Will this be quick? A case study of bug resolution times across industrial projects
Resolution of problem tickets is a source of significant revenue in the worldwide software services industry. Due to the high volume of problem tickets in any large scale customer engagement, automated techniques are necessary to segregate related incoming tickets into groups. Existing techniques fo...
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| Main Authors: | , |
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| Format: | text |
| Language: | English |
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Institutional Knowledge at Singapore Management University
2015
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| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/sis_research/5590 https://ink.library.smu.edu.sg/context/sis_research/article/6593/viewcontent/WillThisBeQuick_2015_pv.pdf |
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| Institution: | Singapore Management University |
| Language: | English |
| Summary: | Resolution of problem tickets is a source of significant revenue in the worldwide software services industry. Due to the high volume of problem tickets in any large scale customer engagement, automated techniques are necessary to segregate related incoming tickets into groups. Existing techniques focus on this classification problem. In this paper, we present a case study built around the position that predicting the category of resolution times within a class of tickets and also the actual resolution times, is strongly beneficial to ticket resolution. We present an approach based on topic analysis to predict the category of resolution times of incoming tickets and validate it on a data-set of 49,000+ problem tickets across 14 classes from four real-life projects. To establish the effectiveness of our approach, we compare topic features with traditional features for both classification and regression problems. Our results indicate the promise of topic analysis based approaches for large scale problem ticket management. |
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