Measuring productivity and quality in model-based design

• US 20070027652A1
• Filed: 07/27/2005
• Published: 02/01/2007
• Est. Priority Date: 07/27/2005
• Status: Active Grant

• Current Assignee: The MathWorks, Inc.
• Original Assignee: The MathWorks, Inc.
• Inventors: Hosagrahara, Arvind
• Granted Patent: US 7,613,589 B2
• Time in Patent Office: Days
• 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, said method comprises the steps of:

providing a modeling application;

identifying an activity for which a user wishes to measure effort, wherein said activity entails using said modeling application;

automatically gathering data related to usage of an input device related to said activity; and

storing the data related to the usage of said input device.

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

3. The method of claim 1 further comprises the step of:

measuring a time period for the user to complete said activity.

4. In a computational device, a method of automatically measuring productivity in a modeling environment, said method comprising the steps of:

identifying a task for which a user wishes to measure the productivity, wherein said task requires use of said modeling environment

providing a plurality of entities from said modeling environment for use with said task, wherein each entity has a type; and

automatically tracking usage of different types of entities while the user is working on said task.

5. The method of claim 4, wherein the modeling environment is a graphical modeling environment.

6. The method of claim 5, wherein said task comprises designing or modifying at least one of a block, a subsystem, and a model.

7. The method of claim 4 further comprises the step of:

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

calculating a weighted metric from said plurality of entities.

8. The method of claim 7, 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.

9. The method of claim 4 further comprises the step of:

setting a predicted time period required to complete said task.

10. The method of claim 4 further comprises the step of:

measuring time spent for the user to complete said task.

11. The method of claim 4 further comprises the step of:

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

12. In a computing device, a medium holding computer executable instructions for a method, said method comprises the steps of:

providing a modeling application;

identifying a task for which a user wishes to automatically measure productivity, wherein said task entails using said modeling application; and

evaluating effort put into said task by automatically tracking use of the input device.

13. The medium of claim 12, wherein said method further comprises the steps of:

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

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

14. The medium of claim 12, wherein said method further comprises the step of:

measuring time spent for the user to complete said task.

15. The medium of claim 12, wherein said method further comprises the step of:

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

16. In a modeling environment, a system for measuring productivity of a task, said system comprises:

a task to be completed in said modeling environment, wherein said task involves designing or modifying a model; and

a metric tool comprising

an input device tracker for automatically tracking use of an input device.

17. The system of claim 16, 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.

18. The system of claim 17, wherein the metric tool further comprises a timer for measuring time spent to complete said task.

19. The system of claim 18, 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.

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

a defect detection mechanism for detecting defects in said task.

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

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

22. The system of claim 16, 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.

23. In a modeling environment, a system for measuring productivity of a task, said system comprises:

a plurality of entities for use in said modeling environment;

a task to be completed in said modeling environment; and

a metric tool comprising an entity calculator automatically tracking usage of the plurality of entities in said task.

24. A productivity management method comprises the steps of:

tracking productivity data of a user within a managed group by measuring effort and time spent for each task, wherein effort is measured by a weighted content metric and usage of an input device;

storing said productivity data in a storage medium;

using said productivity data to predict time and effort required to complete a future task.

25. The method of claim 24 further comprises the step of:

determining bonus for said user using said productivity data.

26. The method of claim 24, wherein the effort is further measured by number of defects detected in each task.

27. The method of claim 26 further comprises the step of:

evaluating quality of each task with said number of defects detected; and

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

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

29. The method of claim 28, wherein the model characteristics are related to model complexity.

30. The method of claim 24 further comprises the step of:

generating a report of said productivity data.

31. A method of improving an application program comprises the steps of:

monitoring user activity with an application program by automatically tracking usage of an input device;

recording 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; and

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

32. The method of claim 31, wherein one of the plurality of tasks comprises waiting for the application program to compile a model.

33. The method of claim 32 further comprises the step of modifying the application program to speed up compilation of a model.

34. The method of claim 31, wherein the report indicates multiple appearance of a specific sequence of input activity.

35. The method of claim 31 further comprises the step of modifying the application program to eliminate the appearance of the specific sequence of input activity.

36. The method of claim 31, wherein the report indicates a performance issue.

37. The method of claim 36 further comprises the step of modifying the application program to eliminate the performance issue.

38. The method of claim 31 further comprises the step of improving the application program in response to the report.