ASE 2022 (series) / Late Breaking Results / A real-world case study for automated ticket team assignment using natural language processing and explainable models
A real-world case study for automated ticket team assignment using natural language processing and explainable modelsVirtual
Tue 11 Oct 2022 11:50 - 12:00 at Banquet A - Technical Session 2 - Debugging and Troubleshooting Chair(s): Andrew Begel
In the context of software development, managing and organizing agile boards of multi-disciplinary teams distributed around the world is a great challenge, especially regarding the process of assigning tickets to the correct team roles. Incorrectly assigned tickets can result in significant resource waste in any project and directly influence delivery outcomes and project costs. This work proposes a method for ticket analysis and automatic team assignment using Natural Language Processing and explainable Machine Learning models. Results show that the models perform well on a real-world team assignment task and provide insights into their decision.
Tue 11 OctDisplayed time zone: Eastern Time (US & Canada) change
Tue 11 Oct
Displayed time zone: Eastern Time (US & Canada) change
10:30 - 12:30 | Technical Session 2 - Debugging and TroubleshootingResearch Papers / Industry Showcase / Late Breaking Results at Banquet A Chair(s): Andrew Begel Carnegie Mellon University, Software and Societal Systems Department | ||
10:30 20mResearch paper | Call Me Maybe: Using NLP to Automatically Generate Unit Test Cases Respecting Temporal Constraints Research Papers Arianna Blasi Meta; prev. Università della Svizzera italiana, Alessandra Gorla IMDEA Software Institute, Michael D. Ernst University of Washington, Mauro Pezze USI Lugano; Schaffhausen Institute of Technology | ||
10:50 20mResearch paper | CoditT5: Pretraining for Source Code and Natural Language Editing Research Papers Jiyang Zhang University of Texas at Austin, Sheena Panthaplackel UT Austin, Pengyu Nie University of Texas at Austin, Junyi Jessy Li University of Texas at Austin, USA, Milos Gligoric University of Texas at Austin Pre-print | ||
11:10 20mIndustry talk | Automated Identification of Security-Relevant Configuration Settings Using NLP Industry Showcase Patrick Stöckle Technical University of Munich (TUM), Theresa Wasserer Technical University of Munich, Bernd Grobauer Siemens AG, Alexander Pretschner TU Munich Pre-print | ||
11:30 20mResearch paper | Is this Change the Answer to that Problem? Correlating Descriptions of Bug and Code Changes for Evaluating Patch Correctness Research Papers Haoye Tian University of Luxembourg, Xunzhu Tang University of Luxembourg, Andrew Habib SnT, University of Luxembourg, Shangwen Wang National University of Defense Technology, Kui Liu Huawei Software Engineering Application Technology Lab, Xin Xia Huawei Software Engineering Application Technology Lab, Jacques Klein University of Luxembourg, Tegawendé F. Bissyandé SnT, University of Luxembourg Pre-print | ||
11:50 10mPaper | A real-world case study for automated ticket team assignment using natural language processing and explainable modelsVirtual Late Breaking Results |