Patent Publication Number: US-9852153-B2

Title: Graphically representing programming attributes

Description:
CLAIM OF PRIORITY 
     This application claims priority under 35 USC §119(e) to U.S. Patent Application Ser. No. 61/707,343, filed on Sep. 28, 2012, the entire contents of which are hereby incorporated by reference. 
    
    
     BACKGROUND 
     This description relates to a graph based approach to representing programming attributes. 
     Complex computations can often be expressed as a data flow through a directed graph (called a “dataflow graph”), with components of the computation being associated with the vertices of the graph and data flows between the components corresponding to links (arcs, edges) of the graph. The components can include data processing components that receive data at one or more input ports, process the data, and provide data from one or more output ports, and dataset components that act as a source or sink of the data flows. A system that implements such graph-based computations is described in U.S. Pat. No. 5,966,072, EXECUTING COMPUTATIONS EXPRESSED AS GRAPHS. Various types of data may be received, processed and output by the components of the graph. Due to similar processing functionality, equivalent types of data may be used and re-used for different applications. 
     SUMMARY 
     In one aspect, a method for representing information includes defining a data structure representing a hierarchy of at least one programming attribute for developing an application. The data structure is stored in a file to allow the data structure to be used by other data structures stored in other files. The method also includes producing a visual diagram including a graphical representation of the data structure and a graphical representation of the file storing the data structure. The visual diagram also includes a graphical representation of a relationship between the data structure and another data structure and a graphical representation of a relationship between the file storing the data structure and another file storing the other data structure. 
     In another aspect, a computer-readable storage medium stores a computer program for representing information. The computer program includes instructions for causing a computing system to define a data structure representing a hierarchy of at least one programming attribute for developing an application. The data structure is stored in a file to allow the data structure to be used by other data structures stored in other files. The instructions also cause the computing system to produce a visual diagram including a graphical representation of the data structure and a graphical representation of the file storing the data structure. The visual diagram also includes a graphical representation of a relationship between the data structure and another data structure and a graphical representation of a relationship between the file storing the data structure and another file storing the other data structure. 
     In another aspect, a computing system for representing information includes at least one processor configured to process information. The processing including defining a data structure representing a hierarchy of at least one programming attribute for developing an application. The data structure is stored in a file to allow the data structure to be used by other data structures stored in other files. The processing also including producing a visual diagram including a graphical representation of the data structure and a graphical representation of the file storing the data structure. The visual diagram also includes a graphical representation of a relationship between the data structure and another data structure and a graphical representation of a relationship between the file storing the data structure and another file storing the other data structure. The computer system also includes an output device for presenting the visual diagram that includes the graphical representations of the data structure and the file and the graphical representations of the relationship of the data structures and the relationship of the files. 
     In another aspect, a computing system for representing information includes means for processing that include defining a data structure representing a hierarchy of at least one programming attribute for developing an application. The data structure is stored in a file to allow the data structure to be used by other data structures stored in other files. The processing also includes producing a visual diagram including a graphical representation of the data structure and a graphical representation of the file storing the data structure. The visual diagram also includes a graphical representation of a relationship between the data structure and another data structure and a graphical representation of a relationship between the file storing the data structure and another file storing the other data structure. The computer system also includes means for presenting the visual diagram that includes the graphical representations of the data structure and the file and the graphical representations of the relationship of the data structures and the relationship of the files. 
     Implementations may include any or all of the following features. The graphical representation of the files may be removable to allow for manipulating the graphical representations of the data structure to define one or more data structure groups and to create one or more new files for storing the one or more data structure groups. The defined data structure may be manipulated to adjust the at least one programming attribute. The defined data structure may be manipulated for inserting the at least one programming attribute into a file. A statement may be inserted with the at least one programming attribute into the file. Manipulating the data structure may include a drag and drop operation. Manipulating the defined data structure may include at least one of adding, deleting and editing content of the hierarchy of the programming attribute. The programming attribute may be a named data type, a function, etc. The relationship between the data structure and the other data structure may represent lineage of the programming attribute. 
     Aspects can include one or more of the following advantages. 
     Graphically representing programming attributes (e.g., fields, named data type structures, functions, etc.) allows a developer to relatively quickly ascertain attribute details (e.g., data types being used) and relationships among attributes (e.g., a named data type structure using previously defined fields) and files used to store the attributes. Presented in graphical form, attributes, files storing the attributes, etc. may be efficiently manipulated, for example, to edit named data type structures and thereby allow the changes to propagate as needed. 
     Other features and advantages of the invention will become apparent from the following description, and from the claims. 
    
    
     
       DESCRIPTION OF DRAWINGS 
         FIG. 1  is a block diagram of a system for executing graph-based computations. 
         FIGS. 2-6  are user interfaces presenting data type information. 
         FIGS. 7-12  are user interfaces presenting graphical representations of data type information. 
         FIG. 13  is a flowchart of an exemplary programming attribute presentation procedure. 
     
    
    
     DESCRIPTION 
       FIG. 1  shows an exemplary data processing system  100  in which programming attributes such as data types, executable functions, etc. may be graphically presented, for example, to allow a casual viewer to efficiently determine the content, hierarchy and lineage of the attributes. In general, to provide such functionality, the system  100  includes a data source  102  that may include one or more sources of data such as storage devices or connections to online data streams, each of which may store data in any of a variety of storage formats (e.g., database tables, spreadsheet files, flat text files, or a native format used by a mainframe). In this example, an execution environment  104  includes a pre-processing module  106  and an execution module  112 . The execution environment  104  may be hosted on one or more general-purpose computers under the control of a suitable operating system, such as the UNIX operating system. For example, the execution environment  104  can include a multiple-node parallel computing environment including a configuration of computer systems using multiple central processing units (CPUs), either local (e.g., multiprocessor systems such as SMP computers), or locally distributed (e.g., multiple processors coupled as clusters or MPPs), or remote, or remotely distributed (e.g., multiple processors coupled via a local area network (LAN) and/or wide-area network (WAN)), or any combination thereof. 
     The pre-processing module  106  reads data from the data source  102  and performs corresponding processing operations, e.g., in anticipation of further proceeding by other modules. Storage devices providing the data source  102  may be local to the execution environment  104 , for example, being stored on a storage medium connected to a computer running the execution environment  104  (e.g., hard drive  108 ), or may be remote to the execution environment  104 , for example, being hosted on a remote system (e.g., mainframe  110 ) in communication with a computer running the execution environment  104 , over a remote connection. 
     The execution module  112  uses the processed data generated by the pre-processing module  106 , for example, to process the data  114  (e.g., enterprise data, company records, etc.) stored in a data storage system  116  accessible to the execution environment  104 . The data storage system  116  is also accessible to a development environment  118  in which a developer  120  is able to review, edit, etc. the information stored in the data storage system  116 . In some arrangements, the development environment  118  may be utilized in preparing and adjusting the execution environment  104  for performing the desired operations. For example, the development environment  118  may be a system for developing applications as dataflow graphs that include vertices (representing components or datasets) connected by directed links (representing flows of work elements) between the vertices. For example, such an environment is described in more detail in U.S. Publication No. 2007/0011668, entitled “Managing Parameters for Graph-Based Applications,” incorporated herein by reference. A system for executing such graph-based computations is described in U.S. Pat. No. 5,966,072, EXECUTING COMPUTATIONS EXPRESSED AS GRAPHS, incorporated herein by reference. Dataflow graphs made in accordance with this system provide methods for getting information into and out of individual processes represented by graph components, for moving information between the processes, and for defining a running order for the processes. This system includes algorithms that choose interprocess communication methods (for example, communication paths according to the links of the graph can use TCP/IP or UNIX domain sockets, or use shared memory to pass data between the processes). 
     The pre-processing module  106  can receive data from a variety of types of systems including different forms of database systems. The data may be organized as records having values for respective fields (also called “attributes” or “columns”), including possibly null values. When first reading data from a data source, the pre-processing module  106  typically starts with some initial format information about records in that data source. In some circumstances, the record structure of the data source may not be known initially and may instead be determined after analysis of the data source. The initial information about records can include the number of bits that represent a distinct value, the order of fields within a record, and the type of data (e.g., string, signed/unsigned integer) represented by the bits. 
     Similar to being used in a record, different data types (e.g., strings, integers, flowing point values) can be used for processing data (e.g., records) performed by the execution environment  104 , the development environment  118 , etc. For example, various types of data types may be defined and used for processing records (e.g., employee records, student records, etc.). To process such records, individual primitive data types (e.g., strings, date, datetime, integer, decimal, etc.) may be used in concert to define an organization of data types, referred to as a data type structure. For example, the following record groups four primitive types to represent attributes of a person: 
                                            record            string(“,”) surname;            string(“,”) given_name;            date(“YYYY-MM-DD”) date_of_birth;            integer(1) gender; // 0 for male, 1 for female            decimal(9) SSN;           end                        
The record includes a number of fields (e.g., the first and last name of the individual is represented along with their date of birth, gender and social security number), and each field consists of a name and a data type. Referring to  FIG. 2 , such a record may be defined by an editor. In this example, a user interface  200  presents an editor for defining the format of data being read from an input file. Along with defining the data being read (e.g., surname, date of birth, gender), the individual data types (e.g., string, date, integer) and limitations for each field are defined. While this example presents the record type as including five distinct entries of information, the record type may be expanded or contracted. For example, more data may be appended, deleted, combined, etc. with current data. Continuing from the instructions above, a record type may be nested, for example, to express a business entity and a list of corresponding employees:
 
     
       
         
           
               
               
             
               
                   
                   
               
             
            
               
                   
                 /* Business entity */ 
               
               
                   
                 record 
               
               
                   
                   string(“,”) business_name; 
               
               
                   
                   decimal(9) tax_payer_id; 
               
               
                   
                   decimal(11) main_TEL_no; 
               
               
                   
                   record 
               
               
                   
                    record 
               
               
                   
                       string(“,”) last; // last name 
               
               
                   
                       string(“,”) first; // first name 
               
               
                   
                    end name; // subrecord 
               
               
                   
                    record 
               
               
                   
                       date(“YYYY-MM-DD”) date_of_birth; 
               
               
                   
                       integer(1) gender; // 0 for male, 1 for female 
               
               
                   
                    end bio; // subrecord 
               
               
                   
                    decimal(9) SSN; 
               
               
                   
                   end[integer(4)] employees; // vector of employees 
               
               
                   
                 end 
               
               
                   
                   
               
            
           
         
       
     
     Through creating and naming data type structures, equivalent fields, etc. may be used for more than one application (e.g., to represent student information, ordering information for employees of a number of companies, etc.). Referring to  FIG. 3 , a user interface  300  may be implemented for presenting a data type structure that includes nested data type information. In this arrangement, fields associated with a company are defined in an upper portion (as represented by a bracket  302 ) and fields for the employee information are defined in a lower portion (as represented by bracket  304 ). As can be imagined, data type structures may be defined for a large variety of applications and many similar fields may be used and re-used (e.g., to define a record for student information, a record for employee information, etc.). 
     Referring to  FIG. 4 , one or more techniques may be implemented to assist a developer with appropriately defining fields and grouping the fields to form data type structures for use, e.g., in application development. For example, by interacting with a user interface  400  (e.g., selecting a field with a pointing device), a drop-down menu  402  may appear and present a listing of named data type structures that may be potentially selected (by the developer) for use in an application. As represented in the drop-down menu  402 , as more and more named data type structures are defined, the presented listing may become onerously large and difficult for a user to navigate to identify a named data type structure of interest. For example, along with frequently selected named data type structures, the listing may grow over time to include a large number of less-frequently-used named data type structures that are unique to specific applications. As illustrated in the figure, the sheer number of entries in the menu  402  could drastically affect a developer&#39;s efficiency and may even discourage use of the user interface  400 . Further, only being assigned names and lacking any other information (as shown in the entries of the menu  402 ) many named data type structures may be redundant and provide no information regarding relationships (if any) among other named data type structures. 
     One or more techniques and methodologies may be implemented to provide more manageable representations of data type structures. In one example, data type structures used in multiple, different applications may be commonly defined. From the example above, the data type structure for each student is equivalent to the data type structure of each business employee and can be commonly defined as: 
                                            record            record             string(“,”) last; // last name             string(“,”) first; // first name            end name; // subrecord            record             date(“YYYY-MM-DD”) date_of_birth;             integer(1) gender; // 0 for male, 1 for female            end bio; // subrecord            decimal(9) SSN;           end                        
By naming this common data type structure (e.g., “person_t”), the named data type structure can be called out and used in applications for similar purposes such as collecting information for student and employee applications. For example, the named data type structure (“person_t”) may be defined as:
 
                                               type person_t =              record               record               string(“,”) last; // last name               string(“,”) first; // first name               end name; // subrecord               record               date(“YYYY-MM-DD”) date_of_birth;               integer(1) gender; // 0 for male, 1 for female               end bio; // subrecord               decimal(9) SSN;           end;                        
Once defined, the named data type structure (“person_t”) can be used to respectively define a data type structure for the business employee and classroom student applications:
 
                                            /* Business entity */           record            string(“,”) business_name;            decimal(9) tax_payer_id;            decimal(11) main_TEL;            person_t[integer(4)] employees; // here           end           /* Classroom */           record            string(“,”) home_room_instructor;            decimal(2) grade;            person_t[integer(4)] students; // and here           end;                        
Similarly, the new data type structures may be named for use in multiple applications. For example, a named data type structure (titled “business_t”) that uses the named data type structure “person_t” may be defined for storing business information:
 
                                            type business_t =           record            string(“,”) business_name;            decimal(9) tax_payer_id;            decimal(11) main_TEL;            person_t[integer(4)] employees; // vector of employees           end;                        
Similarly, a named data type structure (named “class_t”) that uses the named data type structure “person_t” may be defined for storing class information:
 
     
       
         
           
               
               
             
               
                   
                   
               
             
            
               
                   
                 type class_t = 
               
               
                   
                 record 
               
               
                   
                  string(“,”) home_room_instructor; 
               
               
                   
                  decimal(2) grade; 
               
               
                   
                  person_t[integer(4)] students; // vector of students 
               
               
                   
                 end; 
               
               
                   
                   
               
            
           
         
       
     
     Various advantages may be provided from using a common data type structure to define multiple other data type structures. For example, rather than needing to individually adjust the two data type structures (to adjust an included data type structure), the commonly used named data type structure may be redefined once. Correspondingly, by adjusting the named data type structure, any changes would be reflected in both of the data type structures (and any other data type structures that use the named data type structure). Thereby, efficiency may be improved by allowing developers to adjust a single instance of a named data type structure being used in multiple data structures. However, developers should remain alert to such propagating adjustments (e.g., when the developer is interested in only adjusting an included data type structure in less than all of the data type structures that use the included data type structure). 
     Referring to  FIG. 5 , once defined, one or more techniques or methodologies may be implemented for storing the named data type structures and retrieving the structures for use. For example, the named data type structures may be expressed in a language such as Data Manipulation Language (DML) and stored in text files (referred to as DML files). Using the named data type structures defined above (e.g., “person_t”), a DML file titled “project.dml” may be stored in a storage device and retrieved for using the defined data type structure. Various techniques may be implemented for accessing and using named data type structures stored in DML files. For example, a file (e.g., another DML file) may include one or more instructions (e.g., an “include” statement, a “package” statement, etc.) that allows one or more other DML files (and the named data type structures defined within the file) to be accessed and used. For example, the contents of a DML file may include the following language: 
                                            include “project.dml”;           type sales_prospects_t =           record            class_t[integer(4)] educational;            business_t[integer(4)] commercial;           end;                        
By accessing the DML file (“project.dml”) through the use of the “include” statement, the named data type structures (e.g., “business_t”) defined within the DML file can be retrieved and used to define a data type structure (e.g., “sales_prospects_t”) defined within the file. Such a capability reduces redundancy of data type definitions along with the probability of conflicting data type structures (e.g., data type structures with the same name but different type definitions).
 
     As illustrated in the figure, once defined and stored, named data type structures may be presented for selection and use by a developer. For example, a user interface  500  may include programming attributes for building applications (e.g., global variables  502 , functions  504 , user-defined types  506 , etc.). As presented in the user interface  500 , three named data type structures (e.g., “person_t”, “business_t” and “class_t”) are included in the user-defined types  506  and may be selected for use by a developer. However, similar to the drop down menu  402  presented in  FIG. 3 , as the list of data type structures grows for various applications, the entries included in the user-defined types  506  may become unwieldy along with redundant entries becoming rampant. Through the growth of frequently used and less frequently used named data type structures, challenges may arise to identify what particular data type structures are available. Redundancy may also become an issue as identifying previously-defined data type structures may become difficult and overly time-consuming for a developer. While the presentation of the user interface  500  provides a listing of each named data type structure, little additional information is provided. For example, lineage of dependency among data type structures, and how the related data types can be grouped, etc. is generally absent from the user interface  500 . Further, while the name of the data type structure is present, no information regarding the content of the data type structure is provided from the interface beyond what can be gleamed from the title of each data type structure. 
     Referring to  FIG. 6 , a graphical representation  600  is illustrated that represents a named data type structure and the collection of fields that define the structure. Additionally the graphical representation  600  identifies the DML file  602  (e.g. “project.dml”) within which the data type structure is defined and stored. A portion of the graphical representation  600  provides an optional name  604  (e.g., DML files) for the file, referred to as a “package”, which provides a prefix for the names of the attributes defined in the files, when called external to the file. In this particular example, the package name has been left blank. 
     In this example, the graphical representation  600  presents the named data type structure “person_t” as being defined as: 
                                            type person_t =           record              string(“,”) surname;              string(“,”) given_name;              date(“YYYY-MM-DD”) date_of_birth;              integer(1) gender; // 0 for male, 1 for female              decimal(9) SSN;           end;                        
In this example, the graphical representation  600  is oriented to be read from the viewer&#39;s left to right and initially presents the named data type structure name  606  (e.g., “person_t”) on the viewer&#39;s left. From the structure defined above, a series of rectangles present the individual fields (e.g., surname  608 , given_name  610 , date of birth  612 , gender  614  and social security number  616 ) nested into the data type structure “person_t”. The graphical representation  600  conveys a hierarchical layout of the named data type structure and its content. Located to the far left side of the graphical representation  600 , the name  606  identifies the overall structure while the individual fields  608 ,  610 ,  612 ,  614 ,  616  are located more to the right and indicate their residing in a lower level in the hierarchy of the data type structure. From this presentation, the viewer is provided an easy-to-read graphical layout of the information associated with the named data type structure. While rectangle shapes are used in this instance to present the information, other shapes and/or collections of difference shapes may be used for presentations. Other graphical features may also be incorporated for assisting a viewer in efficiently ascertaining the named data type structure information. For example, different colors may be implemented, e.g., to quickly alert a viewer to potential issues (e.g., repeated or conflicting fields being defined within a named data type structure). In this instance, static graphics are used for presenting the information; however, graphics that change over time (e.g., animations, video, etc.) may also be used, for example, to quickly grab a viewer&#39;s attention. Other graphical representations may also be used, for example, rather than using a left-to-right reading orientation, other layouts and orientations may be implemented for presenting one or more named data structures.
 
     Referring to  FIG. 7 , a graphical representation  700  illustrates a DML file (e.g., named “project.dml”) within which three named data type structures are defined. In particular, along with the graphical representation  600  of the previously defined named data type structure “person_t” (shown in  FIG. 6 ), two additional named data type structures (titled “business_t” and “class_t”) are graphically represented in the DML file: 
                                             type business_t =            record             string(“,”) business_name;             decimal(9) tax_payer_id;             decimal(11) main_TEL;             person_t[integer(4)] employees; // here            end           and            type class_t =            record             string(“,”) home_room_instructor;             decimal(2) grade;             person_t[integer(4)] students; // and here            end;                        
Both the “business_t” named data type structure and the “class_t” named data type structure, illustrated by corresponding graphical representations  702 ,  704 , include fields (e.g., the “employee” field included in the “business_t” named data type structure, and the “student” field included in the “class_t” data type structure) that are defined by the named data type structure “person_t”. To graphically illustrate use of the “person_t” named data type structure by the “business_t” and the “person_t” named data type structures, corresponding arrowed lines  706 ,  708  show the connections between the pairs of named data type structures. From these graphically represented relationships, a viewer (e.g., a developer) can relatively quickly identify the relationships between the named data type structures such as information shared among data type structures, lineage of the use of the previously defined named data type structure (such as “person_t”), etc. Along with providing a layout of the relationships of the named data type structures, the graphical representation  700  visually alerts the viewer to potential adjustment issues. For example, if changes are made to the “person_t” named data type structure, as illustrated by the two arrowed lines  706 ,  708 , both the “business_t” and “class_t” named data type structures would be affected by the changes (e.g., the “employees” field of the “business_t” named data type structure and the “students” field of the “class_t” named data type structure would experience any changes to the “person_t” named data type structure). Similar to presenting the relationship among data type structures, other types of relationships may be graphically presented such as relationships between files.
 
     Referring to  FIG. 8 , two DML files are graphically represented along with their relationships. The graphical representation  700  of the “project.dml” file (shown in  FIG. 7 ) is presented along with the three named data structures defined by the DML file (e.g., the “class_t” named data structure  702 , the “business_t” named data structure  704  and the “person_t” named data structure  600 ). Additionally another DML file titled “CRM.dml” is illustrated with a graphical representation  800  within which a named data type structure (titled “sales_prosects_t”) is represented. In this example, two named data type structures are defined by the “CRM.dml” file (e.g., named “educational” and “commercial”) and each of the two named date type structures are defined through named data type structures provided by the “project.dml”. In particular, the “educational” named data type structure is defined from the “class_t” named data type structure and the “commercial” named data type structure is defined by the “business_t” named data type structure. To represent these two relationships between the “CRM.dml” file and the “project.dml” file, two arrowed lines  802 ,  804  are illustrated as linking the two graphical representations of the files. Similar to the representations of the named data type structures being linked within a file, similar relationships may be formed through the linking of fields and named type definitions, etc. between two or more files. For example, adjustments made to the definitions of the “class_t” named data type structure  702  or the “business_t” named data type structure  704  (e.g., by changing the “person_t” named data structure  600 ) in the “project.dml” file can impact the fields (e.g., “educational” and “commercial”) and named data type structures (e.g., “sales_prospect_t” named data type structure) in the linked “CRM.dml” file. 
     Along with presenting graphical representations for the relationships among the fields and named data type structures of the multiple files, the relationship among the files may be graphically represented to the viewer. For example, file level operations may be represented. In this example, for the fields of the CRM.dml file (e.g., “educational” and “commercial”) to attain access to the named data type structures in the “project.dml” file, the “project.dml” file needs to be identified by the “CRM.dml” file. For example, an “include” statement may be entered in the “CRM.dml” file to attain access to the “project.dml” file. To graphically represent the identification, along with listing its own file name  806  in the graphical representation  800 , the one or more needed files (e.g., the “project.dml”) are also represented as needed packages  808 . Further, in this example an arrowed, dashed line  810  graphically represents the file-level operation of the “CRM.dml” file of using an “include” statement to attain access to the contents of the “project.dml” file. 
     Referring to  FIG. 9 a   , various types of graphical representations may be used to illustrate relationships among files, fields and named data type structures. For example, to reduce the visual complexity of the graphical representations, various amounts of detail may be reduced or removed. In the illustrated example, individual field information is removed from the graphical representations  900 ,  902  of the two DML files. By removing the information, graphical representations  904 ,  906 ,  908 ,  910  of the data type structures are compacted by simply representing the names of each named data type structure (e.g., “person_t”, “business_t”, “class_t” and “sales_prospects_t”). Along with reducing the amount of visual business of the graphical representations, real estate is conserved for other information such as the arrowed lines  912 ,  914  that represent relationships between named data type structures within a file, and arrowed lines  916 ,  918  that represent relations between named data type structures that reside in different files. Similarly, the conserved real estate may assist the viewer in quickly recognizing other relationships, e.g., files identifying other files with an arrowed dashed line  920  to indicate the use of an “include” statement to provide file access. Along with providing the viewer (e.g., a developer) with a compacted view of named data type structures and their relationships, other functionality may be provided by the graphical representations. For example, manipulating fields, named data type structures and related information may be more efficiently executed by using the graphical representations. 
     Referring to  FIG. 9 b   , graphical representations may be adjusted and manipulated to efficiently construct, reconstruct, etc. the files data type structures, files, etc. For example, representations of data structures may be grouped differently to define new files. As illustrated, the graphical representations of files (e.g., DML file representations  900  and  902 ) have been removed allowing a developer to adjust the grouping of the graphical representations of the data type structures  904 ,  906 ,  908 ,  910 . Along with allowing the data type structures to be reorganized for storage in same or different file or files, such manipulations may improve relationships among the files and reduce the occurrence of unnecessary “include” statements. Just to demonstrate with the illustrated example, the graphical representation  906  (for the data type structure “business_t”) may be grouped with the graphical representation  910  (for the data type structure “sales_prospects_t”) for more efficient operation. Once grouped, the graphical representations may be initiate file creation for storing the newly grouped data type structures. Along using such operations for grouping and manipulating data type structures, file level operations may also be performed. For example, graphical representations of files (e.g., representations  900 ,  902 ) may be manipulated for combining, removing, appending, etc. the content (e.g., data type structures) of the files. 
     Referring to  FIG. 10 , a user interface  1000  is illustrated that provides an editor  1002  for manipulating graphical representations of fields, named data type structures and other types of programming attributes. The editor  1002  includes a window  1004  that presents the graphical representations of the fields, named data type structures and related information (e.g., arrowed lines to represent data type relationships). The editor  1002  also includes a palette  1006  that allows a user (e.g., a developer) to select from a variety of fields, named data type structures, etc. for inclusion in the applications being developed. For example, as represented in the figure by bold, arrowed line  1008 , a pointing device may be used to select and insert (e.g., drag and drop) a named data type structure into the window  1004  for project development. Similarly, the selection and insertion operation may be reversed such that a named data type structure is selected from the window  1004  (after being developed) and inserted into the palette  1006 . Selection and insertion operations may also be executed solely within the window  1004  or the palette  1006 . For example, operations (e.g., drag and drop operations) may be executed in the palette  1006  to create, edit, etc. one or more fields, named data type structures, etc. Similarly, operations (e.g., select, insert, delete, append, etc.) may be initiated by a user in the window  1004  for adjusting fields, named data type structures, etc. Other types of manipulation operations may also be executed, for example, relationships between fields, named data type structures, files (e.g., DML files), etc. may be graphically manipulated. 
     Referring to  FIG. 11 , operations for manipulating fields, named data type structures, files, etc. and relationships may be graphically initiated by a user (e.g., a developer). For example, arrowed lines may be manipulated (e.g., deleted, added, moved, etc.) for adjusting relationships among fields and named data type structures. In this illustrated example, two lines  1100  and  1102  are deleted (as represented by graphical symbol “x” being respectively positioned on each line through a user&#39;s pointing device). Based upon the relationship being severed between the “project.dml” file and the “CRM.dml” file due to deleting the lines, the “CRM.dml” no longer needs access to the contents of the “project.dml” file. As such, the instruction within the “CRM.dml” file for accessing the “project.dml” file (e.g., “include ‘project.dml’”) is removed from the “CRM.dml” file (as represented by the dashed-line box  1104 ). Correspondingly, the dashed line  1106  that represents this relationship between the “CRM.dml” file and the “project.dml” file may be similarly removed from the graphical representations of the files. Alternatively, when such relationships between files are established or re-established (e.g., by connecting the two files with lines  1100  and  1102 ), the instruction (e.g., “include ‘project.dml”’) may be inserted or re-inserted into the appropriate file (e.g., “CRM.dml”) and a graphical representation (e.g., the dashed line  1106 ) may again be presented to illustrate the relationship. 
     Referring to  FIG. 12 , as the amount of named fields, named data type structures, files, etc. grow, one or more techniques may be implemented to assist the user (e.g., the developer) to navigate among the potential fields, named data type structures, files, etc. that may be selected for use during application development. For example, one or more graphical representations may present a selectable list of files that include useable fields and named data type structures. In some arrangements, hierarchical listings may be used to assist the user in navigating the files, named data type structures, etc. As illustrated in the figure, a pane  1200  is included in a user interface  1202  that allows the user to navigate among a listing of different packages (e.g., XML processing data types, lookup data types, meta programming data types, date/time data types, metadata types, etc.). In one arrangement, once a selection is made, artifacts defined in the selected package, such as named data type structures and functions may be displayed in a graphical representation located on the right-hand side of the user interface  1202  and manipulated (e.g., selected, navigated, dragged-and-dropped onto the pane  1200 ) as needed. 
     Along with organizing, manipulating, etc. fields, named data type structures, files for application development, other types of programming attributes may similarly be graphically represented for assisting developers. For example, functions, variables, etc. used by applications may similarly become unwieldy as more and more such programming attributes are created and stored in libraries for later retrieval and reuse. Other techniques may also be implemented for assisting developers in identifying and selecting appropriate programming attributes. For example, algorithms for logically distributing programming attributes among files (referred to as clustering algorithms) may be used, for example, to organize fields, named data type structures, functions, etc. Through such organizing techniques the amount of instructions (e.g., “include” statements) may be reduced along with redundant use of named data type structures. 
     Referring to  FIG. 13 , a flowchart  1300  represents operations of a procedure for graphically representing programming attributes such as named data type structures used in application development. The operations are typically executed by a single computing device (e.g., providing a development environment); however, operations may be executed by multiple computing devices. Along with being executed at a single site, operation execution may be distributed among two or more locations. 
     Operations may include defining  1302  a data structure representing a hierarchy of one or more programming attributes for developing an application. The graphical representation of the files are removable to allow for manipulating the graphical representations of the data structure to define one or more data structure groups and to create one or more new files for storing the one or more data structure groups. For example, a hierarchy of subrecords, records, fields, named data type structures, etc. may be used to define a data structure. The data structure is defined to be included in a single file (for storage), but in some arrangements the data structure may be included in multiple files (e.g., for storing and later retrieval). Operations also include producing  1304  a visual diagram including a graphical representation of the data structure and a graphical representation the file storing the data structure. The visual diagram also includes a graphical representation of a relationship between the data structure and another data structure and a graphical representation of a relationship between the file storing the data structure and another file storing the other data structure. For example, as shown in  FIG. 7 , two named data type structures (e.g., “business_t” and “class_t”) are graphically represented in a visual diagram that represents the named data type structures included in a file “project.dml”. A third data type structure is also presented (e.g., “person_t”) that includes a hierarchy of fields that are used by both of the other named data type structures (e.g., “business_t” and “class_t”) as indicated by the graphical lines  706 ,  708  also represented in the visual diagram. Along with illustrating the contents of each data structure, relationships among the data structures are graphically represented, for example, to allow a viewer (e.g., a developer) to relatively quickly ascertain the lineage of fields, named data type structures, etc. and their relationships. 
     The approach for graphically representing computational artifact described above can be implemented using software for execution on a computer. For instance, the software forms procedures in one or more computer programs that execute on one or more programmed or programmable computer systems (which may be of various architectures such as distributed, client/server, or grid) each including at least one processor, at least one data storage system (including volatile and non-volatile memory and/or storage elements), at least one input device or port, and at least one output device or port. The software may form one or more modules of a larger program, for example, that provides other services related to the design and configuration of dataflow graphs. The nodes and elements of the graph can be implemented as data structures stored in a computer readable medium or other organized data conforming to a data model stored in a data repository. 
     The software may be provided on a storage medium, such as a CD-ROM, readable by a general or special purpose programmable computer, or delivered (encoded in a propagated signal) over a communication medium of a network to a storage medium of the computer where it is executed. All of the functions may be performed on a special purpose computer, or using special-purpose hardware, such as coprocessors. The software may be implemented in a distributed manner in which different parts of the computation specified by the software are performed by different computers. Each such computer program is preferably stored on or downloaded to a storage media or device (e.g., solid state memory or media, or magnetic or optical media) readable by a general or special purpose programmable computer, for configuring and operating the computer when the storage media or device is read by the computer system to perform the procedures described herein. The inventive system may also be considered to be implemented as a computer-readable storage medium, configured with a computer program, where the storage medium so configured causes a computer system to operate in a specific and predefined manner to perform the functions described herein. 
     A number of embodiments of the invention have been described. Nevertheless, it will be understood that various modifications may be made without departing from the spirit and scope of the invention. For example, some of the steps described above may be order independent, and thus can be performed in an order different from that described. 
     It is to be understood that the foregoing description is intended to illustrate and not to limit the scope of the invention, which is defined by the scope of the appended claims. For example, a number of the function steps described above may be performed in a different order without substantially affecting overall processing. Other embodiments are within the scope of the following claims.