Abstract: An ETL system for extracting transactional data from a plurality of source machines is provided. The ETL system includes a data query module configured to provide an interface to enable a data analyst to define an input query to extract transactional data, which is present on a plurality of source machines. The source machines form a multi-tenant system and each source machine is identified by a unique tenant identifier. The system also includes a query parsing module coupled to the data query module and configured to deconstruct the input query to create a tree structure. The tree structure comprises a plurality of distinct queries. The system further includes a data extraction module coupled to the query parsing module and configured to extract transactional data based on the distinct queries and copy the transactional data to a destination system wherein the transactional data comprises a plurality of data types.

Abstract: A report generation system is provided. The system includes a database configured to store customer data and transactional data for a plurality of customers of a client. The report generation system also includes a query generator accessible by an analyst to define one or more report queries using a plurality of input variables. The query generator is configured to deconstruct the one or more report queries to create a query tree structure. The query tree structure includes a plurality of distinct report queries. The report generation system further includes a report processor configured to process the customer data and the transactional data based on the plurality of distinct report queries and values of input variables to generate one or more reports with output data. The report processor includes a report design module accessible by the analyst to define a plurality of data visualization formats.

Abstract: An ETL system for extracting transactional data from a plurality of source machines is provided. The ETL system includes a data query module configured to provide an interface to enable a data analyst to define an input query to extract transactional data, which is present on a plurality of source machines. The source machines form a multi-tenant system and each source machine is identified by a unique tenant identifier. The system also includes a query parsing module coupled to the data query module and configured to deconstruct the input query to create a tree structure. The tree structure comprises a plurality of distinct queries. The system further includes a data extraction module coupled to the query parsing module and configured to extract transactional data based on the distinct queries and copy the transactional data to a destination system wherein the transactional data comprises a plurality of data types.

Abstract: An in-store customer engagement system is provided. The system includes a retail processing device located in a store, wherein the retail processing device is configured to process transactions of a customer. The system also includes a customer registration device configured to receive customer data from the customer and to register the customer with a customer relationship management (CRM) application of the store. The system further includes a first server communicatively coupled to the retail processing device and to the customer registration device wherein the first server is configured to transmit the customer data to the retail processing device upon registration of the customer with the customer relationship management application.

Abstract: A system for managing customer engagements of a client is provided. The system includes an event tracker configured to track at least one of transactional data and customer profile data of a plurality of customers of the client and a customizable rule engine configured to dynamically generate one or more customized rules using parameters associated with at least one of the transactional data and the customer profile data. The system also includes a customer event management module coupled to the event tracker and to the customizable rule engine, wherein the customer event management module is configured to analyze the transactional data and the d customer profile data for each customer to select one or more applicable rules and to apply the selected rules to generate one or more customized offers for the respective customer. The system further includes a customer engagement module configured to execute instructions for transmitting the one or more customized offers to the respective customer.

Abstract: Bounding resource consumption of code that processes recursive data structures and collections includes making use of quantitative functions (based on user input) that are associated with a tuple of data-structures and whose semantics is specified by describing the effect of various data-structure methods on the relevant quantitative functions. Counter variables are incorporated into source code to count loop iterations (and number of recursive procedure call invocations). Relevant quantitative functions are incorporated into the source code to allow computation of invariants (and hence bounds) on the incorporated counter variables in terms of the quantitative functions.

Abstract: Bounding resource consumption of code using abstract interpretation includes a static analysis to estimate a code's resource consumption in terms of units of resources utilized at any point during execution, expressed as a function of its scalar inputs. An instrumentation mechanism and an abstract interpretation mechanism are employed to compute bounds on the code resource consumption. The instrumentation mechanism includes incorporating one or more counter variables in the source code to count the number of loop iterations and recursive procedure call invocations. The abstract interpretation mechanism includes computing invariants on the instrumented counter variables and scalar program variables to obtain bounds on the number of loop iterations and recursive procedure call invocations, which are then composed together to obtain resource bounds for the entire program.

Abstract: A mobile phone based mobile customer relationship and loyalty servicing system and method thereof which involves media such as SMS, e-mail, instant messenger or a notification to a mobile application or website as well to identify and communicate with the customer in a customer friendly manner. It includes a unique code based operation and special feature of instant analytics for the customer, points/voucher validation and redemption, incentivized referral program, integrated campaigns and the like right at the POS terminal at client outlet enabling real time integration, analytics and communication. The system involving Mobile phones/like mobile operative devices of the end users/customers, at least one client component at the retail/sales outlets and a server component comprising an MCRLP main server system for operative connection to said one client component for customer relationship and loyalty servicing. The Customer interacts with the system and his behavior is modeled.

Abstract: The method executes the application and if there are no errors from the execution of the application, the method ends. If errors exist, the errors are collected from the execution of the application in an error report. Labeled application paths are created by adding a unique label to individual application paths where the application paths are individual loops and individual functions in the application. An analysis is created of the labeled application paths by executing the application with the labeled paths, reviewing the error report for data related to the labels and if an error is sufficiently related to application paths with labels, storing the path that created the errors in a report. If an error is not sufficient related to the application path with labels, the method is repeated by the creating the analysis again by substituting additional application paths for the application paths.

Abstract: The method executes the application and if there are no errors from the execution of the application, the method ends. If errors exist, the errors are collected from the execution of the application in an error report. Labeled application paths are created by adding a unique label to individual application paths where the application paths are individual loops and individual functions in the application. An analysis is created of the labeled application paths by executing the application with the labeled paths, reviewing the error report for data related to the labels and if an error is sufficiently related to application paths with labels, storing the path that created the errors in a report. If an error is not sufficient related to the application path with labels, the method is repeated by the creating the analysis again by substituting additional application paths for the application paths.

Abstract: Bounding resource consumption of code that processes recursive data structures and collections includes making use of quantitative functions (based on user input) that are associated with a tuple of data-structures and whose semantics is specified by describing the effect of various data-structure methods on the relevant quantitative functions. Counter variables are incorporated into source code to count loop iterations (and number of recursive procedure call invocations). Relevant quantitative functions are incorporated into the source code to allow computation of invariants (and hence bounds) on the incorporated counter variables in terms of the quantitative functions.

Abstract: During software development, both before and after release, information may be collected and stored that may provide insight to developers as a generalized service. For example, data from past debugging sessions, source code in various repositories, bug repositories, discussion groups, and various documents may provide relevant information for software developers to fix current problems when this information is coherently matched with the problem. Using various sources, a system may mine the stored data to give the current developer information related to past code development, and reveal why the code changed throughout previous development. Using sophisticated analyses to identify similar code patterns across multiple large software projects, discovering patterns in normal and abnormal uses of particular software interfaces, and employing other mining techniques, a developer may find domain-specific information to facilitate ongoing software development.

Abstract: An automated task centered collaboration technique is described that significantly lowers the technological entry barrier for the development and deployment of a broad class of collaborative applications, which are termed Task Centered Collaboration (TCC) applications. TCC applications facilitate the processing of a large number of work items, or tasks, by people working independently or in small, synchronously collaborating groups. The technique also provides a mechanism for the study of computer mediated communication and human-computer interactions for this class of applications. The technique creates an abstraction applicable to the broad class of TCC applications, which enables the factoring out of significant portions of the application into a common infrastructure.

Abstract: Bounding resource consumption of code using abstract interpretation includes a static analysis to estimate a code's resource consumption in terms of units of resources utilized at any point during execution, expressed as a function of its scalar inputs. An instrumentation mechanism and an abstract interpretation mechanism are employed to compute bounds on the code resource consumption. The instrumentation mechanism includes incorporating one or more counter variables in the source code to count the number of loop iterations and recursive procedure call invocations. The abstract interpretation mechanism includes computing invariants on the instrumented counter variables and scalar program variables to obtain bounds on the number of loop iterations and recursive procedure call invocations, which are then composed together to obtain resource bounds for the entire program.