COCOMO II Database Brad Clark Center for Software Engineering Annual Research Review March 11, 2002

University of Southern California Center for Software Engineering CSE USC March 2002Annual Research Review2 COCOMO II 2002 Calibration Quality of data impacts the quality of the model - and good data is hard to come by Collected data has challenges –Level of detail –Consistency (project size, scope, units, ratings) –Known relationships 100 data points being evaluated –Not all of these data can be used –Need more data

University of Southern California Center for Software Engineering CSE USC March 2002Annual Research Review3 Data Collection and Storage Data Collection –Paper collection form (most desirable because of detail) –From the USC COCOMO software tool estimation files Historical - whole project New data entered into a separate database from calibration data and evaluated. Data storage –Data is labeled with generic identifier –Stored in locked room –Access limited to 3 researchers Affiliate Organizations provide majority of data.

University of Southern California Center for Software Engineering CSE USC March 2002Annual Research Review4 Level of Detail More detail permits normalization of data –In addition to effort, request effort by phase and labor categories included in data –In addition to duration, request number of phases covered and lifecycle description –In addition to size, request types of languages, type of SLOC count, modified code characteristics –Intermediate values of scale / cost driver ratings

University of Southern California Center for Software Engineering CSE USC March 2002Annual Research Review5 Consistency of Data Project Size Effort Breadth and Depth Duration Breadth Process Maturity Rating(SF 5 ) Scale Driver Ratings (SF 1 -SF 4 ) Cost Driver Ratings (EM 1 -EM 17 ) COCOMO II Database

University of Southern California Center for Software Engineering CSE USC March 2002Annual Research Review6 Checking for Known Relationships ?

University of Southern California Center for Software Engineering CSE USC March 2002Annual Research Review7 Data Representation 111 Data fields across 5 tables –Additional data stored with effort, duration, size, scale and cost driver ratings Scale and Cost driver data stored symbolically –RELY value = H –RELY offset = 0.75

University of Southern California Center for Software Engineering CSE USC March 2002Annual Research Review8 Data Flow for Producing a Calibration Symbolic Data Symbol Values Uncalibrated Numeric Data Calibration Process Calibration Process New COCOMO II Values New COCOMO II Values Adjustment Coefficients COCOMO II Database Accuracy Evaluation Accuracy Evaluation Calibrated Numeric Data

University of Southern California Center for Software Engineering CSE USC March 2002Annual Research Review Calibration Data Status Currently screening data for incorporation into calibration database More project data needed –If you calibrate the COCOMO II model locally - would you consider letting us use your data to calibrate the scale / cost drivers? –If you have recently completed projects, would you consider filling out one of our data questionnaires? We can conduct a data collection interview over the phone. We plan to release calibration results by next COCOMO II forum (Fall 2002).

University of Southern California Center for Software Engineering CSE USC March 2002Annual Research Review10 For More Information Website – –Software for COCOMO II and COCOMO 81 models –Data collection form –Upcoming COCOMO events (Forum in Oct 2002) Book: –Software Cost Estimation with COCOMO II, 2000 Affiliates' Private Area