, or if you miss that, please just take them along to the kids church and register them then.
Yes, we have space for mums to take their children, but also to sit with newborns during the service. Please feel free to have your children in the main service. We are family and want you as mums to be a part of what is going on as much as possible.
If you are planning to attend one of our Sunday morning services, you will be greeted by one of our friendly welcoming team members who will help direct you to available parking. We have several spots reserved just for first-time visitors.
Dress comfortably, we're a church of diverse people. You'll feel right at home wearing anything from shorts, to jeans to smart casual.


Numbers 14:18
The LORD is long-suffering, and of great mercy, forgiving iniquity and transgression, and by no means clearing the guilty, visiting the iniquity of the fathers upon the children unto the third and fourth generation.


“She opened the cage and the bird darted into the free air which was the only environment it understood. As it circled the room, its wings brushed the far wall. It shivered an instant, hung suspended as if supported by some unseen hand, and died as it fell to the floor. Neither the bird nor Tarmo had knowledge of the concealed, highly charged panels which recorded, both fluoroscopically and photographically, the images of all those who entered World Center. The image of the bird had appeared on the fluorescent screen. The photographic circuit had been made. And the technicians would curse a burned out circuit.” — Anna Hunger & R DeWitt Miller, The Man Who Lived Forever (clearly the bird did not)


In the Healthchecks source code, /docker/ directory, you can find a sample configuration for running the project with Docker and Docker Compose.
Note: The Docker configuration is a recent addition, and, for the time being, should be considered experimental.
Note: For the sake of simplicity, the sample configuration starts a single database node and a single web server node, both on the same host. It does not handle TLS termination.
/docker/.env
file.
As a minimum, set the following fields:DEFAULT_FROM_EMAIL
– the "From:" address for outbound emailsEMAIL_HOST
– the SMTP serverEMAIL_HOST_PASSWORD
– the SMTP passwordEMAIL_HOST_USER
– the SMTP usernameSECRET_KEY
– secures HTTP sessions, set to a random valueCreate and start containers:
$ cd docker
$ docker-compose up
Create a superuser:
$ docker-compose run web /opt/healthchecks/manage.py createsuperuser
Open http://localhost:8000 in your browser and log in with the credentials from the previous step.
If you plan to expose your Healthchecks instance to the public internet, make sure you put a TLS-terminating reverse proxy in front of it.
Important: This Dockerfile uses UWSGI, which relies on the X-Forwarded-Proto header to determine if a request is secure or not. Make sure your TLS-terminating reverse proxy:
For example, in NGINX you can use the $scheme
variable like so:
proxy_set_header X-Forwarded-Proto $scheme;


Astronomy, Electronics, C#, C++, Ardunio, SQL, JAVA, Amateur Radio
Some of the ares of my skills include
I do get alot of pleasure from writing something new that may have never been attempted before.
Okay not everyting is successful but if you dont try you will never know.
HTML
CSS
C#
C++
Arduino
SigFox
LoRaWAN
Contact Me!
Please feel free to contact me via the following email address:


{% extends 'base.html' %} {% load static %} {% block content %}
Password Has been changed successfully. Please Login Here


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{% extends "base.html" %} {% block stuff %} {% if projects == 'all' %}
Choose which columns you would like to see in the Projects table. Click a heading to select / deselect all checkboxes in that group.


Real-time Visualization of US Twitter Sentiment
Stack
: Storm Topology, Twitter Streaming API, Bing Maps API, JMS, ActiveMQ, Camel, WebSockets and D3.js
Start Viz
Stop Viz


Simulation of the Sleeping Barber Problem
Barber
Seat 1
Seat 2
Seat 3
Seat 4
Seat 5
Seat 6
Seat 7
Enter
Exit
Waiting Seats = 7
waiting = 0
For Barber:
Sleeping
Awake
For Seats:
Available
Occupied


From Maruni’s 2016 collection, the Rumpa Sängen are simple, light, and playful. Designed by English designer Jasper Morrison.
$2645.00 CAD
A counter stool designed in 1935 by one of the world's most prominent architects - Alvar Aalto.
$4520.00 CAD
The Adam Stool collection is inspired by industrial design, an artist's studio, and a workshop.
$3020.00 CAD


How to Change from Gecode 1.3.1 to Gecode 2.0.x
As Gecode 2.0.0 is a major revision of Gecode, your programs that are written for Gecode 1.3.1 are likely to require some modifications before they work again. All modifications are straightforward, though.This short summary shows how to adapt your models and linker invocation, for changes to propagator implementations, etc, please consult the changelog.
IntVar and BoolVar
Boolean variables (BoolVar) are not any longer integer variables (IntVar). The same holds for variable arrays (BoolVarArray, IntVarArray). So, you can not mix Boolean and integer variables in the same array (use two different arrays) and you can not cast between them. If you want to link the value of a BoolVar to the value of an IntVar you have to use a channel constraint. Posting constraints remains unchanged, as all constraints offer two overloaded versions (one for IntVar, one for BoolVar).Regular constraint
The regular constraint has been renamed to extensional (after all, it is an extensionally specified constraint). The old name is still available in the MiniModel module.If you want to use regular expressions, you have to add
#include "gecode/int/minimodel.hh"
Boolean constraints
In order to make the interface to Boolean constraints more regular and similar to set constraints, Boolean constraints are available as rel constraints. That is, instead ofbool_and(home, x, y, z);
bool_and(home, x, y);
Branching
Values and types for selecting how to branch have been made uniform. Replace BVAL_* by INT_VAL_*, BVAR_* by INT_VAR_*, and so on.Global cardinality constraint
The interface for the global cardinality constraint has been simplified. The constraint is now called count. Please check the documentation for details.Sortedness constraint
The sortedness constraint has been renamed to sorted.Linking
Some generic functionality has been put into its own library (libgecodesupport
GecodeSupport.dll


| RootLogger Constructor | Construct a RootLogger |
| Additivity (inherited from Logger) | Gets or sets a value indicating if child loggers inherit their parent's appenders. |
| Appenders (inherited from Logger) | Get the appenders contained in this logger as an ICollection. |
| EffectiveLevel | Gets the assigned level value without walking the logger hierarchy. |
| Hierarchy (inherited from Logger) | Gets or sets the Hierarchy where this Logger instance is attached to. |
| Level | Gets or sets the assigned Level for the root logger. |
| Name (inherited from Logger) | Gets the logger name. |
| Parent (inherited from Logger) | Gets or sets the parent logger in the hierarchy. |
| Repository (inherited from Logger) | Gets the ILoggerRepository where this Logger instance is attached to. |
| AddAppender (inherited from Logger) | Add newAppender to the list of appenders of this Logger instance. |
| CloseNestedAppenders (inherited from Logger) | Closes all attached appenders implementing the IAppenderAttachable interface. |
| Equals (inherited from Object) | Determines whether the specified Object is equal to the current Object. |
| GetAppender (inherited from Logger) | Look for the appender named as name
|
| GetHashCode (inherited from Object) | Serves as a hash function for a particular type, suitable for use in hashing algorithms and data structures like a hash table. |
| GetType (inherited from Object) | Gets the Type of the current instance. |
| IsEnabledFor (inherited from Logger) | Checks if this logger is enabled for a given Level passed as parameter. |
| Log (inherited from Logger) | Overloaded. This is the most generic printing method that is intended to be used by wrappers. |
| RemoveAllAppenders (inherited from Logger) | Remove all previously added appenders from this Logger instance. |
| RemoveAppender (inherited from Logger) | Overloaded. Remove the appender passed as parameter form the list of appenders. |
| ToString (inherited from Object) | Returns a String that represents the current Object. |
| CallAppenders (inherited from Logger) | Deliver the LoggingEvent to the attached appenders. |
| Finalize (inherited from Object) | Allows an Object to attempt to free resources and perform other cleanup operations before the Object is reclaimed by garbage collection. |
| ForcedLog (inherited from Logger) | Overloaded. Creates a new logging event and logs the event without further checks. |
| MemberwiseClone (inherited from Object) | Creates a shallow copy of the current Object. |
RootLogger Class | log4net.Repository.Hierarchy Namespace


cat JSON_DOCNAME | dataset create COLLECTION_NAME KEY
dataset create -i JSON_DOCNAME COLLECTION_NAME KEY
dataset create COLLECTION_NAME KEY JSON_VALUE
dataset create COLLECTION_NAME KEY JSON_FILENAME
create adds or replaces a JSON document to a collection. The JSON document can be read from a standard in, a named file (with a “.json” file extension) or expressed literally on the command line.
In the following four examples jane-doe.json is a file on the
local file system contains JSON data containing the JSON_VALUE
of {"name":"Jane Doe"}
. The KEY we will create is r1.
Collection is “people.ds”. The following are equivalent in
resulting record.
cat jane-doe.json | dataset create people.ds r1
dataset create -i blob.json people.ds r1
dataset create people.ds r1 '{"name":"Jane Doe"}'
dataset create people.ds r1 jane-doe.json


Biography
Information about yourself, your research interests and other pertinent details that enhance your ORCID record.
Visibility
{{ ngOrcidDefaultVisibilityLabel }} {{ defaultVisibility | visibilityStringLabel }}.


Add all required logic to login. Make sure you are able to login using the API (using username(root) and password(Api@2020))
- Save the JWT token received after successful login.
- Use the token for Authorization of ALL subsequest request.


I only put this here because I could - and because leogaggl asked me to.
Sorry but this code only works in a newer browser such as Google Chrome.
Copyright © 2016 Simon Bruce, See license