Developing a Change Prediction Cost Model based on Version History data and Change Couplings

finished by Bela Grossmann.

More information can be found in the project plan.

Final Thesis (PDF, 625 KB)

Recent research activities in software evolution analysis concentrated on analyzing release history data as obtained from repositories of versions and problem reporting systems, such as CVS, Subversion, Rational ClearCase, and Bugzilla. The focus of analyses typically is on software co-changes and change impact. But also a relationship between software maintenance and evolution cost and software co-changes is hardly needed to prove how effective certain software evolution analyses methods can be and if evolution history data can support an effective cost prediction for software evolution.

The goal of this diploma thesis is to develop a Change Prediction Cost Model for software evolution based on change couplings and version history information. The work shall be based upon cost models in the software engineering and maintenance area. The validation of the cost model shall be performed by applying the model to a real world open source software (OSS) project.

• Analysis of cost estimation models
• Analysis of change coupling effects for maintenance tasks
• Definition of the Change Prediction Cost Model (CPCM)
• Proof-of-concept on a small OSS case study
• Implementation of the CPCM model and integration with Release History Database (as web service interfaces, and web browser as GUI)
• Validation of the CPCM in a real-world case study

• A cost prediction model for software evolution based on release history data and change couplings.
• A prototype implementation of the cost model to be applicable to OSS projects (incl. browser GUI and Web service interface(s)).

Dr. Martin Pinzger, Prof. Harald Gall

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