Abstract:
One or more processors determine whether a first procedure within a first program meets a first criterion. The first criterion is included in a plurality of criteria that are configured for pessimistic aliasing. Responsive to the determination, one or more processors determine whether to flag the first procedure for pessimistic aliasing.

Description:
BACKGROUND OF THE INVENTION 
     The present invention relates generally to the field of computer program optimization, and more particularly to defining alias sets for procedures that can access variables declared outside of the procedure scope. 
     An alias occurs when different variables point directly or indirectly to a single area of storage. An alias set is a set of aliases created during aliasing. Aliasing refers to assumptions made during program optimization about which variables can point to or occupy the same storage area. 
     SUMMARY 
     Embodiments of the present invention provide a method, system, and program product to define alias sets. One or more processors determine whether a first procedure within a first program meets a first criterion, wherein the first criterion is included in a plurality of criteria that are configured for pessimistic aliasing. Responsive to the determination, one or more processors determine whether to flag the first procedure for pessimistic aliasing. 
    
    
     
       BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS 
         FIG. 1  is a functional block diagram illustrating a computing environment, in accordance with an exemplary embodiment of the present invention. 
         FIG. 2  illustrates a first example of operational processes for deciding whether to generate a pessimistic or an accurate alias set, on a computing device within the environment of  FIG. 1 , in accordance with an exemplary embodiment of the present invention. 
         FIG. 3  illustrates a second example of operational processes for deciding whether to generate a pessimistic or an accurate alias set, on a computing device within the environment of  FIG. 1 , in accordance with an exemplary embodiment of the present invention. 
         FIG. 4  depicts a block diagram of components of the computing device executing a heuristic program, in accordance with an exemplary embodiment of the present invention. 
     
    
    
     DETAILED DESCRIPTION 
     In computer programming, a procedure is a collection of executable statements that form a subroutine of a program. When a first procedure invokes or calls a second procedure, it is often the case that a variable is accessed that is not local to the first procedure. In other words, the first procedure has accessed a variable that was declared outside the scope of the first procedure. Examples of procedures that access variables outside of procedure scope include nested procedures (i.e., procedures declared within other procedures), methods in object-oriented (OO) languages, ‘C’ functions that can access file scope variables, etc. For reasons of simplicity, the term “nested procedure” will be used hereafter to refer to any procedure that has access to one or more variables declared outside the scope of the procedure. 
     In the context of an optimizing compiler, an alias set for a procedure is a set of variables within a program that can be referenced and/or modified by a call to the procedure. A call to a procedure “kills” the variables in the procedure alias set. In compiler terminology, a variable value is killed when the variable cannot be retained in registers across procedure call boundaries because it is assumed that the call to the procedure resulted in a modification of the values, i.e. the register data has become “stale.” When a variable value is not retained in the registers, the next time the variable is referenced it must be reloaded from the computer memory to get the latest value. Reloading variable values from the computer memory as opposed to reading the value directly from a register results in decreased runtime performance. The more variables within a program that are reloaded from memory as opposed to being read from the registers, the worse the runtime performance for the program. 
     Successful optimization of a program requires the computation of alias sets for all procedures within the program. The computation of alias sets is often referred to as “aliasing.” Aliasing nested procedures frequently results in the generation of “pessimistic” alias sets. A pessimistic alias set for a procedure includes many variables that are not actually affected by a call to that procedure. Thus, procedures that have pessimistic alias sets decrease runtime performance more than procedures that have accurately computed alias sets (i.e., alias sets that accurately reflect the set of variables that are truly affected by a call to the procedure). 
     Despite the negative runtime performance implications, computing pessimistic aliasing sets for nested procedures is often done because it is computationally simpler than computing accurate alias sets. In the case of programs containing nested procedures, computing accurate alias sets to improve runtime performance is not done because nested procedures often call many other nested procedures and external procedures. In addition, nested procedures often dereference many pointer variables. These characteristics lead to the expectation that computing accurate alias sets for nested procedures is not desirable because: 1) it will be expensive to do so; and 2) a very large alias set will be generated anyway, which will still lead to poor runtime performance. 
     Embodiments of the present invention recognize that generating a pessimistic alias set is preferable for nested procedures that are very likely to be aliased with many program variables. Embodiments of the present invention recognize that generating an accurate alias set is preferable for nested procedures that are very likely to be aliased with a small number of program variables. Embodiments of the present invention provide a method, system, and computer program product to predict whether nested procedures are likely to be aliased with many program variables. Embodiments of the present invention provide a method, system, and computer program product to predict whether nested procedures are good candidates for computationally demanding accurate aliasing or whether such procedures should undergo pessimistic aliasing. 
     The present invention will now be described in detail with reference to the Figures. 
       FIG. 1  is a functional block diagram illustrating a computing environment, generally designated  100 , in accordance with one embodiment of the present invention. Computing environment  100  includes computing device  102  connected over network  130 . Computing device  102  includes heuristic program  104 , program  106 , pessimistic aliasing program  108 , and accurate aliasing program  110 . 
     In various embodiments of the present invention, computing device  102  is a computing device that can be a standalone device, a server, a laptop computer, a tablet computer, a netbook computer, a personal computer (PC), or a desktop computer. In another embodiment, computing device  102  represents a computing system utilizing clustered computers and components to act as a single pool of seamless resources. In general, computing device  102  can be any computing device or a combination of devices with access to heuristic program  104 , program  106 , pessimistic aliasing program  108 , and accurate aliasing program  110  and is capable of executing these programs. Computing device  102  may include internal and external hardware components, as depicted and described in further detail with respect to  FIG. 4 . 
     In this exemplary embodiment, heuristic program  104 , program  106 , pessimistic aliasing program  108 , and accurate aliasing program  110  are stored on computing device  102 . However, in other embodiments, heuristic program  104 , program  106 , pessimistic aliasing program  108 , and accurate aliasing program  110  may be stored externally and accessed through a communication network, such as network  130 . Network  130  can be, for example, a local area network (LAN), a wide area network (WAN) such as the Internet, or a combination of the two, and may include wired, wireless, fiber optic or any other connection known in the art. In general, network  130  can be any combination of connections and protocols that will support communications between computing device  102 , heuristic program  104 , program  106 , pessimistic aliasing program  108 , and accurate aliasing program  110 , in accordance with a desired embodiment of the present invention. 
     In exemplary embodiments, heuristic program  104  analyzes nested procedures within program  106  that are able to access variables declared outside of the scope of the procedure. Heuristic program  104  determines the likelihood that variables within the procedures contained in program  106  are aliased with too many program variables to make the generation of an accurate alias set worthwhile. Heuristic program  104  determines whether aliasing the procedures within program  106  should be conducted with pessimistic aliasing program  108  or accurate aliasing program  110 . 
     In exemplary embodiments, program  106  is any program written in a computer language that allows procedures within program  106  to be able to access variables declared outside of the scope of the procedure. Examples of computer languages that allow such situations in the form of nested procedures include common business-oriented language (COBOL), Programming Language One (PL/I), and to some extent the C programming language (C) (i.e., the GNU Compiler Collection (GCC), which supports nested procedures as a language extension of C). 
     In addition to programs written in computer languages that allow truly nested procedures, program  106  represents programs that support language constructs that allow functions to access variables declared outside the function scope. Examples of such languages include object-oriented (OO) languages where class methods have access to class member variables. Other examples include languages like C where functions in a module have access to static variables declared in the module (called file scope variables). Program  106  also includes programs written in OO languages such as Java, which have small subroutines called methods that can access class member variables. 
     In exemplary embodiments, pessimistic aliasing program  108  assigns the same aliasing information to all procedures that can access variables declared outside of their scope. Pessimistic aliasing program  108  assumes that all variables in the program that are accessed in at least one such procedure are killed by a call to any such procedure. 
     If:
         P is a set of all procedures in a program;   V is a set of all variables declared in the program (this includes variables declared local to a procedure);   scope: P→N is a function that maps a procedure to a natural number indicating its nesting level. For a procedure p that is not nested within another procedure, scope(p)=1. If a procedure p is declared inside a procedure q where scope(q)=1, then scope(p)=2, and so on and so forth;   scope: V→N is a function that maps a variable in V to a natural number indicating the scope in which it is declared. For a variable v that is declared in the module outside the scope of any procedure (e.g., a file static variable in ‘C’), scope(v)=0. If v is declared in a procedure p, then scope(v)=scope(p);   UsedInNestedProcs={vεV|v is referenced and/or set in pεP and scope(v)&lt;scope(p).} These are variables that are referenced and/or set in a procedure but are declared in a containing scope;   External={vεV|v is an external variable and is accessible outside the current compilation unit.}; and   AddrTaken={vεV|v has had its address taken.}.
 
Then one way of defining a pessimistic alias set of variables (AliasNestedProcs) within procedures in a program is as follows:
 
AliasNestedProcs=UsedInNestedProcs∪External∪AddrTaken
       

     In exemplary embodiments, accurate aliasing program  110  defines alias sets specific to each procedure based on analysis of the specific variables and procedures that the procedure can access. In various embodiments, a call graph (G) is constructed for this analysis as follows:
 
 G =( V,E )
 
     Where:
         G is a directed graph with vertices V and edges E;   V=P (i.e., the set of procedures in the program serve as the vertices of the graph);   E=(p, q); where p, qεP and p directly calls q; and   UsedInNestedProc_{p}={vεV|v is referenced and/or set inside p E P (or q E P that is reachable from p in G) and scope(v)&lt;scope(p) (or scope(v)&lt;scope(q)).}.
 
The accurate alias sets for nested procedures p can now be defined as follows:
   Alias_{p}=UsedInNestedProc_{p}; (if neither p nor any other procedures reachable from p in G can make external calls); or   Alias_{p}=UsedInNestedProc_{p}∪External∪AddrTaken; (if p or some procedure reachable from p in G can make external calls).       

     It should be understood that: 1) the variables in the alias sets computed above are likely in practice to have aliases themselves, which may be calculated via any kind of aliasing method known in the literature (e.g., aliasing based on analyzing the flow of the program, static aliasing methods that may decide aliasing for individual variables based on type (such as ANSI aliasing in the ‘C’ language), etc.); and 2) in practice the alias sets for the nested procedures may contain various procedure symbols in order to make the alias sets reflexive and symmetric. 
     Typically, for a nested procedure it is more costly to compute an accurate alias set as shown above compared to a pessimistic alias set. An accurate alias set requires the creation of a call graph, computation of a reachability relationship, and aliasing is done at an individual procedure level. The computation of an accurate alias set also results in higher memory requirements during compilation of large or complex programs. This is due, at least in part, to the fact that there is no common alias set computed for all procedures that can access variables declared outside of their scope such as is seen with a pessimistic alias set. In addition, if a procedure in a non-large, non-complex program both calls an external function or performs many pointer dereference operations and is called by many other procedures in the program, then many procedures within the program will likely be aliased with many program variables and the cost of generating an accurate alias set will be prohibitive. 
     In some scenarios and embodiments, one benefit of an accurate alias set is that the aliasing can be more accurate for each procedure and, in some cases, can increase the opportunity for maintaining data in registers across procedure call boundaries. 
       FIG. 2  illustrates a first example of operational processes, generally designated  200 , for deciding whether to generate a pessimistic or an accurate alias set, on computing device  102  within the environment of  FIG. 1 , in accordance with an exemplary embodiment of the present invention. 
     In decision step  202 , heuristic program  104  determines, via the construction of a call graph substantially similar to the call graph described above, whether a procedure in program  106  exceeds a threshold number of calls away from a leaf procedure. A leaf procedure, as used herein, refers to a procedure that does not call any other procedures. In one embodiment, the threshold number of calls is a number of calls that an administrator or user sets. In another embodiment, there is a recommended threshold number of calls based on a statistical analysis of past results with other programs comparable to program  106 . In other embodiments, the threshold number of calls reflects the amount of computation that can be tolerated by a compiler. In various embodiments, a call graph is created by heuristic program  104  in order to determine how many calls away a procedure is from a leaf procedure. Thus, if the threshold number of calls away from a leaf procedure is determined to be two or greater, then a procedure, represented by a vertex or node in the call graph, cannot require two or more edges to reach any leaf procedure. 
     If heuristic program  104  determines that the procedure exceeds the threshold number of calls away from a leaf procedure, then heuristic program  104  dictates that a pessimistic alias set should be generated for that procedure (step  212 ) using pessimistic aliasing program  108 . If heuristic program  104  determines that the procedure does not exceed the threshold number of calls away from a leaf procedure, then heuristic program  104  proceeds to decision step  204 . 
     In decision step  204 , heuristic program  104  determines whether a procedure less than a threshold number of calls away from a leaf procedure makes one or more indirect calls to other procedures, or can reach other procedures that make indirect calls. As used herein, an indirect call refers to a call using a function pointer. A function pointer points to executable code within memory instead of referring to data values. When dereferenced, a function pointer can be used to invoke the function it points to and pass it arguments just like a typical function call. If a procedure makes an indirect call, then the target of the call is unknown and, hence, the outcome of generating an accurate alias set is also unknown. 
     If heuristic program  104  determines that the procedure makes one or more indirect calls to other procedures or calls one or more procedures that make indirect calls, then heuristic program  104  dictates that a pessimistic alias set should be generated for that procedure (step  212 ) using pessimistic aliasing program  108 . If heuristic program  104  determines that the procedure does not make one or more indirect calls to other procedures, then heuristic program  104  proceeds to decision step  206 . 
     In step  206 , heuristic program  104  determines whether a procedure, which has passed decision steps  202  and  204 , exceeds a threshold criterion for complexity. In various embodiments, a threshold criterion for complexity includes one or more of: 1) the procedure exceeds a threshold value for size (e.g., lines of code, etc.); 2) the procedure exceeds a threshold number of calls to other procedures; and 3) the procedure has difficult-to-analyze constructs (e.g., inline assembler code, etc.). 
     If heuristic program  104  determines that the procedure exceeds a threshold criterion for complexity, then heuristic program  104  dictates that a pessimistic alias set should be generated for that procedure (step  212 ) using pessimistic aliasing program  108 . If heuristic program  104  determines that the procedure does not exceed a threshold criterion for complexity, then heuristic program  104  proceeds to decision step  208 . 
     In step  208 , heuristic program  104  determines whether a procedure, which has passed decision steps  202 - 206 , calls an external procedure or can reach another procedure in the call graph that calls an external procedure. If a procedure (or another procedure that the procedure can reach) makes a call to an external procedure, then the target of the call is unknown and, hence, the outcome of generating an accurate alias set is also unknown. 
     If heuristic program  104  determines that the procedure makes a call to an external procedure or can reach another procedure in the call graph that calls an external procedure, then heuristic program  104  dictates that a pessimistic alias set should be generated for that procedure (step  212 ) using pessimistic aliasing program  108 . If heuristic program  104  determines that the procedure does not make a call to an external procedure or cannot reach another procedure in the call graph that calls an external procedure, then heuristic program  104  proceeds to decision step  210 . 
     In step  210 , heuristic program  104  determines whether a procedure, which has passed decision steps  202 - 208 , exceeds a threshold number for making too many pointer de-references or calls other procedures that exceed a threshold number for making too many pointer de-references. Procedures that make pointer de-references kill variables that have had their addresses taken. 
     If heuristic program  104  determines that the procedure exceeds a threshold number for making too many pointer de-references or calls other procedures that exceed a threshold number for making too many pointer de-references, then heuristic program  104  dictates that a pessimistic alias set should be generated for that procedure (step  212 ) using pessimistic aliasing program  108 . If heuristic program  104  determines that the procedure does not exceed a threshold number for making too many pointer de-references or call other procedures that exceed a threshold number for making too many pointer de-references, then heuristic program  104  proceeds to step  214 . 
     In the embodiment shown in  FIG. 2 , the procedures that pass the criteria for decision steps  202 - 214  (i.e., the answer=“N”) are determined to be worthwhile for the generation of an accurate alias set by accurate aliasing program  110  (step  214 ). 
     It should be understood that the processes detailed in  FIG. 2  are just one embodiment for heuristic program  104 . Many other embodiments are possible. For example, steps  202 - 210  are executed in any order that enables a satisfactory aliasing strategy for a program in various embodiments. In other embodiments, one or more steps in  FIG. 2  are skipped (i.e., not performed) by heuristic program  104  to still provide a satisfactory aliasing strategy for certain programs. In yet other embodiments, heuristic program  104  is set to allow one or more steps in  FIG. 2  to fail and still determine that the generation of an accurate alias set by accurate aliasing program  110  is worthwhile. 
       FIG. 3  illustrates a second example of operational processes, generally designated  300 , for deciding whether to generate a pessimistic or an accurate alias set, on computing device  102  within the environment of  FIG. 1 , in accordance with an exemplary embodiment of the present invention. 
       FIG. 3  depicts an exemplary embodiment in which a first pass analysis is done by heuristic program  104  in steps  302 ,  206 ,  304 , and  306  using substantially similar criteria as described in steps  204 - 210  ( FIG. 2 ). Any procedures within program  106  that are determined to require pessimistic aliasing by heuristic program  104  are flagged in the first pass analysis. In this embodiment, a second pass analysis is then initiated by heuristic program  104  whereby any procedures not flagged in the first pass analysis are analyzed via a call graph using an analysis substantially similar to the step  202  analysis in  FIG. 2 . In this exemplary embodiment, a procedure is flagged by heuristic program  104  as requiring pessimistic aliasing in the second pass analysis if: 1) the procedure fails the threshold criterion described in step  202 ; or 2) the procedure encounters a node representing another procedure, which has been flagged as requiring pessimistic aliasing in steps  302 ,  206 ,  304 , and  306 . 
     Using the embodiment depicted in  FIG. 3  results in less computation for steps  302 ,  304 ,  306 , and  308  as compared respectively to steps  204 ,  208 ,  210 , and  202  in  FIG. 2 . For example, heuristic program  104  determines in step  302  whether a procedure makes one or more indirect calls to other procedures, but it does not require the determination of whether that procedure can reach other procedures that make indirect calls like in step  204  in  FIG. 2 . This is because unlike step  202  in  FIG. 2 , step  308  in  FIG. 3  has the additional criterion whereby it determines a procedure should undergo pessimistic aliasing if it encounters a node representing another procedure, which has been flagged as requiring pessimistic aliasing in steps  302 ,  206 ,  304 , and  306  in  FIG. 3 . Step  202  in the embodiment shown in  FIG. 2  cannot encounter procedures flagged by the other steps because those steps have not been allowed to flag procedures before step  202  is executed. 
     Likewise and for the same reason, heuristic program  104  determines in step  304  whether a procedure calls an external procedure, but it does not require the determination of whether that procedure can reach other procedures that can call an external procedure like in step  208  in  FIG. 2 . 
     Also likewise and again for the same reason, heuristic program  104  determines in step  306  whether a procedure exceeds a threshold number for making too many pointer de-references, but it does not require the determination of whether that procedure can reach other procedures that exceed a threshold number for making too many pointer de-references like in step  210  in  FIG. 2 . 
     It should be understood that the use of a call graph in steps  202  and  308  does not require the computation of a reachability relationship in the graph. Instead, a shallow search of the call graph starting at the vertex represented by the procedure in question is sufficient for most cases. Thus, a shallow search includes searching from the vertex in question until either the threshold condition is violated or all possible vertices within the distance of the threshold have been searched. 
       FIG. 3  depicts a block diagram,  400 , of components of computing device  102 , in accordance with an illustrative embodiment of the present invention. It should be appreciated that  FIG. 4  provides only an illustration of one implementation and does not imply any limitations with regard to the environments in which different embodiments may be implemented. Many modifications to the depicted environment may be made. 
     Computing device  102  includes communications fabric  402 , which provides communications between computer processor(s)  404 , memory  406 , persistent storage  408 , communications unit  410 , and input/output (I/O) interface(s)  412 . Communications fabric  402  can be implemented with any architecture designed for passing data and/or control information between processors (such as microprocessors, communications and network processors, etc.), system memory, peripheral devices, and any other hardware components within a system. For example, communications fabric  402  can be implemented with one or more buses. 
     Memory  406  and persistent storage  408  are computer-readable storage media. In this embodiment, memory  406  includes random access memory (RAM)  414  and cache memory  416 . In general, memory  406  can include any suitable volatile or non-volatile computer-readable storage media. 
     Heuristic program  104 , program  106 , pessimistic aliasing program  108 , and accurate aliasing program  110  are stored in persistent storage  408  for execution and/or access by one or more of the respective computer processors  404  via one or more memories of memory  406 . In this embodiment, persistent storage  408  includes a magnetic hard disk drive. Alternatively, or in addition to a magnetic hard disk drive, persistent storage  408  can include a solid state hard drive, a semiconductor storage device, read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, or any other computer-readable storage media that is capable of storing program instructions or digital information. 
     The media used by persistent storage  408  may also be removable. For example, a removable hard drive may be used for persistent storage  408 . Other examples include optical and magnetic disks, thumb drives, and smart cards that are inserted into a drive for transfer onto another computer-readable storage medium that is also part of persistent storage  408 . 
     Communications unit  410 , in these examples, provides for communications with other data processing systems or devices, including resources of network  130 . In these examples, communications unit  410  includes one or more network interface cards. Communications unit  410  may provide communications through the use of either or both physical and wireless communications links. Heuristic program  104 , program  106 , pessimistic aliasing program  108 , and accurate aliasing program  110  may be downloaded to persistent storage  408  through communications unit  410 . 
     I/O interface(s)  412  allows for input and output of data with other devices that may be connected to computing device  102 . For example, I/O interface  412  may provide a connection to external devices  418  such as a keyboard, keypad, a touch screen, and/or some other suitable input device. External devices  418  can also include portable computer-readable storage media such as, for example, thumb drives, portable optical or magnetic disks, and memory cards. Software and data used to practice embodiments of the present invention, e.g., heuristic program  104 , program  106 , pessimistic aliasing program  108 , and accurate aliasing program  110 , can be stored on such portable computer-readable storage media and can be loaded onto persistent storage  408  via I/O interface(s)  412 . I/O interface(s)  412  also connect to a display  420 . 
     Display  420  provides a mechanism to display data to a user and may be, for example, a computer monitor, or a television screen. 
     The present invention may be a system, a method, and/or a computer program product. The computer program product may include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present invention. 
     The computer readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. The computer readable storage medium may be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of the computer readable storage medium includes the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device such as punch-cards or raised structures in a groove having instructions recorded thereon, and any suitable combination of the foregoing. A computer readable storage medium, as used herein, is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire. 
     Computer readable program instructions described herein can be downloaded to respective computing/processing devices from a computer readable storage medium or to an external computer or external storage device via a network, for example, the Internet, a local area network, a wide area network and/or a wireless network. The network may comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. A network adapter card or network interface in each computing/processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium within the respective computing/processing device. 
     Computer readable program instructions for carrying out operations of the present invention may be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, or either source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C++ or the like, and conventional procedural programming languages, such as the “C” programming language or similar programming languages. The computer readable program instructions may execute entirely on the user&#39;s computer, partly on the user&#39;s computer, as a stand-alone software package, partly on the user&#39;s computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user&#39;s computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGA), or programmable logic arrays (PLA) may execute the computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects of the present invention. 
     Aspects of the present invention are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer readable program instructions. 
     These computer readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer readable program instructions may also be stored in a computer readable storage medium that can direct a computer, a programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer readable storage medium having instructions stored therein comprises an article of manufacture including instructions which implement aspects of the function/act specified in the flowchart and/or block diagram block or blocks. 
     The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process, such that the instructions which execute on the computer, other programmable apparatus, or other device implement the functions/acts specified in the flowchart and/or block diagram block or blocks. 
     The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts or carry out combinations of special purpose hardware and computer instructions. 
     The programs described herein are identified based upon the application for which they are implemented in a specific embodiment of the invention. However, it should be appreciated that any particular program nomenclature herein is used merely for convenience, and thus the invention should not be limited to use solely in any specific application identified and/or implied by such nomenclature. 
     It is to be noted that the term(s) such as “Smalltalk,” “Java,” and the like may be subject to trademark rights in various jurisdictions throughout the world and are used here only in reference to the products or services properly denominated by the marks to the extent that such trademark rights may exist.