Abstract:
There is disclosed a method, apparatus and computer program for facilitating improvement of a user interface. A plurality of critical paths though the user interface are determined. A complexity of each of the critical paths is calculated. The complexity of the critical paths relative to a level of criticality of those paths is then indicated.

Description:
FIELD OF THE INVENTION  
       [0001]    The invention relates to user interface design and more specifically to a solution for facilitating the improvement of key areas of a user interface. 
       BACKGROUND OF THE INVENTION  
       [0002]    As applications become increasingly powerful, a key target in developing successful software is to provide functionality in as a simple and consumable way as possible. The functionality provided by applications is presented to the user through a User Interface (UI), which themselves have seen a corresponding increase in complexity as the capabilities of the underlying application grows. Given that the UI acts as the boundary between the user and the application, a poorly designed or overly complex UI can markedly reduce a user&#39;s satisfaction with the product, or even prevent the user from benefiting from the application&#39;s capabilities. 
         [0003]    For the purpose of the discussion herein, the complexity of a UI is defined by its “navigability” (the ease of navigating through the UI) and its “simplicity” (the ease of exercising functionality presented by the UI). Navigability reflects, for example, how many panels the user has to navigate through to perform a given task, while simplicity reflects for example the number of possible data fields/actions a user has to fill/perform to execute a defined functional task in the application. Overall complexity is often a delicate balance between navigability and simplicity. Attempting to improve navigability, by reducing the number of panels to navigate through, has the consequence of worsening its simplicity; in other words, it becomes harder for the user to identify necessary actions on a given panel, as it becomes increasingly overloaded with options. 
         [0004]    There are several problems facing architects, developers and testers of UIs. For example, although significant effort is conventionally spent in testing an application&#39;s core functionality, the UI traditionally receives less attention and is treated subjectively rather than undergoing objective analysis. This is surprising given the recognition of its importance, but may reflect a lack of tooling and unbiased approaches. Further, it has been appreciated by the inventors that a new user&#39;s first impression is typically gained through exercising core (“Golden Path”) tasks, and thus that it is important to ensure that such tasks are the simplest, even at the possible expense of increased complexity for less-frequently used “advanced” tasks. 
         [0005]    There is currently a lack of tools to measure quantitatively and objectively the complexity of a UI. Further, current tooling gives a very poor view of complexity in relation to the rest of the interface under test, particularly concerning the importance of Golden Paths. 
       SUMMARY OF THE INVENTION  
       [0006]    According to a first aspect, there is provided a method for facilitating improvement of a user interface, the method comprising: determining a plurality of critical paths through the user interface; calculating a complexity of each of the critical paths; and indicating the complexity of the critical paths relative to a level of criticality of those paths. 
         [0007]    A path may be critical (golden) if it is one that is frequently exercised by users. Alternatively, a path may be critical if it is the least complex route to a node which users have identified as critical. A solution has been disclosed where a user-interface designer may be provided with an indication of the complexity of the critical paths relative to a level of criticality (goldenness) of those paths. In other words, one path may be more critical than another and this is indicated relative to the complexity of those paths. For example, path A may be more critical than path B and in addition path 
         [0008]    A may be more complex than path B. If a path is both relatively more critical and relatively more complex, then attention to the user-interface (path A) may be required. 
         [0009]    In one embodiment, paths exercised by users of the user interface are monitored and the most frequently exercised paths are identified as critical paths. 
         [0010]    In one embodiment users identify nodes within the user interface as fulfilling their goals. A least complex route through the user interface to each of the identified nodes is then calculated. Such routes calculated comprise critical paths. 
         [0011]    In one embodiment, a user assigns a weighting to each node identified as fulfilling a user&#39;s goal. 
         [0012]    In one embodiment, the weighting assigned to a final node (identified as fulfilling a user&#39;s goal) in a critical path is identified. That weighting is applied to the complexity associated with the critical path to create a weighted complexity. 
         [0013]    In one embodiment, the weighted complexity of each critical path relative to a level of criticality of those paths is indicated. 
         [0014]    In one embodiment, the complexity of nodes forming part of critical paths is identified. 
         [0015]    In one embodiment, for each node, at least one of the following is determined: depth of the node; the breadth of the node; the number of transitions from the node to another node; and the number of data fields that have to be filled in to reach the node. 
         [0016]    According to a second aspect, there is provided an apparatus for facilitating improvement of a user interface, the apparatus comprising: determining a plurality of critical paths through the user interface; calculating a complexity of each of the critical paths; and indicating the complexity of the critical paths relative to a level of criticality of those paths. 
         [0017]    The invention may be implemented in computer software. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS  
         [0018]    Embodiments of the present invention will now be described, by way of example only, and with reference to the following drawings. 
           [0019]      FIG. 1  illustrates an exemplary user interface. 
           [0020]      FIGS. 2   a,    2   b  and  2   c  show, in accordance with a first embodiment of the present invention, the process of generating a route map of possible paths within a user interface. 
           [0021]      FIG. 3  illustrates, in accordance with a first embodiment of the present invention, the process of modelling user behaviour. 
           [0022]      FIG. 4  shows, in accordance with a first embodiment, the process of determining golden paths. 
           [0023]      FIG. 5  is a flow chart, in accordance with a first embodiment of the present invention, of the process of calculating the complexity of the determined golden paths. 
           [0024]      FIG. 6  is a flow chart, in accordance with a second embodiment of the present invention, of the process of determining golden nodes. 
           [0025]      FIG. 7  illustrates, in accordance with a second embodiment of the present invention, the process of determining golden paths. 
           [0026]      FIG. 8  illustrates, in accordance with a second embodiment of the present invention, the process of calculating the complexity of the golden paths. 
           [0027]      FIG. 9  illustrates the components involved in a first embodiment of the present invention. 
           [0028]      FIG. 10  illustrates the components involved in a second embodiment of the present invention. 
           [0029]      FIG. 11  illustrates an exemplary user interface. 
       
    
    
     DETAILED DESCRIPTION OF THE INVENTION  
       [0030]    Tooling is provided which is capable of measuring complexity of a user interface. The solution disclosed takes into account the paths most frequently exercised by users (Golden Paths). 
         [0031]      FIG. 1  illustrates the structure of an exemplary user interface. For explanatory purposes, this user interface is shown as a simple tree of nodes. It will however be appreciated that more complicated grid structures are also envisaged. This will be addressed in more detail below on. 
         [0032]    With reference to  FIG. 1 , this diagram has a root web page identified as URL 1 . URL 1  has links (transitions) to its two children URL 2  and URL 5 , which each have in turn have transitions to their children URL 3 , URL 4  and URL 6 . Each web page may additionally have a number of data fields which need input before a transition to another page is made. This is also shown on  FIG. 1 .  FIG. 1  also shows directionality of the transitions via arrows. It should however be appreciated that this does not preclude the possibility of a user retracing their steps via, for example, the use of the browser “back” arrow. 
         [0033]    Whilst the example is of a web site including a plurality of web pages, it should be appreciated that the invention is not limited to such. The invention is equally applicable to other types of user interface where a user can transition between multiple panes, pages, etc. 
         [0034]      FIGS. 2   a  and  2   b  show, in accordance with an embodiment, the generation of a conceptual route map of possible paths (nodes) within a user interface and also the determination of the complexity of these nodes. 
         [0035]    At step  10  the following counters are initialised to 0: a depth counter (D tot ), an accumulated breadth counter (B tot ) and an accumulated data fields counter (F tot ). The breadth counter is used to determine the navigability of a given node, by tracking the number of alternative transitions en-route to the node. The depth counter is for determining which level and the number of data fields counter is used to determine the number of data fields a user has to input to reach the current node. The conceptual route map that is generated is held as a database having the following entries for each node in the user interface:
   (i) a node (e.g., URL) identifier;   (ii) the number of data fields (m);   (iii) the accumulated depth of the node;   (iv) the accumulated breadth of the node;   (v) the number of data fields needed to be filled in to reach the current node; and   (vi) the number of transitions for a node (n)   
 
         [0042]    At step  20 , an entry for the current node (node i) is generated in the database. Identifying information is then associated with the node. For example, a current web page may have a particular URL associated with it (e.g., URL 1 ). 
         [0043]    The number of data fields (m i ) presented to the user as part of the current node is then counted and stored in the database to update m i  (step  40 ). At step  50 , the number of transitions (n) from the current node (i) to another node are counted and stored in the database. The depth for the current node (D i ) is then made equal to D tot . The breadth for the current node (B i ) is then made equal to B tot  and the number of accumulated data fields F i  is then made equal to F tot . These values are all stored against node i in the database (step  60 ). 
         [0044]    The D tot , B tot  and F tot  counters are all used respectively to complete the database entries for the current node i. 
         [0000]    Thus for the root node (URL 1 ) of  FIG. 1 , the entry generated looks as follows: 
         [0000]                                                    Number of           Accumulated   Number of           data fields       Accumulated   Number of   transitions       Identifier   (m)   Depth   Breadth   Data Fields   (n)                   URL1   2   0   0   0   2                    
It is determined at step  70  whether there are any unprocessed transitions.
 
         [0045]    Since only the root node (URL 1 ) has been processed, the answer is yes (URL 2  &amp; URL 5 ) and processing proceeds to  FIG. 2   b,  step  85 . The system moves to the next transition (i.e., node j) URL 2  (step  85 ). At step  95  counters are incremented as follows: 
         [0000]        D   tot   =D   tot +1(becomes 1),  B   tot   =B   tot   +n   i (i.e.,  n   i  is 2 and  B   tot  becomes 2) and  F   tot   =F   tot   +m   i  (i.e.,  m   i  is 2 and  F   tot  becomes 2). 
         [0046]    At step  96  i is set to the value of j. An entry is then generated for URL 2  in the database (step  20 ), identifying information is associated with this entry (step  30 ). The number of data fields is counted for the current node and stored at step  40 . The number of transitions n i  is counted and stored at step  50  and this is stored in the database. 
         [0047]    At step  60 , D i  is set to D tot , B i  is set to B tot  and F i  is set to F tot . These values are then stored against node i in the database: 
         [0000]    
       
         
               
               
               
               
               
               
             
           
               
                   
               
               
                   
                 Number of 
                   
                   
                 Accumulated 
                 Number of 
               
               
                   
                 data fields 
                   
                 Accumulated 
                 Number of 
                 transitions 
               
               
                 Identifier 
                 (m) 
                 Depth 
                 Breadth 
                 Data Fields 
                 (n) 
               
               
                   
               
             
             
               
                 URL1 
                 2 
                 0 
                 0 
                 0 
                 2 
               
               
                 URL2 
                 1 
                 1 
                 2 
                 2 
                 2 
               
               
                   
               
             
          
         
       
     
         [0048]    It is determined at step  70  that there is another unprocessed transition to URL 3 . The system moves to the next transition (node j), URL 3  (step  85 ). At step  95  D tot  is incremented by 1 (to become 2); B tot  is incremented by the value of n for the previous node i (i.e., 2) and now becomes 4 and the F tot  is incremented by m i  (i.e., 1) to become 3. At step  96 , i is set to equal j. Processing then loops round to step  20 . 
         [0049]    An entry is then generated for URL 3  in the database (step  20 ), identifying information is associated with this entry (step  30 ) and the number of data fields m i  is counted and stored at step  40 . The number of transitions n i  is counted at step  50  and this is also associated with the new entry. 
         [0050]    At step  60 , D i  is set to D tot , B i  is set to B tot  and F i  is set to F tot . These values are stored against node i in the database: 
         [0000]    
       
         
               
               
               
               
               
               
             
           
               
                   
               
               
                   
                 Number of 
                   
                   
                 Accumulated 
                 Number of 
               
               
                   
                 data fields 
                   
                 Accumulated 
                 Number of 
                 transitions 
               
               
                 Identifier 
                 (m) 
                 Depth 
                 Breadth 
                 Data Fields 
                 (n) 
               
               
                   
               
             
             
               
                 URL1 
                 2 
                 0 
                 0 
                 0 
                 2 
               
               
                 URL2 
                 1 
                 1 
                 2 
                 2 
                 2 
               
               
                 URL3 
                 4 
                 2 
                 4 
                 3 
                 0 
               
               
                   
               
             
          
         
       
     
         [0051]    It is determined at step  70  that there are no unprocessed transitions and at step  80  that URL 3  is not the root node. At step  90  the system moves up a level to node k (i.e., moves back to the node last visited) and D tot  is decremented by 1 to become 1, B tot  is decremented by the new value of n (2) to become 2 and F tot  is decremented by the new value of m (1) to become 2. In other words the new values should correspond to the values listed against URL 2  in the database. At step  97  i is set to equal k. 
         [0052]    It is determined at step  70  that URL 2  has one more unprocessed transition URL 4 . Consequently the system moves to the next transition (j) URL 4  at step  85 . At step  95 , D tot  is incremented by 1 to become 2, B tot  by n i  (2) to become 4. Also at step  95 , F tot  is incremented by m i  (1) to become 3. At step  96  i is set to the value of j. Processing then continues with step  20 . 
         [0053]    At step  20 , a new entry for URL 4  is generated and at step  30  identifying data is associated with this entry. The number of data fields (m i , 0) is counted and stored in the database at step  40 . At step  50 , the number of transitions (n i ) from the current node are counted and stored. 
         [0054]    At step  60 , D i  is set to D tot , B i  is set to B tot  and F i  is set to F tot . Theses values are stored against node i: 
         [0000]    
       
         
               
               
               
               
               
               
             
           
               
                   
               
               
                   
                 Number of 
                   
                   
                 Accumulated 
                 Number of 
               
               
                   
                 data fields 
                   
                 Accumulated 
                 Number of 
                 transitions 
               
               
                 Identifier 
                 (m) 
                 Depth 
                 Breadth 
                 Data Fields 
                 (n) 
               
               
                   
               
             
             
               
                 URL1 
                 2 
                 0 
                 0 
                 0 
                 2 
               
               
                 URL2 
                 1 
                 1 
                 2 
                 2 
                 2 
               
               
                 URL3 
                 4 
                 2 
                 4 
                 3 
                 0 
               
               
                 URL4 
                 0 
                 2 
                 4 
                 3 
                 0 
               
               
                   
               
             
          
         
       
     
         [0055]    The system then moves back up the tree to process URL 5  and URL 6 . 
         [0056]    Finally the system is back at root node URL 1  and it is determined that there are no unprocessed transitions at step  70 . It is further determined at step  80  that URL 1  is the root node. Consequently processing ends. 
         [0057]    The database now looks as follows: 
         [0000]    
       
         
               
               
               
               
               
               
             
           
               
                   
               
               
                   
                 Number of 
                   
                   
                 Accumulated 
                 Number of 
               
               
                   
                 data fields 
                   
                 Accumulated 
                 Number of 
                 transitions 
               
               
                 Identifier 
                 (m) 
                 Depth 
                 Breadth 
                 Data Fields 
                 (n) 
               
               
                   
               
             
             
               
                 URL1 
                 2 
                 0 
                 0 
                 0 
                 2 
               
               
                 URL2 
                 1 
                 1 
                 2 
                 2 
                 2 
               
               
                 URL3 
                 4 
                 2 
                 4 
                 3 
                 0 
               
               
                 URL4 
                 0 
                 2 
                 4 
                 3 
                 0 
               
               
                 URL5 
                 1 
                 1 
                 2 
                 2 
                 1 
               
               
                 URL6 
                 2 
                 2 
                 3 
                 3 
                 0 
               
               
                   
               
             
          
         
       
     
         [0058]    Having generated an internal route map of the possible nodes that a user may visit in exercising a user interface such as that shown by  FIG. 1 , some modelling of actual user behaviour is performed. This is shown in  FIG. 3 . 
         [0059]    At step  100 , an indication has been received that an action which causes a node transition (e.g., clicking a URL link) has been performed. The node is then added to a path progress list at step  110 . It is determined at step  120  whether the user&#39;s goal has been achieved. Note, provision is made for the user to indicate this to the system. If the answer is no, then processing loops round. Once the user has indicated that they have achieved their goal, the complete path is stored in a completed paths list at step  130 . (The entries in the progress path may be removed). 
         [0060]    Modelling of user behaviour may continue for multiple users until the system receives an indication that it is no longer necessary to continue monitoring. The system will then have a list of completed paths that users have followed through the user interface. 
         [0061]    Processing is then performed to determine which of the paths through the user interface are “golden paths”; in other words, which paths are most frequently exercised by users ( FIG. 4 ). 
         [0062]    At step  200 , the first path in the completed paths list is accessed and the system progresses through the list of paths from top to bottom. It is determined whether this path has been seen before. If this is the first time the path has been seen, then the path is added to a list of previously seen paths and is marked as having been seen once before (step  220 ). Processing then loops round. 
         [0063]    If the path has been seen before, then the number of occurrences of the path is incremented by one in the previously seen paths list (step  230 ). Processing continues until the previously seen paths list contains a list of all paths modelled according to  FIG. 3  and the number of times a user has followed such a path. 
         [0064]    At step  250  the previously seen paths list is ordered according to the number of times each path has been followed. At step  260  the top x (system configured number) paths are selected as golden paths. 
         [0065]    The system then goes on to calculate a complexity value for each golden path ( FIG. 5 ). By way of example, the golden paths identified are as follows:
   1) URL 1 , URL 2 , URL 3 , ULR 2 , URL 4 ;   2) URL 1 , URL 2 , URL 3 ;   3) URL 1 , URL 5 , URL 6 , URL 5 , URL 1 , URL 2 ; and   4) URL 1 , URL 5 , URL 6 .   
 
         [0070]    In the example, there are four golden paths listed. At step  300  path  1  is accessed. At step  310 , each node identified in the path is located in the route map generated by the processing of  FIGS. 2   a  and  2   b.  The complexity for each node is then generated at step  320  using an algorithm such as: 
         [0000]      [ D   i +1]*[ B   i +1]*[ F   i +1] 
         [0071]    It should be appreciated that “+1” is used to avoid a situation where one of the values equates to 0 and thereby nullifies the whole algorithm. 1 is chosen for the sake of simplicity. Equally each value could be incremented by another number. Also, D i , B i  and F i  could be incremented by different values to give some more weight than others. 
         [0072]    Thus for URL  1 , the depth (D i ) is 0, breadth (B i ) 0; and the number of accumulated data fields (F i ) 0. Consequently the complexity for node URL 1  is 1. 
         [0073]    The complexity values for each node in path  1  are shown below: 
         [0000]    
       
         
               
               
               
             
               
               
               
             
           
               
                   
                   
               
               
                   
                 Node 
                 Complexity 
               
               
                   
                   
               
             
             
               
                   
               
             
          
           
               
                   
                 URL1 
                 1 
               
               
                   
                 URL2 
                 18 
               
               
                   
                 URL3 
                 60 
               
               
                   
                 URL4 
                 120 
               
               
                   
                   
               
             
          
         
       
     
         [0074]    It will be appreciated that URL 2  appears twice in path  1 , possibly because users are being sent the wrong way and then have to retrace their steps. There is no need to include URL 2  twice in the complexity calculations. 
         [0075]    Once the complexity for each individual node in a path has been calculated, then the complexity values can be summed at step  330  in order to determine the overall complexity for a path. Thus for path  1 , the total complexity value is: 
         [0000]      (1+18+60+18+120)=217. 
         [0076]    The complexity value is then associated with the current golden path. 
         [0077]    At step  350 , it is then determined whether there are any more golden paths and if so, the processing loops round. 
         [0078]    Once all the calculations are complete, the information stored will look as follows: 
         [0000]    
       
         
               
               
               
             
               
               
               
             
           
               
                   
                   
               
               
                   
                 Path 
                 Complexity 
               
               
                   
                   
               
             
             
               
                   
               
             
          
           
               
                   
                 1 
                 217 
               
               
                   
                 2 
                 79 
               
               
                   
                 3 
                 140 
               
               
                   
                 4 
                 97 
               
               
                   
                   
               
             
          
         
       
     
         [0079]    At step  360 , the paths are then ordered according to their complexity: 
         [0000]    
       
         
               
               
               
             
               
               
               
             
           
               
                   
                   
               
               
                   
                 Path 
                 Complexity 
               
               
                   
                   
               
             
             
               
                   
               
             
          
           
               
                   
                 1 
                 217 
               
               
                   
                 3 
                 140 
               
               
                   
                 4 
                 97 
               
               
                   
                 2 
                 79 
               
               
                   
                   
               
             
          
         
       
     
         [0080]    It will be appreciated that the paths are numbered according to the frequency with which they are followed. Thus the system has information about which paths are most frequently followed and which are the most complex. Naturally it would be sensible for nodes in the most frequently followed paths to be simplest. Thus at step  360 , if the y (system configured value) most frequently visited paths (e.g., 3) appear in the top z (system configured value; e.g., 2) in terms of complexity then the user is informed that this is an area of the user interface that requires work. Thus in this example, the nodes in paths  1  and  3  perhaps need some attention. This can be notified to a user interface-designer. This would seem to make sense, since it will be appreciated that in both paths the user has had to retrace their steps to reach their eventual end goal. This would seem to indicate that there is something leading users to follow the wrong route. 
         [0081]    Thus a system has been presented which enables a user interface designer to determine which paths in a user interface are most frequently exercised (“golden”) and also the complexity of such golden paths. The user interface designer can then take steps to simplify the more complex of the golden paths. 
         [0082]    It should be appreciated that the metrics used to calculate complexity are exemplary only. 
         [0083]      FIG. 9  illustrates the components involved in the first embodiment. System  705  comprises a route map generator  700  (processing of  FIGS. 2   a,    2   b  and  2   c ) for creating a conceptual route map of user interface  750  using route map database  740 ; a user behaviour modeller  710  (processing of  FIG. 3 ); a golden paths determiner  720  (processing of  FIG. 4 ); and a complexity calculator  730  (processing of  FIG. 5 ). 
         [0084]      FIGS. 6 ,  7  and  8  show the processing of the present invention in accordance with a second embodiment. In the first embodiment, golden or critical paths are those that are frequently exercised by users of the user interface. In the second embodiment, users identify “golden nodes” (critical nodes). A node is “golden” if it represents a goal desired by a user. The system then calculates the least complex path (route) to that golden node. Such a path is then classified as a “golden path” (critical path) to the golden node. It should be appreciated that, as with the first embodiment, a conceptual route map of the system is first created. Further, the complexity value of each node should be calculated at the same time as an entry for that node is added to the database. 
         [0085]    With reference to  FIG. 6 , an indication is received from a user that a goal has been achieved at step  400  (i.e., that a desired node has been reached). An identifier for the node (“golden node”) is then stored (step  410 ). The user assigns the node a weighting (scale 1-100) indicating how important a goal is at step  420 . A critical goal is given a weighting of 100. The process then tests for more goals (step  440 ) and loops round. 
         [0086]      FIG. 7  illustrates the determination of golden paths. At step  500 , a golden node is accessed. The least complex route to the golden node is then calculated. It will be appreciated that in the present example, there is only one direct route through the user-interface (i.e., without the user retracing their steps). The calculation of the least complex route is equivalent to the well-known and frequently discussed travelling salesman problem. It will therefore not be discussed in any more detail, suffice to say that the distance between two nodes in the travelling salesman problem is equivalent to the complexity value calculated for the destination node in this embodiment. 
         [0087]    At step  520 , the calculated route is stored as a golden path. It is then determined at step  530  whether there are any more golden nodes and the process loops round until all golden nodes have been processed. 
         [0088]    With reference to  FIG. 8 , the complexity of the golden paths is then calculated. At step  600 , a golden path is accessed. The complexity of the accessed path is calculated at step  610 . This calculation is performed in the same manner as the first embodiment. In other words, the complexity of each individual node in a path is calculated and then the complexity values are summed. 
         [0089]    At step  620  the weighting is applied to the overall complexity value using the algorithm:
       complexity*weighting
 
The calculated value is then associated with the golden path at step  630 . At  640 , processing loops round for all additional golden paths.
       
 
         [0091]    Once all golden paths have been processed, the listed golden paths are then ordered according to their weighted complexity at step  650 . By way of example, the golden paths may be listed in reverse order for this weighted complexity. Then the first w goals may be flagged as overly complex given their assigned weighting. 
         [0092]      FIG. 10  illustrates the components involved in the second embodiment. System  805  comprises a route map generator  800  (processing of  FIGS. 2   a,    2   b  and  2   c ) for creating a conceptual route map of user interface  850  using route map database  840 ; a golden nodes determiner  810  (processing of  FIG. 6 ); a golden paths determiner  820  (processing of  FIG. 7 ); and a complexity calculator  830  (processing of  FIG. 8 ). 
         [0093]    In the first embodiment, the route map of nodes is first created and then the complexity of those nodes is separately calculated. It should however be appreciated that this does not have to be the case. For example complexity values could be calculated alongside the generation of an entry for a node in the database. 
         [0094]    It will be apparent that the first embodiment uses weightings implicitly; that is by the number of times a user follows a certain path. The more times they follow a path, the higher the weighting of that goal. 
         [0095]    As previously discussed, a user-interface may comprise a more complex grid of nodes. This is shown with reference to  FIG. 11 . It can be seen from this  FIG. 11  that URL 3  has a transition back to URL 1  and also a further transition to URL 4 . This can therefore mean that it possible to reach a node via multiple routes. In the example, URL 4  can be reached from either URL 2  or from URL 3 . It will be appreciated that dependent upon the route taken, the complexity value associated with URL 4  could differ. For example, URL 4  has a depth of 3 when reached via URL 3  but a depth of only 2 when reached directly from URL 2 . 
         [0096]    To cope with this possibility, the complexity of each node is calculated at the same time as the route map is being generated. If for example, URL 4  is reached for the second time but this time via URL 3 , then the complexity value for node URL 4  is held in memory and compared with the previous complexity value for that node as held in the database. If the value in memory is lower than the value in the database, then a more efficient route to the node has been found. The database entry is updated with the current values for D tot , B tot  and F tot  and also the new complexity value. Conversely, if the complexity value held in memory is higher or equal to the equivalent value in the database for the node, then a more efficient route to the node has not been found and the algorithm should return to the calling node. The values for D tot , B tot  and F tot  are then reset to the equivalent values held for the calling node in the database. It should be appreciated that the transition from node URL 3  to node URL 1  is now considered to be a processed transition. 
         [0097]    By way of summary, golden (critical) paths are identified. A path is critical if it is one of the more frequently exercised paths or if it is the shortest path to a golden (critical) node.