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                                Please mark your calendars!

        Improving Software Development Process and Product Management 
                            with Software Project Telemetry

                                           Qin  Zhang
                                Wednesday, August 30, 2:00pm
                                            POST 302


Software development is slow, expensive and error prone, often resulting
in products with a large number of defects which cause serious problems
in usability, reliability, and performance. To combat this problem,
software measurement provides a systematic and empirically-guided
approach to control and improve software development processes and final
products. However, due to the high cost associated with “metrics
collection” and difficulties in “metrics decision-making”, measurement
is not widely adopted by software organizations.

This dissertation proposes a novel metrics-based program called
“software project telemetry” to address the problems. It uses software
sensors to collect metrics automatically and unobtrusively. It employs a
domain-specific language to represent telemetry trends in software
product and process metrics. Project management and process improvement
decisions are made by detecting changes in telemetry trends and
comparing trends between different periods of the same project. Software
project telemetry avoids many problems inherent in traditional metrics
models, such as the need to accumulate a historical project database and
ensure that the historical data remains comparable to current and future
projects.

The claim of this dissertation is that software project telemetry
provides an effective approach to (1) automated metrics collection and
analysis, and (2) in-process, empirically-guided software development
process problem detection and diagnosis. Two empirical studies were
carried out to evaluate the claim: one in software engineering classes,
and the other in the Collaborative Software Development Lab. The results
suggested that software project telemetry had acceptably-low metrics
collection and analysis overhead, and that it provided decision-making
value at least in the exploratory context of the two studies.

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