We have conducted a study in a large telecommunication company in Turkey to employ a software measurement program and to predict prerelease defects. We have previously built such predictors using AI techniques. This project is a transfer of our research experience into a real life setting to solve a specific problem for Trcll: to improve code quality by predicting pre-release defects and efficiently allocating testing resources. Our results in this project have many practical implications that managers have started benefiting: using version history information, developers only need to inspect 31 % of the code to find around 84 % of the defects with 29 % false alarms, compared to 60 % inspection effort with 46 % false alarms without using the historical data. In this paper we also shared in detail our experience in terms of the project steps (i.e. challenges and opportunities). 1
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