Managing component coupling in an object-centric process implementation

• US 8,682,630 B2
• Filed: 06/15/2009
• Issued: 03/25/2014
• Est. Priority Date: 06/15/2009
• Status: Active Grant

• Current Assignee: Globalfoundries US Incorporated (GlobalFoundries, Inc.)
• Original Assignee: International Business Machines Corporation
• Inventors: Kuester, Jochen M., Wahler, Ksenia
• Primary Examiner(s): Augustin, Evens J
• Application Number:
  US12/484,326
• Publication Number:
  US 20100318958A1
• Time in Patent Office: 1,744 Days
• Field of Search: 707/609
• US Class Current: 703/13
• CPC Class Codes: G06F 8/10 Requirements analysis; Specification techniques
• CPC Class Codes: G06F 8/24 Object-oriented
• CPC Class Codes: G06F 8/60 Software deployment

Abstract

A method, system, and computer program product for managing component coupling in an object-centric process implementation are provided. The method includes, prior to deriving components that implement a centralized model: analyzing the centralized model to compute couplings within the centralized model resulting in a coupling metric; computing a predicted component model using objects, activities, and the coupling metric of the centralized model; and modifying control flow of the centralized model when a value of the coupling metric exceeds a pre-defined threshold value, re-analyzing the centralized model having the modified control flow, and repeating the computing, modifying and re-analyzing until the coupling metric is less than or equal to the pre-defined threshold. The method also includes implementing an object-centric process having component coupling that is derived from the centralized model when the value of the coupling metric is equal to or less than the pre-defined threshold value.

Claims

1. A method for managing component coupling in an object-centric process implementation, comprising:

prior to deriving components that implement a centralized model;

analyzing the centralized model with a processor;

computing couplings within the centralized model to define a coupling metric;

computing a predicted component model using objects, activities, and the coupling metric of the centralized model; and

modifying control flow of the centralized model when a value of the coupling metric exceeds a pre-defined threshold value, re-analyzing the centralized model having the modified control flow, and repeating the computing, modifying and re-analyzing until the coupling metric is less than or equal to the pre-defined threshold; and

implementing an object-centric process with the processor having component coupling that is derived from the centralized model when the value of the coupling metric is equal to or less than the pre-defined threshold value.

2. The method of claim 1, wherein the centralized model is an activity-centric process model supplied as a specification for a business process, and wherein analyzing the centralized model to compute couplings resulting in a coupling metric includes:

determining object dependencies by analyzing control flow between activities that change the state of objects in the centralized model;

determining expected coupling of object lifecycle components; and

identifying components determined to be highly coupled based upon the object dependencies determination.

3. The method of claim 1, wherein the coupling metric specifies a degree of coupling for object life cycle components.

4. The method of claim 1, wherein the coupling metric represents a ratio between an actual number of communication channels in the assembly model and the maximum possible number of communication channels between components in the assembly model.

5. The method of claim 1, further comprising:

identifying common process behaviors represented in workflow patterns and identifying a manner in which solutions for different patterns contribute to the overall coupling in the centralized model.

6. The method of claim 1, wherein analyzing the centralized model to compute couplings within the centralized model includes:

determining upstream and downstream control objects for each edge in the centralized model;

computing control handover object pairs based on the upstream and downstream control object determination;

computing decision notification object pairs based on the upstream and downstream control object determination; and

deriving the predicted component model from the control handover object pairs and the decision notification object pairs.

7. The method of claim 1, wherein control flow of the centralized model is modified using refactoring techniques.

8. The method of claim 1, further comprising deploying process software for managing component coupling in an object-centric process implementation, the deploying comprising:

installing the process software on at least one server;

identifying server addresses for users accessing the process software on the at least one server;

installing a proxy server if needed;

sending the process software to the at least one server and copying the process software to a file system of the at least one server;

sending the process software to at least a first client computer; and

executing the process software on the first client computer.

9. The method of claim 8, wherein the installing the process software further comprises:

determining if programs will reside on the at least one server when the process software is executed;

identifying the at least one server that will execute the process software; and

transferring the process software to storage for the at least one server.

10. The method of claim 8, wherein the sending the process software to the first client computer further includes having the at least one server automatically copy the process software to the first client computer, and running an installation program at the first client computer to install the process software on the first client computer.

11. The method of claim 8, wherein the sending the process software to the first client computer further comprises identifying a user and an address of the first client computer.

12. The method of claim 8, wherein the sending the process software to the first client computer includes sending the process software to at least one directory on the first client computer.

13. The method of claim 8, wherein the sending the process software to the first client computer includes sending the process software to the first client computer via e-mail.

14. The method of claim 1, further comprising integrating process software for managing component coupling in an object-centric process implementation, the integrating comprising:

determining if the process software will execute on at least one server;

identifying an address of the at least one server;

checking the at least one server for operating systems, applications, and version numbers for validation with the process software, and identifying any missing software applications for the at least one server that are required for integration;

updating the at least one server with respect to any operating system and application that is not validated for the process software, and providing any of the missing software applications for the at least one server required for the integration;

identifying client addresses and checking client computers for operating systems, applications, and version numbers for validation with the process software, and identifying any software applications missing from the client computers that are required for integration;

updating the client computers with respect to any operating system and application that is not validated for the process software, and providing any missing software application for the client computers required for the integration; and

installing the process software on the client computers and the at least one server.

15. The method of claim 1, further comprising on demand sharing of process software for managing component coupling in an object-centric process implementation, the on demand sharing comprising:

creating a transaction containing unique customer identification, requested service type, and service parameters;

sending the transaction to at least one main server;

querying the at least one main server about processing capacity associated with the at least one main server to help ensure availability of adequate resources for processing of the transaction; and

allocating additional processing capacity when additional capacity appears needed to process the transaction, the additional processing capacity being selected from the group of additional capacities consisting of central processing unit capacity, processor memory capacity, network bandwidth capacity, and storage capacity.

16. The method of claim 15, further comprising recording a plurality of usage measurements selected from the group of usage measurements consisting of network bandwidth, processor memory, storage, and central processing unit cycles.

17. The method of claim 16, further comprising:

summing the usage measurements;

acquiring at least one multiplicative value associated with the usage measurements and with unit costs; and

recording any such acquired multiplicative value as an on demand charge to a requesting customer.

18. The method of claim 17, further comprising at least one of:

posting the on demand charge on a web site if requested by the requesting customer; and

sending the on demand charge via e-mail to the requesting customer'"'"'s e-mail address.

19. The method of claim 17, further comprising charging the on demand charge to the requesting customer'"'"'s account if an account exists and if the requesting customer has selected a charge account payment method.

20. The method of claim 1, further comprising deploying, accessing, and executing process software for managing component coupling in an object-centric process implementation, the deploying, accessing, and executing process software implemented through a virtual private network, the method further comprising:

determining if a virtual private network is required;

checking for remote access to the virtual private network when it is required;

if the remote access does not exist, identifying a third party provider to provide secure, encrypted connections between a private network and remote users;

identifying the remote users; and

setting up a network access server operable for downloading and installing client software on desktop computers for remote access of the virtual private network;

accessing the process software;

transporting the process software to at least one remote user'"'"'s desktop computer; and

executing the process software on the at least one remote user'"'"'s desktop computer.

21. The method of claim 20, further comprising:

determining if the virtual private network has a site-to-site configuration for providing site-to-site access, and if the virtual private network is not so available, installing equipment required to establish a site-to-site configuration for the virtual private network;

installing large scale encryption into the site-to-site virtual private network; and

accessing the process software through the site-to-site configuration with large scale encryption.

22. A system for managing component coupling in an object-centric process implementation, comprising:

a computer processor; and

coupling predictor logic executing on the computer processor, the coupling predictor logic implementing;

prior to deriving components that implement a centralized model;

analyzing the centralized model with a processor;

computing couplings within the centralized model to define a coupling metric;

computing a predicted component model using objects, activities, and the coupling metric of the centralized model; and

modifying control flow of the centralized model when a value of the coupling metric exceeds a pre-defined threshold value, re-analyzing the centralized model having the modified control flow, and repeating the computing, modifying and re-analyzing until the coupling metric is less than or equal to the pre-defined threshold; and

implementing an object-centric process with the processor having component coupling that is derived from the centralized model when the value of the coupling metric is equal to or less than the pre-defined threshold value.

23. The system of claim 22, wherein the centralized model is an activity-centric process model supplied as a specification for a business process, and wherein analyzing the centralized model to compute couplings resulting in a coupling metric includes:

determining object dependencies by analyzing control flow between activities that change the state of objects in the centralized model;

determining expected coupling of object lifecycle components; and

identifying components determined to be highly coupled based upon the object dependencies determination.

24. The system of claim 22, wherein the coupling metric specifies a degree of coupling for object life cycle components.

25. The system of claim 22, wherein the coupling metric represents a ratio between an actual number of communication channels in the assembly model and the maximum possible number of communication channels between components in the assembly model.

26. The system of claim 22, wherein analyzing the centralized model to compute couplings within the centralized model includes:

determining upstream and downstream control objects for each edge in the centralized model;

computing control handover object pairs based on the upstream and downstream control object determination;

computing decision notification object pairs based on the upstream and downstream control object determination; and

deriving the predicted component model from the control handover object pairs and the decision notification object pairs.

27. A computer program product for managing component coupling in an object-centric process implementation, the computer program product including computer-readable program instructions embodied on a non-transitory computer storage medium, which when executed by a computer processor, cause the computer processor to implement:

prior to deriving components that implement a centralized model;

analyzing the centralized model with a processor;

computing couplings within the centralized model to define a coupling metric;

computing a predicted component model using objects, activities, and the coupling metric of the centralized model; and

modifying control flow of the centralized model when a value of the coupling metric exceeds a pre-defined threshold value, re-analyzing the centralized model having the modified control flow, and repeating the computing, modifying and re-analyzing until the coupling metric is less than or equal to the pre-defined threshold; and

implementing an object-centric process with the processor having component coupling that is derived from the centralized model when the value of the coupling metric is equal to or less than the pre-defined threshold value.

28. The computer program product of claim 27, wherein the centralized model is an activity-centric process model supplied as a specification for a business process, and wherein analyzing the centralized model to compute couplings resulting in a coupling metric includes:

determining object dependencies by analyzing control flow between activities that change the state of objects in the centralized model;

determining expected coupling of object lifecycle components; and

identifying components determined to be highly coupled based upon the object dependencies determination.

29. The computer program product of claim 27, wherein the coupling metric specifies a degree of coupling for object life cycle components.

30. The computer program product of claim 27, wherein the coupling metric represents a ratio between an actual number of communication channels in the assembly model and the maximum possible number of communication channels between components in the assembly model.

31. The computer program product of claim 27, wherein analyzing the centralized model to compute couplings within the centralized model includes:

determining upstream and downstream control objects for each edge in the centralized model;

computing control handover object pairs based on the upstream and downstream control object determination;

computing decision notification object pairs based on the upstream and downstream control object determination; and

deriving the predicted component model from the control handover object pairs and the decision notification object pairs.