Time management and task completion and prediction software

• US 6,519,763 B1
• Filed: 03/29/1999
• Issued: 02/11/2003
• Est. Priority Date: 03/30/1998
• Status: Expired due to Term

• Current Assignee: Compuware Corporation (KKR & Co., Inc.)
• Original Assignee: Compuware Corporation (KKR & Co., Inc.)
• Inventors: Sivakumar, Arunachallam Sivaprakasam, Kaufer, Stephen, Palka, Thomas, Emrich, Marco A.
• Primary Examiner(s): Chaki, Kakali
• Assistant Examiner(s): DAS, CHAMELI
• Application Number:
  US09/277,732
• Time in Patent Office: 1,415 Days
• Field of Search: 717/1, 717/11, 717/3, 717/6, 717/8, 717/101, 717/100, 717/120, 717/121, 707/3, 707/302, 707/2, 707/10, 706/21, 706/45, 706/46, 706/10, 706/11, 706/12, 706/13, 706/16, 709/302
• US Class Current: 717/101
• CPC Class Codes: G06Q 10/109 Time management, e.g. calendars, reminders, meetings or time accounting

Abstract

A computer software application in the form of a software management and task completion and prediction apparatus by which project completion can be ascertained and management of a project can be maintained with a high efficiency and accuracy. The software application is a web-based application which enables users to proactively manage and accurately predict strategic software development and deliverables. This application and delivery management system comprises distributed data collectors, an application server and a browser interface. The data collectors automatically gather data already being generated by various tools within the organization, such as scheduling, defect tracking, requirements management and software quality tools. This data is constantly being collected and fed into the application server, thereby providing objective and updated information. New tools can be easily added without disrupting operations. The data collected is fed into the applications server which is the brain of the apparatus. The application server analyzes the data collected by the data collectors to generate a statistically significant probability curve. This curve is then compared to the original planned schedule of product delivery to determine if the project is meeting its targets. Based upon this comparison, the software application predicts a probable delivery date based upon the various inputs and variables from the development process. In addition, the application server also generate early warning alerts, as needed and indicated. At such time as the software apparatus identifies a potential problem, the alerts automatically inform the user, so as to mitigate a crisis and assist with resolution of the problem. The alerts are communicated to the designated user by e-mail.

Claims

1. A method for forecasting project completion, comprising:

(a) collecting data from a project development tool;

(b) managing said data;

(c) analyzing said data;

(d) processing said data through a project completion prediction tool;

(e) predicting a time interval for completion of said project wherein the step of processing said data includes assigning confidence level for a task; and

wherein the step of assigning said confidence level for said task building a probability curve for attaining a confidence level for completion of said task.

2. The method of claim 1, wherein the step building said probability curve includes analyzing resources assigned to said task.

3. The method of claim 2, wherein the step of analyzing resources includes adjusting a duration for completion of said task.

4. The method of claim 1, wherein the step of analyzing said data includes evaluating data from prior task completions.

5. The method of claim 1, wherein the step analyzing said data includes an analysis of said data over a plurality of iterations.

6. The method of claim 1, further comprising the step of applying said probability curve to a Monte Carlo simulation.

7. The method of claim 6, further comprising implementing a trend analysis for determining a potential change in completion of said task.

8. The method of claim 7, wherein said change is selected from the group consisting of:

incoming defects, quantity of tests created, quantity of regressions found, and combinations thereof.

9. The method of claim 7, further comprising the step of performing an alert analysis.

10. The method of claim 9, wherein the step of performing an alert analysis includes storing alert information in a database and comparing alert analysis results with alert identification values.

11. The method of claim 10, further comprising the step of generating an alert when said results meet said identification values.

12. The method of claim 1, wherein the step of reporting project completion analysis includes reports selected from the group consisting of:

data of requirements verified, data of requirements failed, data of requirements untested, current test results, history for a test case, a trend of new tests added versus the quantity of verified requirements, and a trend of time spent testing versus the number of verified requirements, and combinations thereof.

13. A computer system for predicting project completion, comprising:

a database to store project information;

a manager to collect data from a project development tool;

an analyzer to evaluate collected data; and

a tool to build a probability curve from a user defined confidence level for completion of a task.

14. The system of claim 13, further comprising an adjustment tool to change a duration of task completion.

15. The system of claim 14, wherein said change of duration is based upon a history of timely task completion of a prior task.

16. The system of claim 13, wherein said tool applies said analyzer over a plurality of iterations to build said probability curve.

17. The system of claim 13, further comprising a statistical tool to apply said curve to a Monte Carlo simulation.

18. The system of claim 17, wherein said statistical tool conducts a trend analysis to determine a change in completion of said task.

19. The system of claim 18, wherein said change is selected from the group consisting of:

incoming defects, quantity of tests created, quantity of regressions found, and combinations thereof.

20. The system of claim 18, further comprising an alert analyzer.

21. The system of claim 20, wherein said alert analyzer compares an alert analysis result to an alert identification value.

22. The system of claim 21, further comprising an alert generator to activate an alert when said analysis result meets said identification value.

23. An article comprising:

a computer-readable signal-bearing medium;

means in the medium for collecting data from a project development tool;

means in the medium for analyzing said data; and

means in the medium for building a probability curve illustrating confidence of an operator for completion of a task.

24. The article of claim 23, wherein the medium is selected from the group consisting of:

a recordable data storage medium and a modulated carrier signal.

25. The article of claim 23, wherein said data collecting means comprises a data collector to extract data from a project development tool.

26. The article of claim 23, further comprising a tool for changing a duration for completion of a task.

27. The article of claim 23, wherein said curve building means applies said data analyzing means over a plurality of iterations.

28. The article of claim 23, wherein said curve building means applies said data to a Monte Carlo simulation.

29. The article of claim 23, further comprising an alert analysis tool to activate an alert when an alert analysis result meets an alert identification value.