Software developers often miss usage information about deployed software during software evolution. This dissertation describes the MALTASE framework that acquires usage information by monitoring and analyzing user interactions. MALTASE monitors interactions as reproduction steps and classifies users according to their skills. An empirical evaluation found that MALTASE introduces an acceptable performance overhead, enables developers to reproduce failures, and is able to reliably classify user skills.
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Software developers often miss usage information about deployed software during software evolution. This dissertation describes the MALTASE framework that acquires usage information by monitoring and analyzing user interactions. MALTASE monitors interactions as reproduction steps and classifies users according to their skills. An empirical evaluation found that MALTASE introduces an acceptable performance overhead, enables developers to reproduce failures, and is able to reliably classify user s...
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