Measuring productivity and quality in model-based design

• US 7,613,589 B2
• Filed: 07/27/2005
• Issued: 11/03/2009
• Est. Priority Date: 07/27/2005
• Status: Active Grant

• Current Assignee: The MathWorks, Inc.
• Original Assignee: The MathWorks, Inc.
• Inventors: Hosagrahara, Arvind Suresh
• Primary Examiner(s): Dunn; Drew A
• Assistant Examiner(s): VO, HIEN XUAN
• Application Number:
  US11/191,344
• Publication Number:
  US 20070027652A1
• Time in Patent Office: 1,560 Days
• Field of Search: 702/182, 702/183, 707 4- 6, 706 45- 56, 709/223, 715/762, 715/771
• US Class Current: 702/182
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202

Abstract

Methods and systems for automatically measuring productivity and quality of model-based designs are disclosed. The present invention uses model contents, time spent, and input activities to measure effort put in a task and quality of the task. Defects and other model characteristics are tracked and used as a criterion to determine quality of a model-based design. The present invention allows for predicting resources required for a future task and for providing guidelines to improve usability of an application.

Claims

1. A method for automatically measuring effort in working on a model, the method comprising:

providing a graphical modeling application using a computing device;

identifying an activity for which a user wishes to measure effort, the activity comprising designing or modifying at least one of a block, a subsystem, and said model using said modeling application;

measuring, using the computing device, a time period for the user to complete the activity;

automatically gathering, using the computing device, data related to usage of an input device related to the activity;

storing the data related to the usage of the input device in a storage device; and

determining, using the computing device, the effort in working on the model based on the time period and the data.

2. The method of claim 1, wherein the input device is one of a mouse and a keyboard.

3. In a computing device, a method of automatically measuring productivity in a graphical modeling environment, the method comprising:

identifying a task for which a user wishes to measure the productivity, the task comprising designing or modifying at least one of a block, a subsystem, and a model using the modeling environment;

providing, using the computing device, a plurality of entities from the modeling environment for use with the task, wherein each entity has a type;

measuring, using the computing device, time spent for the user to complete the task;

automatically tracking and storing usage of different types of entities, using the computing device, while the user is working on the task; and

determining, using the computing device, the productivity in the graphical modeling environment based on the usage of the different types of entities and the time.

4. The method of claim 3, further comprising:

assigning, using the computing device, a weight for each type of said plurality of entities;

calculating, using the computing device, a weighted metric from said plurality of entities.

5. The method of claim 4, wherein the weight for a type of said plurality of entities is related to complexity of building and configuring said type of said plurality of entities.

6. The method of claim 3, further comprising:

setting, using the computing device, a predicted time period required to complete said task.

7. The method of claim 3, further comprising:

detecting, using the computing device, at least one of a defect and model characteristic in said task.

8. In a computing device, a computer-readable medium holding computer executable instructions, the instructions when executed causing a computer to perform:

providing a graphical modeling application;

identifying a task for which a user wishes to automatically measure productivity, the task comprising designing or modifying at least one of a block, a subsystem, and a model using the modeling application;

assigning a weight for each type of a plurality of entities provided from the modeling application for use with the task and calculating a weighted content metric from the plurality of entities; and

evaluating effort put into the task from the weighted content metric and by automatically tracking use of the input device.

9. The medium of claim 8, wherein said medium further comprises instructions that when executed cause a computer to perform:

providing a plurality of entities for use with said task; and

assigning a weight for each type of said plurality of entities.

10. The medium of claim 8, wherein said medium further comprises instructions that when executed cause a computer to perform:

measuring time spent for the user to complete said task.

11. The medium of claim 8, wherein said medium further comprises instructions that when executed cause a computer to perform:

detecting at least one of a defect and a model characteristic in said task.

12. In a graphical modeling environment, a system for measuring productivity of a task, the system comprising:

an input device; and

a processor configured to process;

a task to be completed in said modeling environment, the task involving designing or modifying one of a block, a subsystem, and a model, and

a metric tool comprising;

an input device tracker for automatically tracking use of the input device,

a productivity evaluator for determining the productivity of the task based on the use of the input device, and

a detector for detecting a defect or a model characteristic in the task.

13. The system of claim 12, wherein the metric tool further comprises a weighted content calculator that is capable of normalizing contents created during said task with an assigned weight for each type of contents.

14. The system of claim 13, wherein the metric tool further comprises a timer for measuring time spent to complete said task.

15. The system of claim 14, wherein the metric tool further comprises:

a report generator for reporting metrics found by at least one of said timer, said input device tracker, and said weighted content calculator.

16. The system of claim 12, wherein the metric tool further comprises:

a defect detection mechanism for detecting defects in said task.

17. The system of claim 12, wherein the metric tool further comprises:

a model characteristic detection mechanism for detecting model complexity in said model.

18. The system of claim 12, wherein the metric tool is on a server and the input device is on a client and the modeling environment is remotely accessed by a user on the client.

19. In a graphical modeling environment, a system for measuring productivity of a task, the system comprising:

a processor configured to process;

a plurality of entities for use in the modeling environment;

a task to be completed in the modeling environment, the task comprising designing or modifying at least one of a block, a subsystem, and a model;

a time predictor for setting a predicted time period required to complete the task; and

a metric tool comprising an entity calculator automatically tracking usage of the plurality of entities in the task and a productivity evaluator determining the productivity of the task based on the usage of the plurality of entities.

20. A productivity management method comprising:

tracking, using a computing device, productivity data of a user within a managed group by measuring effort and time spent for each task, the each task comprising designing or modifying at least one of a block, a subsystem, and a model in a graphical modeling environment, and the effort being measured by a weighted content metric and usage of an input device;

assigning, using the computing device, a weight for each type of a plurality of entities provided from the modeling environment for use with the each task and calculating the weighted content metric from the plurality of entities;

storing the productivity data in a storage device; and

predicting time and effort required to complete a future task, using the computing device, based on the productivity data.

21. The method of claim 20, further comprising:

determining, using the computing device, a bonus for said user using said productivity data.

22. The method of claim 20, wherein the effort is further measured by number of defects detected in each task.

23. The method of claim 22, further comprising:

evaluating, using the computing device, quality of each task with said number of defects detected; and

evaluating, using the computing device, at least one of productivity and effort of each task with the measured effort and time spent.

24. The method of claim 20, wherein the effort is further measured by model characteristics detected in each task.

25. The method of claim 24, wherein the model characteristics are related to model complexity.

26. The method of claim 20, further comprising:

generating, using the computing device, a report of said productivity data.

27. A method of improving an application program comprising:

monitoring, using a computing device, user activity with an application program by automatically tracking usage of an input device;

recording, using the computing device, time spent on a plurality of tasks, wherein the plurality of tasks comprises at least one of an application program task performed by the application program and a user task performed by the user, the user task comprising designing or modifying at least one of a block, a subsystem, and a model;

determining, using the computing device, effort in working on the plurality of tasks based on the time spent; and

generating, using the computing device, a report including the time spent on the plurality of tasks and the usage of the input device.

28. The method of claim 27, wherein one of the plurality of tasks comprises waiting for the application program to compile a model.

29. The method of claim 28, further comprising:

modifying, using the computing device, the application program to speed up compilation of a model.

30. The method of claim 27, wherein the report indicates multiple appearance of a specific sequence of input activity.

31. The method of claim 27, further comprising:

modifying, using the computing device, the application program to eliminate the appearance of the specific sequence of input activity.

32. The method of claim 27, wherein the report indicates a performance issue.

33. The method of claim 32, further comprising:

modifying, using the computing device, the application program to eliminate the performance issue.

34. The method of claim 31, further comprising:

improving, using the computing device, the application program in response to the report.