Abstract:
Software applications receive input data, perform processing of the received data and generate output. In one aspect the output is modification of data structures. The software application is tested with instances of input data that lead to various data modifications in the data structures. In another aspect, patterns are found in the modifications of the data structures, which are evaluated and analyzed for software vulnerabilities.

Description:
BACKGROUND 
     Enterprise software applications are typically complex and may consist of several abstraction layers and many different frameworks. An abstraction layer is a way of presenting a complex functionality by hiding implementations details. A software framework is another abstraction, which is a software platform used to develop applications. An advanced generation of software applications may utilize open source solutions with various levels of security. An open source solution is computer software that is available with source code. The source code and copyright are provided under a license that permits users to study, change, improve, and eventually distribute the software. However, often the security aspect is neglected, which causes unauthorized accesses or other performance problems such as error situations and application crashes. Tools for detecting potential security and performance vulnerabilities have become a crucial part in testing software applications. 
     Brute force algorithm is a general problem-solving technique, which includes identifying and systematically checking all possible candidates for solving a problem. Using a brute force algorithm to discover security and performance vulnerabilities of software applications is practically useless since the amount of time needed to analyze a software application it too much, even using the newest generation of computers. There is a need to apply some logic to analyze software application behavior in an optimized way. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The claims set forth the embodiments with particularity. The embodiments are illustrated by way of examples and not by way of limitation in the figures of the accompanying drawings in which like references indicate similar elements. The embodiments, together with its advantages, may be best understood from the following detailed description taken in conjunction with the accompanying drawings. 
         FIG. 1A  is a block diagram illustrating a software application and its incoming and outgoing data flows. 
         FIG. 1B  is a block diagram illustrating an embodiment of an evaluation framework for a software application with its incoming and outgoing data flows. 
         FIG. 2  is a block diagram illustrating an embodiment of a system for evaluation of software applications. 
         FIG. 3  is a block diagram illustrating an embodiment of an environment of an evaluation engine. 
         FIG. 4  is a class diagram illustrating an evaluation snapshot structure. 
         FIG. 5  is a flow diagram illustrating an embodiment of a method for evaluation of software applications. 
         FIG. 6  is flow diagram illustrating an embodiment of a method for determining patterns in generated data structures for evaluation of software applications. 
         FIG. 7  is a block diagram illustrating an embodiment of a computing environment in which the techniques described for evaluation of software applications can be implemented. 
     
    
    
     DETAILED DESCRIPTION 
     Embodiments of techniques for evaluation of software applications are described herein. In the following description, numerous specific details are set forth to provide a thorough understanding of the embodiments. One skilled in the relevant art will recognize, however, that the embodiments can be practiced without one or more of the specific details, or with other methods, components, materials, etc. In other instances, well-known structures, materials, or operations are not shown or described in detail. 
     Reference throughout this specification to “one embodiment”, “this embodiment” and similar phrases, means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one of the one or more embodiments. Thus, the appearances of these phrases in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. 
     A software application may be considered as a complex entity that has incoming and outgoing data flows.  FIG. 1A  represents such an application  100  with input data  110  and output data  120 . The incoming data flow, which is input data  110 , influences the internal state of the software application  100 , while, at some point, the software application  100  generates an outgoing data flow, such as the output data  120 . Thus, the process may be defined to include at least three major steps: receiving of incoming data, data processing, and generating outgoing data. During this process, the software application  100  may use some internal data structures  105  to store interim data. The content of the internal data structures  105  may depend on the input data  110  and software application logic. Data structures that are modified during the software application execution may be determined and then used to evaluate the software application steps using these data structures. The point where the execution of a request to the software application has reached (i.e., the breakpoint) together with variables (i.e., the data structures) that are changed during the software application execution define a program snapshot. A breakpoint identifies from an object and an instruction position within the bytecode of that object. Variables are mapped to data structures (e.g., a byte). 
     Some of the data structures may be data wrappers. Data wrappers are thus mapped to an input pattern. Referring to  FIG. 1B , by analyzing the changes within the internal data structures  105 , it may be possible to define evaluation snapshots that direct the software application  100  to essentially different states. An evaluation snapshot is a program snapshot. Because there is a direct dependency between the input data  110  and the internal data structures  105 , the derived evaluation snapshots for the internal data structures  105  may also be applied to the input data  110 . The evaluation snapshots defined in this way may be linked with parent-child relationship and an ordered graph (tree) of evaluation snapshots can be built. The ordered graph may be expanded with additional patterns (e.g., both input patterns and resulting internal data structures patterns) that lead the software application  100  to different states. Some of these software application states may be of interest and by following a simple traverse algorithm applied to the tree such program, a software application state may be reached. If an evaluation framework, such as evaluation framework  130  is used to analyze the internal data structures  105  and create an evaluation snapshot tree for the software application  100 , then data structure patterns  150 , and input data patterns  140  may be identified. The input data patterns  140  are dependent on the data structure patterns  150 . The identified data structure patterns  150  may be evaluated based on predefined rules that aim to discover critical scenarios for the software application  100 . 
       FIG. 2  is a block diagram illustrating an embodiment of a system  200  for evaluation of software applications. The system  200  includes an evaluation engine  205 , evaluated software application  210 , evaluation hook  215 , an in-flow data engine  220 , and an integrated development environment (IDE)  225 . 
     Following the algorithm mentioned above for evaluation of a program in reference to  FIGS. 1A and 1B , an oriented graph of evaluation snapshots for the software application  210  can be built. The edges of the graph may be executed software application steps and the nodes may be classified based on variables that are modified. The evaluation engine  205  includes evaluation snapshots  270  and controls an evaluation snapshots loop. The evaluation engine  205  also creates an evaluation snapshot graph. The modified variables may contain abstract data structures and when these data structures are accessed on some step, evaluation of some of the parent snapshots may be needed in order to determine the resulting snapshots. 
     The evaluation hook  215  is a module responsible for interacting with the evaluated software application  210 . The evaluation hook  215  may also monitor the “one step” behavior of the evaluated software application  210  and could process steps in both directions. The evaluation hook  215  may also participate in building software application snapshots. 
     The evaluated software application  210  may include software application code  230 , software application runtime  235 , data structures  240 , and data structure wrappers  245 . The software application code  230  may include bytecode  250  and source code  255 . The bytecode  250  may be used by the evaluation engine  205 . The source code  255  may be used by the IDE  225  by means of an evaluation plug-in  260 . In one embodiment, the source code  255  increases usability of the IDE  255 , and a potential problem may be visualized in the source code  255 . The software application runtime  235  may include all loaded classes and may communicate with the data structures  240  containing static and local variables. Data structure wrappers  245  may be used for data structures  240  that are mapped to patterns  275  in evaluation snapshots  270 . 
     The in-flow data engine  220  may simulate input data for the evaluated software application  210 . In one embodiment, the in-flow data engine  220  may generate test application examples based on an evaluation snapshot. 
     The IDE  225  and the evaluation plugin  260  may provide visual representation and management tools for the whole evaluation process. 
       FIG. 3  is a block diagram illustrating an embodiment of an environment  300  of an evaluation engine  305 . The evaluation engine  305  includes a management module  310 , evaluation snapshots  315 , and evaluation runtime loop  320 . The evaluation engine  305  may evaluate an evaluated software application  355  by using an evaluation book  345  and an input data engine  350 . The evaluation engine  305  may also use file system  325  to store and extract data necessary for the evaluation process. 
     The management module  310  may provide management activities such as suspend/resume against different instances of the evaluated software application  355 . In one embodiment, the management module  310  is also operable to provide a visualization of the evaluation process. 
     The evaluation runtime loop  320  may create an evaluation snapshot graph from evaluation snapshots  315 . The evaluation runtime loop  320 , in connection with the evaluation hook  345 , may be operable to monitor the behavior of the evaluated software application  355 . The evaluation runtime loop  320 , in communication with the input data engine  350 , may be operable to simulate input data for the evaluated software application  355 . The evaluation runtime loop  320  may use the file system  325  for performing backups of the evaluation snapshots  315 , storing progress reports  330 , and extracting configuration data such as evaluation configuration  340 . In one embodiment, the progress reports  330  are human readable. In one embodiment, the evaluation configuration  340  includes configuration rules. In one embodiment, the configuration rules may define prioritization of the evaluation snapshots. In yet another embodiment, the configuration rules may define evaluation snapshots to be excluded from the evaluation runtime loop  320 , which may be based on rules that define certain evaluation snapshots not being of interest for the evaluation process. 
       FIG. 4  is a class diagram illustrating an evaluation snapshot structure. An evaluation snapshot loop may starts from an initial evaluation snapshot  405 . When evaluation snapshot  410  is added to the graph, the evaluation snapshot  410  has a parent association  415  to an existing evaluation snapshot. Evaluation snapshot  410  may contain a program snapshot  420 . The program snapshot  420  may contain current breakpoint  425  and variables  430  changed during the software application execution. A breakpoint  425  identifies, from an object  435 , and an instruction position  440  within the byte code of that object. A variable  430  may be mapped to data structure  445 . Some of the data structures  445  may be data wrappers  450 . Data wrappers  450  may be mapped to input patterns  455 . 
       FIG. 5  is a flow diagram illustrating an embodiment of a method  500  for evaluating of software applications. At block  510 , input data is simulated for a software application. The software application may expect input data such as remote requests, application programming interface (API) calls, sent messages, etc. The input data may be input data  110  in  FIG. 1A  and  FIG. 1B . In one embodiment, the simulated data is a contiguous data stream. The simulated input data is received by the software application such as software application  100  and the software application may generate some data structures according to the internal logic of the software application. The generated data structures may be data structures  105  and data structures  240 . 
     At block  520 , patterns of the generated data structures are determined. There may be a direct dependency between the generated data structures and the input data, and the patterns of the generated data structures may indicate these dependencies. 
     The input data for a software application may be a countable set. For example, the input data may be a sequence of bytes that go through one communication channel connected with the software application. In some embodiments, the input data may be more complex, but it remains a countable set and the same algorithm may be used. In one embodiment, the bytes from the input data are enumerated with the number of their position within the sequence: 1, 2, . . . n. By having bytes: B 1 , B 2 , . . . , Bn, for each such byte being a part from given input data, the following states S(Bn) may be defined: 
     not_needed: the byte Bn is still not processed from the software application; 
     free_data: the byte Bn is read by the software application, but there is still no branching based on its value, which means there is no data structure changed or program operations performed based on this data; 
     value_set: the byte Bn (or some sequence of bytes Bn . . . Bn+m) has a predefined value set (e.g. [ab, ac, ad]) that directs the program to an exact branch; and 
     strict_value: the same as the value set, but containing a single value. In one embodiment, an input state Sn may be defined as a union of all state of bytes that are part from the input: Sn=[S(B 1 ), S(B 2 ), . . . ]. An evaluation snapshot can be mapped to such input state. Similarly to the input data, a countable set from all attributes/variables within the evaluated software application may be built. Attributes/variables are all “places” where some data could be stored, for example, static variable of classes, thread locals, instances of loaded classes, attributes of these instances, local variables of called methods, etc. All attributes are given unique names, which may be done using one or more initial points and then mentioning all attributes as a reference according to this initial point (e.g., root classloader→all_classloders→app_classX→classXYZ→attributeABC). The attributes within a given snapshot could have the following states: 
     not_changed: attribute An has never been changed from the evaluation snapshot; 
     changed_with_constant: attribute An has been changed to a constant (the value of the constant does not contain the value of an input byte); here, a boundary case may be when the value depends on the count of processed input bytes. 
     changed_with_formula: attribute An has been changed to value of a computable formula that contains input bytes; 
     changed_with_value_set: a value set that contains a formula or constant values; 
     data_structure_wrapper: data structure wrappers may be used when there is a repeatable data structure pattern (e.g., within the input data with a defined list of data structures and no need to have different snapshots one for one data structure, another with list of two data structures, etc,); it is enough to have one snapshot with a data structure wrapper. There is also a need to detect such repeatable data structures during the execution of the software application. 
     Turning back to  FIG. 5 , at block  530 , the determined patterns are evaluated based on predefined rules. In one embodiment, the patterns are checked for critical scenarios for the software application and critical instances of input data leading to the critical scenarios are defined. Critical scenarios for a software application include undesired situations and states of the executed software application. Undesired states may be error states, while undesired situation may be an unauthorized access to some data or resources. In one embodiment, the patterns are checked for possible system crashes and security faults. 
     At block  540 , critical instances of input data causing critical errors in the software application may be reported. 
       FIG. 6  is flow diagram illustrating an embodiment of a method  600  for determining patterns in generated data structures. At block  610 , a software evaluation snapshot is received. The point where an execution of a request to a software application reached (execution breakpoint) together with all variables (data structures) that are changed during the software application execution define a snapshot. The evaluation snapshot  610  is an initial snapshot such as initial snapshot  405 , from which an evaluation snapshot loop is started. 
     Then, at block  620 , a program step of the software application is executed. Only program steps that modify some data structures or evaluate a data structure are of interest. These are operations that change value (e.g. x=1) and operations that branch based on a value (e.g. if x=0 { . . . }). At block  630 , a resulting evaluation snapshot is collected. The resulting evaluation snapshot results from the executed program step at block  620 . 
     At decision block  640 , a check is performed to determine whether the resulting evaluation snapshot includes predefined exclusive patterns. The predefined exclusive patterns may be defined in configuration data such as evaluation configuration  340 . If a predefined exclusive pattern is identified in the resulting evaluation snapshot, then the method returns to block  620  to execute another program step. If a predefined exclusive pattern is not found in the resulting evaluation snapshot, then the method continues to decision block  650  to perform another check. At decision block  650 , the attributes, execution breakpoint, changed variables and input patterns of the resulting evaluation snapshot are checked to determine if they coincide with those of an existing snapshot from a set of existing evaluation snapshots. If these attributes do not coincide with those of an existing evaluation snapshot, then, at block  670 , the resulting evaluation snapshot is added to the set of existing evaluation snapshots and the method returns to block  620  to execute another program step. If the attributes, execution breakpoint, changed variables and input patterns of the resulting evaluation snapshot do coincide with those of an existing evaluation snapshot, then the method continues to block  660  to map the resulting evaluation snapshot to the existing evaluation snapshot and the method returns to block  620  to execute another program step. 
     An example of a simple software application that receives as an input text and generates as an output a word that repeats most in the text follows. The software application caches the output in order to analyze the searches later. The software application code may be in Java as presented in Table 1: 
     
       
         
               
             
               
               
             
               
               
             
               
               
             
               
               
             
               
               
             
               
               
             
               
               
             
               
               
             
               
               
             
               
               
             
               
               
             
               
               
             
               
               
             
               
               
             
               
             
           
               
                 TABLE 1 
               
               
                   
               
             
             
               
                 package example; 
               
               
                 import java.io.BufferedReader; 
               
               
                 import java.io.BufferedWriter; 
               
               
                 import java.io.ByteArrayInputStream; 
               
               
                 import java.io.IOException; 
               
               
                 import java.io.InputStream; 
               
               
                 import java.io.InputStreamReader; 
               
               
                 import java.io.OutputStream; 
               
               
                 import java.io.OutputStreamWriter; 
               
               
                 import java.util.ArrayList; 
               
               
                 import java.util.Hashtable; 
               
               
                 import java.util.Iterator; 
               
               
                 public class WordCounter { 
               
             
          
           
               
                   
                 public static ArrayList&lt;String&gt; mostRepeatedWords = new 
               
               
                   
                 ArrayList&lt;String&gt;( ); 
               
               
                   
                 public void mostRepeated(InputStream in, OutputStream out) throws 
               
               
                   
                 IOException { 
               
             
          
           
               
                   
                 BufferedReader reader = new BufferedReader(new 
               
               
                   
                 InputStreamReader(in)); 
               
               
                   
                 String line = reader.readLine( ); 
               
               
                   
                 String[ ] words = line.split(“\\W”); 
               
               
                   
                 Hashtable&lt;String, Integer&gt; wordCountTable = new 
               
               
                   
                 Hashtable&lt;String, Integer&gt;( ); 
               
               
                   
                 for (String word : words) { 
               
             
          
           
               
                   
                 Integer count = wordCountTable.get(word); 
               
               
                   
                 if (count == null) { 
               
             
          
           
               
                   
                 count = new Integer(1); 
               
             
          
           
               
                   
                 } else { 
               
             
          
           
               
                   
                 count = new Integer(count.intValue( ) + 1); 
               
             
          
           
               
                   
                 } 
               
             
          
           
               
                   
                 wordCountTable.put(word, count); 
               
             
          
           
               
                   
                 } 
               
               
                   
                 reader.close( ); 
               
               
                   
                 String result = “”; 
               
               
                   
                 int count = 0; 
               
               
                   
                 Iterator&lt;String&gt; wordIterator = 
               
               
                   
                 wordCountTable.keySet( ).iterator( ); 
               
               
                   
                 while (wordIterator.hasNext( )) { 
               
             
          
           
               
                   
                 String word = wordIterator.next( ); 
               
               
                   
                 int wordCount = wordCountTable.get(word).intValue( ); 
               
               
                   
                 if (wordCount &gt; count) { 
               
             
          
           
               
                   
                 result = word; 
               
               
                   
                 count = wordCount; 
               
             
          
           
               
                   
                 } 
               
             
          
           
               
                   
                 } 
               
               
                   
                 BufferedWriter writer = new BufferedWriter(new 
               
               
                   
                 OutputStreamWriter(out)); 
               
               
                   
                 writer.write(result); 
               
               
                   
                 writer.newLine( ); 
               
               
                   
                 writer.close( ); 
               
               
                   
                 mostRepeatedWords.add(result); 
               
             
          
           
               
                   
                 } 
               
             
          
           
               
                 } 
               
               
                   
               
             
          
         
       
     
     The snapshot presented in Table 2 is generated at the end of its evaluation: 
     
       
         
               
             
               
               
             
               
               
             
               
               
             
               
               
             
               
               
             
               
               
             
               
               
             
               
               
             
               
               
             
               
               
             
               
               
             
               
               
             
               
               
             
               
               
             
               
               
             
               
               
             
               
             
           
               
                 TABLE 2 
               
               
                   
               
             
             
               
                 SNAPSHOT: { 
               
             
          
           
               
                   
                 OBJECT_INSTANCES: [ 
               
               
                   
                 { INSTANCE_NUMBER: 1 
               
             
          
           
               
                   
                 TYPE: WordCounter.class 
               
               
                   
                 LOCAL_VARIABLES: [ 
               
             
          
           
               
                   
                 { NAME: reader, TYPE: BufferedReader.class, ... }; 
               
               
                   
                 { NAME: line, 
               
             
          
           
               
                   
                 TYPE: String; 
               
             
          
           
               
                   
                 VALUE: { TYPE: 
               
               
                   
                 RESTRICTED_INPUT_STREAM, 
               
             
          
           
               
                   
                 SIZE: UNRESTRICTED, 
               
               
                   
                 RESTRICTEDCHARSET: [‘\n’]; 
               
             
          
           
               
                   
                 } 
               
             
          
           
               
                   
                 } 
               
               
                   
                 ... 
               
             
          
           
               
                   
                 ] 
               
             
          
           
               
                   
                 } ] 
               
               
                   
                 STATIC_STRUCTURES: [ 
               
               
                   
                  { NAME: mostRepeatedWords 
               
             
          
           
               
                   
                 TYPE: ArrayList.class 
               
               
                   
                 VALUE: [ 
               
               
                   
                 { TYPE: String.class 
               
             
          
           
               
                   
                 VALUE: { TYPE: 
               
               
                   
                 RESTRICTED_INPUT_STREAM, 
               
             
          
           
               
                   
                 SIZE: UNRESTRICTED, 
               
               
                   
                 RESTRICTEDCHARSET: [‘\n’, ‘ ’] 
               
             
          
           
               
                   
                 } 
               
             
          
           
               
                   
                 } ] 
               
             
          
           
               
                   
                  } 
               
               
                   
                 ] 
               
               
                   
                 OUTPUT: { ... } 
               
               
                   
                 ... 
               
             
          
           
               
                 } 
               
               
                   
               
             
          
         
       
     
     Other snapshots are also generated but they are not of interest for the checks performed below. There may be a predefined set of rules (checks) that are executed against that snapshot. Two possible checks may be: 
     Check 1: If OBJECT_INSTANCES contain some VARIABLE with VALUE having UNRESTRICTED SIZE, then this is an indicator for possible out-of-memory problem. This rule may be used to discover a situation when there is no limitation for buffering the data coming from the input data stream within the memory. In that situation, a variable with unrestricted size is sought. 
     In the example above: the check discovers variable “line”, Then, any lone: enough input data stream that does not contain ‘\n’ causes an out-of-memory problem for the software application (see restrictions on variable&#39;s value). 
     Check 2: If STATIC_STRUCTURES contain some VALUE from type RESTRICTED_INPUT_STREAM that is an indicator for possible out-of-memory problem. 
     This rule may be used to discover a situation when data coming from the input data stream is stored within the memory in static objects. This situation could lead to an out-of-memory problem as the incoming data request could be repeated many times and, each time, the memory used by the program increases. 
     In the example above: the check discovers variable “mostRepeatedWords”. Then, any call to the software application causes an increase of the used memory. After multiple calls, the out-of-memory problem appears. 
     Some embodiments may include the above-described methods being, written as one or more software components. These components, and the functionality associated with each, may be used by client, server, distributed, or peer computer systems. These components may be written in a computer language corresponding to one or more programming languages such as, functional, declarative, procedural, object-oriented, lower level languages and the like. They may be linked to other components via various application programming interfaces and then compiled into one complete application for a server or a client. Alternatively, the components maybe implemented in server and client applications. Further, these components may be linked together via various distributed programming protocols. Some example embodiments may include remote procedure calls being used to implement one or more of these components across a distributed programming environment. For example, a logic level may reside on a first computer system that is located remotely from a second computer system containing an interface level (e.g., a graphical user interface). These first and second computer systems can be configured in a server-client, peer-to-peer, or some other configuration. The clients can vary in complexity from mobile and handheld devices, to thin clients and on to thick clients or even other servers. 
     The above-illustrated software components are tangibly stored on a computer readable storage medium as instructions. The term “computer readable storage medium” should be taken to include a single medium or multiple media that stores one or more sets of instructions. The term “computer readable storage medium” should be taken to include any physical article that is capable of undergoing a set of physical changes to physically store, encode, or otherwise carry a set of instructions for execution by a computer system which causes the computer system to perform any of the methods or process steps described, represented, or illustrated herein. A computer readable storage medium may be a non-transitory computer readable storage medium. Examples of non-transitory computer readable storage media include, but are not limited to: magnetic media, such as hard disks, floppy disks, and magnetic tape; optical media such as CD-ROMs, DVDs and holographic devices; magneto-optical media; and hardware devices that are specially configured to store and execute, such as application-specific integrated circuits (“ASICs”), programmable logic devices (“PLDs”) and ROM and RAM devices. Examples of computer readable instructions include machine code, such as produced by a compiler, and files containing higher-level code that are executed by a computer using an interpreter. For example, an embodiment may be implemented using Java, C++, or other object-oriented programming language and development tools. Another embodiment may be implemented in hard-wired circuitry in place of, or in combination with machine readable software instructions. 
       FIG. 7  is a block diagram of an exemplary computer system  700 . The computer system  700  includes a processor  705  that executes software instructions or code stored on a computer readable storage medium  755  to perform the above-illustrated methods. The computer system  700  includes a media reader  740  to read the instructions from the computer readable storage medium  755  and store the instructions in storage  710  or in random access memory (RAM)  715 . The storage  710  provides a large space for keeping static data where at least some instructions could be stored for later execution. The stored instructions may be further compiled to generate other representations of the instructions and dynamically stored in the RAM  715 . The processor  705  reads instructions from the RAM  715  and performs actions as instructed. According to one embodiment, the computer system  700  further includes an output device  725  (e.g., a display) to provide at least some of the results of the execution as output including, but not limited to, visual information to users and an input device  730  to provide a user or another device with means for entering data and/or otherwise interact with the computer system  700 . Each of these output devices  725  and input devices  730  could be joined by one or more additional peripherals to further expand the capabilities of the computer system  700 . A network communicator  735  may be provided to connect the computer system  700  to a network  750  and in turn to other devices connected to the network  750  including other clients, servers, data stores, and interfaces, for instance. The modules of the computer system  700  are interconnected via a bus  745 . Computer system  700  includes a data source interface  720  to access data source  760 . The data source  760  can be accessed via one or more abstraction layers implemented in hardware or software. For example, the data source  760  may be accessed by network  750 . In some embodiments the data source  760  may be accessed via an abstraction layer, such as, a semantic layer. 
     A data source is an information resource. Data sources include sources of data that enable data storage and retrieval. Data sources may include databases, such as, relational, transactional, hierarchical, multi-dimensional (e.g., OLAP), object oriented databases, and the like. Further data sources include tabular data (e.g., spreadsheets, delimited text files), data tagged with a markup language (e.g., XML data), transactional data, unstructured data (e.g., text files, screen scrapings), hierarchical data (e.g., data in a file system, XML data), files, a plurality of reports, and any other data source accessible through an established protocol, such as, Open DataBase Connectivity (ODBC), produced by an underlying software system (e.g., ERP system), and the like. Data sources may also include a data source where the data is not tangibly stored or otherwise ephemeral such as data streams, broadcast data, and the like. These data sources can include associated data foundations, semantic layers, management systems, security systems and so on. 
     In the above description, numerous specific details are set forth to provide a thorough understanding of embodiments. One skilled in the relevant art will recognize, however that the embodiments can be practiced without one or more of the specific details or with other methods, components, techniques, etc. in other instances, well-known operations or structures are not shown or described in details. 
     Although the processes illustrated and described herein include series of steps, it will be appreciated that the different embodiments are not limited by the illustrated ordering of steps, as some steps may occur in different orders, some concurrently with other steps apart from that shown and described herein. In addition, not all illustrated steps may be required to implement a methodology in accordance with the one or more embodiments. Moreover, it will be appreciated that the processes may be implemented in association with the apparatus and systems illustrated and described herein as well as in association with other systems not illustrated. 
     The above descriptions and illustrations of embodiments, including what is described in the Abstract, is not intended to be exhaustive or to limit the one or more embodiments to the precise forms disclosed. While specific embodiments of, and examples for, the one or more embodiments are described herein for illustrative purposes, various equivalent modifications are possible within the scope, as those skilled in the relevant art will recognize. These modifications can be made in light of the above detailed description. Rather, the scope is to be determined by the following claims, which are to be interpreted in accordance with established doctrines of claim construction.