Patent Publication Number: US-9892207-B2

Title: Automatic migration for on-premise data objects to on-demand data objects

Description:
BACKGROUND 
     Cloud computing is an emerging technology that has the potential to be used widely for business applications. Cloud computing can offer enterprises the opportunity to significantly reduce the total cost of ownership (TCO) of business applications by using various cloud services. Thus, there is a demand to migrate these business applications to cloud based services/applications in order to reduce related costs (e.g. IT-staff, maintenance, hardware, etc.). 
     SUMMARY 
     Implementations of the present disclosure include computer-implemented methods for automatically migrating on-premise data objects used by an on-premise application to on-demand data objects used by an on-demand application. In some implementations, actions include retrieving mapping rules corresponding to the on-premise data objects, the mapping rules being retrieved from a rule repository; extracting, by one or more processors, data corresponding to on-premise data objects that are affected during execution of the on-premise application, the on-premise application being executed within an on-premise computing environment, the data being stored in an on-premise database based on an on-premise database schema; generating, by the one or more processors, an export file, the export file including the data; generating, by the one or more processors, an import file based on the export file and the mapping rules, the import file including the data; and providing the import file to an on-demand computing environment that hosts the on-demand application, the import file being process-able by the on-demand computing environment to write the data from the import file into an on-demand database. 
     In some implementations, the mapping rules map fields of on-premise data objects to fields of on-demand data objects. 
     In some implementations, generating the import file includes parsing the data provided in the export file, and mapping the data based on the mapping rules. 
     In some implementations, actions further include Identifying, by the one or more processors, on-premise data object models corresponding to the on-premise data objects, defining the mapping rules to map fields of the on-premise data object models to fields of corresponding on-demand data object models, and storing the mapping rules in the rule repository. 
     In some implementations, extracting data is achieved based on a schema mapping that maps fields of the on-premise database to fields of the on-premise objects based on the on-premise database schema. 
     In some implementations, the data is written to the on-premise database based on a schema mapping that maps fields of the on-demand data objects to fields of the on-demand database based on an on-demand database schema. 
     In some implementations, the on-premise application embodies a business process of an enterprise, the business process including one or more tasks, at least one task affecting an on-premise data object. 
     In some implementations, the on-premise computing environment is operated and maintained by an enterprise. 
     In some implementations, the on-demand computing environment is operated and maintained by a service provider. 
     In some implementations, an on-premise data object is affected during execution of the on-premise application when data is one or more of stored to and read from the on-premise data object. 
     It is appreciated that methods in accordance with the present disclosure can include any combination of the aspects and features described herein. That is, methods in accordance with the present disclosure are not limited to the combinations of aspects and features specifically described herein, but also include any combination of the aspects and features provided. 
     The present disclosure also provides a computer-readable storage medium coupled to one or more processors and having instructions stored thereon which, when executed by the one or more processors, cause the one or more processors to perform operations in accordance with implementations of the methods provided herein. 
     The present disclosure further provides a system for implementing the methods provided herein. The system includes one or more processors, and a computer-readable storage medium coupled to the one or more processors having instructions stored thereon which, when executed by the one or more processors, cause the one or more processors to perform operations in accordance with implementations of the methods provided herein. 
     The details of one or more implementations of the present disclosure are set forth in the accompanying drawings and the description below. Other features and advantages of the present disclosure will be apparent from the 
    
    
     
       DESCRIPTION OF DRAWINGS 
         FIG. 1  depicts an example system in accordance with implementations of the present disclosure. 
         FIG. 2  depicts a generic business process. 
         FIG. 3  illustrates a mapping between an on-premise business object and a corresponding on-demand business object. 
         FIG. 4  illustrates a process in accordance with implementations of the present disclosure. 
         FIG. 5  is a schematic illustration of example computer systems that can be used to execute implementations of the present disclosure. 
     
    
    
     Like reference symbols in the various drawings indicate like elements. 
     DETAILED DESCRIPTION 
     Implementations of the present disclosure are generally directed to migration of on-premise data objects to on-demand data objects. In some implementations, an on-premise application (e.g., locally-accessible) accesses data stored by an on-premise database (e.g., “legacy” data). In some examples, an on-premise application is a computer-executable application that is locally executed by an enterprise. For example, the on-premise application can be provided as one or more computer-executable programs that are executed using computing devices that are operated by the enterprise (e.g., a company). In some examples, an on-demand application is a computer-executable application that is provided by a service provider and that is remotely accessed by one or more enterprises. For example, the on-demand application can be provided as one or more computer-executable programs that are executed using computing devices that are operated by the service provider (e.g., a cloud service provider), the on-demand application being accessed by one or more enterprises (e.g., over a network). 
     In some examples, an enterprise seeks to switch from an on-premise application to an on-demand application. In this manner, the enterprise is able to reduce costs, as the enterprise no longer has the burden of operating and maintaining the on-premise application. Instead, the service provider operates and maintains the on-demand application. In some instances, for example, data structures of the on-demand application are different from data structures of the on-premise application, resulting in a risk of previously stored on-premise data being unusable with the on-demand application. 
     Accordingly, implementations of the present disclosure enable migration of on-premise data (e.g., stored by an on-premise database of the enterprise) to on-demand data (e.g., stored by an on-demand database provided by the service provider). In this manner, legacy data used by the enterprise is not lost when moving from the on-premise application to the on-demand application. For example, on-premise business objects (e.g., implemented by a business process of the on-premise application) can access data stored by the on-premise database using a first mapping. In some examples, the on-premise business objects are extracted, including extraction of the data accessed by the on-premise business objects. The on-premise business objects are mapped to on-demand business objects, including a second mapping between attributes (based on the data) of the on-premise business objects and the on-demand business objects. Additionally, the attributes of the on-demand business objects are mapped to an on-demand database using a third mapping. An on-demand application (e.g., cloud-based application) can access the data stored in the on-demand database. 
     Implementations of the present disclosure will be described in further detail herein with reference to an example context. The example context includes migration from an on-premise business application to an on-demand business application. In the example context, data objects, provided as business objects, that are used by an on-premise business application are identified and are migrated for use with an on-demand business application. However, implementations of the present disclosure are applicable in other contexts, such as non-business applications that use non-business data objects. 
       FIG. 1  illustrates a computing system  100  that includes an on-premise computing environment  102  and an on-demand computing environment  104 . In some implementations, the on-premise computing environment  102  is local to an enterprise. For example, the on-premise computing environment  102  may (physically) reside or be under the control of the enterprise (e.g., a company) that owns and operates the on-premise computing environment  102 . The on-demand environment  104  can include a BO importer  116 , an on-demand database  118 , and an on-demand application  120 . 
     In some examples, the on-demand computing environment  104  is a distributed (“cloud”) computing environment that is operated by a service provider. In some examples, the on-demand computing environment  104  is remote from the on-premise computing environment  102  operated by the enterprise. In some examples, the on-demand computing environment  104  can be (physically) inaccessible to by a user of the on-premise computing environment  102 . In some examples, the on-demand computing environment  104  can be geographically remote from the on-premise computing environment  102 . 
     In some examples, the on-premise computing environment  102  can include an on-premise application  106 , an on-premise database  108 , a business object (BO) extractor  110 , a mapping engine  112 , and a rules database  114 . In some examples, the on-demand computing environment  104  can include the mapping engine  112  and the rules database  114 . In some examples, the mapping engine  112  and the rules database  114  can be distributed between the on-premise computing environment  102  and the on-demand computing environment  104 . 
     In some examples, the on-premise application  106  is any appropriate type of application that processes data retrieved from the database  108  and/or that stores data to the database  108 . Although depicted as a single application, the on-premise application  106  may be implemented as one or more applications that are executed in the on-premise computing environment  102 . 
     In some implementations, a business process is embodied in the on-premise business application  106 . One or more business objects (BOs) can be associated with the business process. In some examples, BOs can be manipulated during execution of the business process. In the example context, the on-premise application  106  can include a service-based business process such as a sales order business process, for example. The example sales order business process can include an order sub-process, a billing sub-process and a shipping sub-process. In the example context, a sales order object (e.g., sales order BO) can be provided and can be linked to multiple sales item objects (e.g., sales item BOs). Actions can be provided and can be controlled by business constraints. In some examples, each action can move the sales order BO through the order sub-process, the billing sub-process and the shipping sub-process. 
     In some examples, each BO can be provided based on an object model that describes static features or components associated with the BO and/or dependencies between the BO and other BOs. In some examples, a BO can include attributes or variables. In some examples, attributes are initialized at the time of instantiation of the BO and can assume different values during the business process that acts on the BO. In the example context, the sales order BO in the sales order business process can include attributes such as Order ID, number of order items, and delivery date. 
     In some examples, the on-premise database  108  stores attribute data associated with the business process, and particularly, the business objects. The business objects include one or more fields. The one or more fields are populated (e.g., at runtime) with corresponding attribute data from the on-premise database  108 . For example, the on-premise application  106  accesses the on-premise database  108  in response to execution of the business process, and particularly, such that the BOs associated with business process are populated with associated attribute data. In some examples, the on-premise database  108  stores the attribute data of the on-premise BO according to a first schema. In some examples, the on-premise database  108  is an in-memory repository. 
     In accordance with implementations of the present disclosure, the on-premise computing environment  102  can support migration from the on-premise application  106  to the on-demand application  120  of the on-demand computing environment  104 . For example, the enterprise that operates and maintains the on-premise application  106  can decide that instead of using the on-premise application  106  to support operations of the enterprise (e.g., sales order processing), the enterprise will use the on-demand application  120  provided by the provider of the on-demand computing environment  104 . To that end, the enterprise migrates the on-premise data stored in the database  108  for storage in the on-demand database  118  and use with the on-demand application  120 . In accordance with implementations of the present disclosure, the on-premise computing environment can include the BO extractor  110 , the mapping engine  112  and the rules database  114 . Although the BO extractor  110 , the mapping engine  112  and the rules repository  114  are depicted as part of the on-premise computing environment  102 , it is appreciated that the BO extractor  110 , the mapping engine  112  and the rules repository  114  can be provided as part of the on-demand computing environment  104  or can be provided by a third-party service provider. 
     In some implementations, the BO extractor  110  extracts the BOs associated with the business process, and the attribute data of the BOs associated with the business process. For example, the business process can be examined and the BOs that are affected by the business process can be identified. In some examples, the BO extractor  110  extracts the BOs and generates an extensible markup language (XML) file based on the extracted BOs. In some examples, the BO extractor  110  generates the XML file to include the attribute data associated with the BOs associated with the business process. 
     In some implementations, the mapping engine  112  maps the extracted, on-premise BOs to on-demand BOs. In some examples, the mapping engine  112  accesses the rules database  114  to obtain one or more rules regarding mapping of the on-premise BO fields to the on-demand BO fields. For example, the mapping engine  112  processes (e.g., analyzes) the XML file and identifies one or more rules (e.g., a rule set) associated with the XML file from the rules database  114 . The mapping engine  112  applies the one or more associated rules to the on-premise BO (e.g., the XML file) to map the on-premise BO to a corresponding on-demand BO. In some examples, the mapping engine  112  applies the one or more associated rules to the on-premise BO such that one or more fields of the on-premise BO are mapped to one or more fields of the on-demand BO. Thus, the attributes associated with the fields of the on-premise BO are mapped to the corresponding fields of the on-demand BO. In some examples, the mapping engine  112  serializes the mapped data into an import file (e.g., an XML file). 
     In some examples, one field of the on-premise BO may be mapped to two or more fields of the on-demand BO. In some examples, two or more fields of the on-premise BO may be mapped to one field of the on-demand BO. In some examples, the one or more rules associated with the on-premise BO are based on the on-premise BO. For example, the one or more rules are specific for the particular on-premise BO. In some examples, the one or more rules are based on the on-demand environment  104 . For example, the one or more rules are specific for the on-demand environment  104  (and an on-demand application). 
     In some implementations, first mapping rules are defined to map on-premise BOs to the corresponding on-premise database schema. In some examples, the first mapping rules are pre-defined. For example, the first mapping rules can be provided as part of the on-premise application  106  to enable retrieval of data from the database  108  during execution of the on-premise application  106 . In some implementations, second mapping rules are defined to map fields of on-premise BOs to corresponding fields on on-demand BOs. For example, the second mapping can be provided as part of a migration process for moving from the on-premise application  106  to the on-demand application  120 . In some implementations, third mapping rules are defined to map on-demand BOs to the corresponding on-demand database schema. In some examples, the third mapping rules are pre-defined. For example, the third mapping rules can be provided as part of the on-demand application  120  to enable retrieval of data from the database  118  during execution of the on-demand application  120 . Each of the first, second and third mapping rules can be persisted in the rules repository  114 . 
     In some implementations, the BO importer  116  imports the on-premise BOs to provide corresponding on-demand BOs that can be affected by the on-demand application  120 . For example, the BO importer  116  receives the import file form the mapping engine  112  and generates corresponding on-demand BOs based on the data provided in the import file. For example, the BO importer  116  parses the import file and maps the BOs according to third mapping rules (e.g., mapping on-demand BOs to the on-demand database schema of the database  118 ) and writes the data into the on-demand database. 
     The on-demand database  118  stores the attribute data associated with the on-demand BO. In some examples, the BO importer  116  maps the data of the on-demand BO to the on-demand database  118  according to a second schema. In some examples, the second schema differs from the first schema of the on-premise database  108 . For example, the BO importer  116  maps the fields of the on-demand BO to the on-demand database  118  such that the attributes associated with the fields is stored by the on-demand database  118  according to the second schema. In some examples, the on-premise database  118  is an in-memory repository. 
     In some examples, the on-demand application  120  is an application hosted on the on-demand environment  104 . The on-demand application  120  accesses the on-demand database  118  in response to execution of an on-demand business process, to populate the BOs associated with on-demand business process with associated attribute data of the on-demand database  118 . In some examples, the on-demand business process supplants the on-premise business process. In some examples, the on-demand business process differs from the on-premise business process. In some examples, the on-demand business process and the on-premise business process provide a similar (or same) result (e.g., sales order processing). The on-demand application  120  is interacts with the on-demand BO, similar to that mentioned above with respect to the on-premise application  106  interacting with the on-premise BO. 
       FIG. 2  illustrates a generic business process  200  that can be embodied by the on-premise business process  106  and/or the on-demand business process  120 . The generic business process  200  is associated with (e.g., includes) one or more tasks (e.g., Task 1, Task 2, . . . , Task n) and accesses one or more business objects (e.g., BO 1 , BO 2 , . . . , BO i ) during execution of the tasks. For example, each task may access one or more business objects, and the attributes (data) associated with the one or more business objects (e.g., from the on-premise database and/or the on-demand database). 
     In some examples, a task (e.g., Task 1, Task 2, . . . , Task n) is associated with two or more business objects (e.g., BO 1 , BO 2 , . . . , BO i ). In some examples, a business object (e.g., BO 1 , BO 2 , . . . , BO i ) is associated with two or more tasks (e.g., Task 1, Task 2, . . . , Task n). 
       FIG. 3  illustrates a mapping between an on-premise business object (BO OP,q )  302  and a corresponding on-demand business object (BO OD,r )  304 . For example, the on-premise business object (BO OP,q )  302  and the on-demand business object (BO OD,r )  304  are one of BO 1 , BO 2 , . . . , BO i  of  FIG. 2 . 
     In some examples, the mapping between the on-premise business object (BO OP,q )  302  and the corresponding on-demand business object (BO OD,r )  304  includes at least three separate mappings. 
     In some examples, a first mapping can include a mapping between an on-premise database  306  (e.g., the on-premise database  108 ) to the on-premise business object (BO OP,q )  302 , and particularly, a mapping between the data of the on-premise database  306  to the fields of the on-premise business object (BO OP,q )  302 , according to a first schema associated with the on-premise database  306 . For example, the on-premise database  306  includes a data table  308  associated with the first schema. As illustrated, the table  308  includes data fields A 1 , A 2 , A 3 , B 1 , B 2 , B 3 , C 1 , C 2 , and C 3 . Each of the data fields can be associated with one more contents of data (e.g., attributes). The on-premise business object (BO OP,q )  302  includes fields  316 ,  318 ,  320 . The first mapping includes a mapping of the data of data field A 1  to the field  316  of the on-premise business object (BO OP,q )  302  such that an attribute 1  populates the field  316  (e.g., the attribute 1  is based on the data of data field A 1 ); a mapping of the data field A 2  to the field  318  of the on-premise business object (BO OP,q )  302  such that an attribute 2  populates the field  318  (e.g., the attribute 2  is based on the data of the data field A 2 ); and a mapping of the data field A 3  to the field  320  of the on-premise business object (BO OP,q )  302  such that an attribute 3  populates the field  320  (e.g., the attribute 3  is based on the data of the data field A 3 ). 
     In some examples, the second mapping can include a mapping between the on-premise business object (BO OP,q )  302  and the on-demand business object (BO OD,r )  304 , and particularly, a mapping between the fields of the on-premise business object (BO OP,q ) and fields of the on-demand business object (BO OD,r ), according to one or more mapping rules. 
     For example, the on-demand business object (BO OD,r )  304  includes fields  322 ,  324 ,  326 . The second mapping includes a mapping of the field  316  of the on-premise business object (BO OP,q ) to the field  324  of the on-demand business object (BO OD,r )  304  such that an attribute y  populates the field  324  (e.g., the attribute y  is based on the attribute 1 ); a mapping of the field  318  of the on-premise business object (BO OP,q )  302  to the field  326  of the on-demand business object (BO OD,r )  304  such that an attribute z  populates the field  326  (e.g., the attribute z  is based on the attribute 2 ); and a mapping of the field  320  of the on-premise business object (BO OP,q )  302  to the field  322  of the on-demand business object (BO OD,r )  304  such that an attribute x  populates the field  322  (e.g., the attribute x  is based on the attribute 3 ). In some examples, the attribute of the on-demand business object (BO OD,r )  304  is substantially the same (or similar) to the attribute of the on-premise business object (BO OP,q )  302  that it is associated with (e.g., attribute x  is substantially the same as attribute 3 ; attribute y  is substantially the same as attribute 1 ; attribute z  is substantially the same as attribute 2 ). 
     In some examples, the third mapping can include a mapping between the on-demand business object (BO OD,r )  304  and an on-demand database  328  (e.g., the on-demand database  120 ), and particularly, a mapping between the fields of the on-demand business object (BO OD,r )  304  and the attributes of the on-demand database  328 , according a second schema associated with the on-demand database  328 . In some examples, the second schema differs from the first schema of the on-premise database  306 . 
     For example, the on-demand database  328  includes a data table  330  associated with the second schema. The table  330  includes data fields E 1 , E 2 , E 3 , F 1 , F 2 , F 3 , G 1 , G 2 , and G 3 . Each of the data fields can be associated with one more contents of data (e.g., attributes). The third mapping includes a mapping of the field  322  of the on-demand business object (BO OD,r )  304  to the data field E 1  such that attribute x  is stored at data field E 1  (e.g., the data of the data field E 1  is based on the attribute x ); a mapping of the field  324  of the on-demand business object (BO OD,r )  304  to the data field F 2  such that attribute y  is stored at data field F 2  (e.g., the data of the data field F 2  is based on the attribute y ); and a mapping of the field  326  of the on-demand business object (BO OD,r )  304  to the data field G 3  such that attribute is stored at data field G 3  (e.g., the data of the data field G 3  is based on the attribute z ); 
       FIG. 4  depicts an example process  400  for the migration of on-premise data objects to on-demand data objects. The example process  400  can be executed as one or more computer-executable programs executed using one or more computing devices. For example, the system  100  can execute the example process  400 . 
     The on-premise application is identified ( 402 ). In some examples, the on-premise application includes an application that is to be supplanted by an on-demand application. For example, the on-premise application  106  of the on-premise environment  102  is identified. The identified on-premise application can embody a business process (e.g., the business process  200 ). 
     Affected BO(s) are identified ( 404 ). For example, on-premise BO(s) that are affected during execution of the on-premise application, and particularly, the business process underlying the on-premise application, are identified. For example, the on-premise business object (BO OP,q )  302  that is associated with the on-premise application  106  can be identified. 
     Migration rules are generated ( 406 ). In some examples, the rules associated with migrating the identified on-premise BOs and the data associated therewith from the on-premise environment  102  to the on-demand environment are generated  104 . For example, the rules can include rules relating to mappings between the on-premise database schema and the on-premise BO(s) (e.g., the on-premise business object (BO OP,q )  302 ) according to the first schema, between the on-premise BO(s) (e.g., the on-premise business object (BO OP,q )  302 ) and the on-demand BO(s) (e.g., the on-demand business object (BO OD,r )  304 ), and between the on-demand BO(s) (e.g., the on-demand business object (BO OD,r )  304 ) and the on-demand database schema according to the second schema. 
     The on-premise BO(s) are extracted ( 408 ). Specifically, the on-premise BO(s) that are identified (e.g., at  404 ) are extracted, and particularly, the attribute data associated with the on-premise BO(s) is extracted. For example, the BO extractor  110  extracts the identified BO(s) (e.g., the on-premise business object (BO OP,q )  302 ) and attribute data (e.g., attribute 1 , attribute 2 , attribute 3 ) from the on-premise database  306 . 
     In some implementations, the extraction of the on-premise BO(s) can be time-based. For example, a scheduling functionality may be applied to the extraction of the on-premise BO(s) such that the extraction occurs during specific time frames. Thus, during the extraction, the data of the on-premise database  306  associated with on-premise BO is “locked” (e.g., unaccessible or uneditable) to avoid inconsistencies of the data of the on-premise database  306 . In some examples, the extraction can be split among one or more time frames. 
     The on-premise BO(s) are mapped to the on-demand BO(s) ( 410 ). Specifically, the fields of the extracted, on-premise BO(s) (e.g., at step  408 ) are mapped to the on-demand BO(s) by applying one or more of the generated migration rules (e.g., at step  406 ). Mapping of the fields between the on-premise BO(s) and the on-demand BO(s) (e.g., between fields  316 ,  318 ,  320  of the on-premise business object (BO OP,q )  302  and the fields  322 ,  324 ,  326  of the on-demand business object (BO OD,r )  304 ) includes mapping attributes associated with the fields of the on-premise BO(s) to the corresponding fields of the on-demand BO(s). 
     The on-demand BO(s) are imported ( 412 ). Specifically, the on-demand BO(s) is imported within the on-demand environment. For example, the BO importer  116  imports the on-demand BO(s) (e.g., the on-demand business object (BO OD,r )  304 ) after mapping the on-premise BO(s) to the on-demand BO(s). 
     In some implementations, the importation of the on-demand BO(s) can be time-based. For example, a scheduling functionality may be applied to the importation of the on-premise BO(s) such that the importation occurs during specific time frames. Thus, during the importation, the data of the on-demand database is “locked” (e.g., unaccessible or uneditable) to avoid inconsistencies of the data of the on-demand database. In some examples, the importation can be split among one or more time frames. 
     The data associated with the on-demand BO(s) is mapped to the on-demand database ( 414 ). Specifically, the data (e.g., attributes) of the on-demand BO(s) is mapped to the on-demand database according to the second schema. For example, the BO importer  116  maps the fields of the on-demand BO (e.g., fields  322 ,  324 ,  326  of the on-demand business object (BO OD,r )  304 ) to the on-demand database  328  such that the attributes associated with the fields are stored by the on-demand database  328  according to the second schema. 
     Referring now to  FIG. 5 , a schematic diagram of an example computing system  500  is provided. The system  500  can be used for the operations described in association with the implementations described herein. For example, the system  500  may be included in any or all of the server components discussed herein. The system  500  includes a processor  510 , a memory  520 , a storage device  530 , and an input/output device  540 . Each of the components  510 ,  520 ,  530 , and  540  are interconnected using a system bus  550 . The processor  510  is capable of processing instructions for execution within the system  500 . In one implementation, the processor  510  is a single-threaded processor. In another implementation, the processor  510  is a multi-threaded processor. The processor  510  is capable of processing instructions stored in the memory  520  or on the storage device  530  to display graphical information for a user interface on the input/output device  540 . 
     The memory  520  stores information within the system  500 . In one implementation, the memory  520  is a computer-readable medium. In one implementation, the memory  520  is a volatile memory unit. In another implementation, the memory  520  is a non-volatile memory unit. The storage device  530  is capable of providing mass storage for the system  500 . In one implementation, the storage device  530  is a computer-readable medium. In various different implementations, the storage device  530  may be a floppy disk device, a hard disk device, an optical disk device, or a tape device. The input/output device  540  provides input/output operations for the system  500 . In one implementation, the input/output device  540  includes a keyboard and/or pointing device. In another implementation, the input/output device  540  includes a display unit for displaying graphical user interfaces. 
     The features described can be implemented in digital electronic circuitry, or in computer hardware, firmware, software, or in combinations of them. The apparatus can be implemented in a computer program product tangibly embodied in an information carrier, e.g., in a machine-readable storage device, for execution by a programmable processor; and method steps can be performed by a programmable processor executing a program of instructions to perform functions of the described implementations by operating on input data and generating output. The described features can be implemented advantageously in one or more computer programs that are executable on a programmable system including at least one programmable processor coupled to receive data and instructions from, and to transmit data and instructions to, a data storage system, at least one input device, and at least one output device. A computer program is a set of instructions that can be used, directly or indirectly, in a computer to perform a certain activity or bring about a certain result. A computer program can be written in any form of programming language, including compiled or interpreted languages, and it can be deployed in any form, including as a stand-alone program or as a module, component, subroutine, or other unit suitable for use in a computing environment. 
     Suitable processors for the execution of a program of instructions include, by way of example, both general and special purpose microprocessors, and the sole processor or one of multiple processors of any kind of computer. Generally, a processor will receive instructions and data from a read-only memory or a random access memory or both. Elements of a computer are a processor can include executing instructions and one or more memories for storing instructions and data. Generally, a computer will also include, or be operatively coupled to communicate with, one or more mass storage devices for storing data files; such devices include magnetic disks, such as internal hard disks and removable disks; magneto-optical disks; and optical disks. Storage devices suitable for tangibly embodying computer program instructions and data include all forms of non-volatile memory, including by way of example semiconductor memory devices, such as EPROM, EEPROM, and flash memory devices; magnetic disks such as internal hard disks and removable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks. The processor and the memory can be supplemented by, or incorporated in, ASICs (application-specific integrated circuits). 
     To provide for interaction with a user, the features can be implemented on a computer having a display device such as a CRT (cathode ray tube) or LCD (liquid crystal display) monitor for displaying information to the user and a keyboard and a pointing device such as a mouse or a trackball by which the user can provide input to the computer. 
     The features can be implemented in a computer system that includes a back-end component, such as a data server, or that includes a middleware component, such as an application server or an Internet server, or that includes a front-end component, such as a client computer having a graphical user interface or an Internet browser, or any combination of them. The components of the system can be connected by any form or medium of digital data communication such as a communication network. Examples of communication networks include, e.g., a LAN, a WAN, and the computers and networks forming the Internet. 
     The computer system can include clients and servers. A client and server are generally remote from each other and typically interact through a network, such as the described one. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. 
     In addition, the logic flows depicted in the figures do not require the particular order shown, or sequential order, to achieve desirable results. In addition, other steps may be provided, or steps may be eliminated, from the described flows, and other components may be added to, or removed from, the described systems. Accordingly, other implementations are within the scope of the following claims. 
     A number of implementations of the present disclosure have been described. Nevertheless, it will be understood that various modifications may be made without departing from the spirit and scope of the present disclosure. Accordingly, other implementations are within the scope of the following claims.