How to Find Actionable Static Analysis Warnings: A Case Study with FindBugs
Automatically generated static code warnings suffer from a large number of false alarms. Hence, developers only take action on a small percent of those warnings. To better predict which static code warnings should not be ignored, we suggest that analysts need to look deeper into their algorithms to find choices that better improve the particulars of their specific problem. Specifically, we show here that effective predictors of such warnings can be created by methods that locally adjust the decision boundary (between actionable warnings and others). These methods yield a new high water-mark for recognizing actionable static code warnings. For eight open-source Java projects (cassandra, jmeter, commons, lucene-solr, maven, ant, tomcat, derby) we achieve perfect test results on 4/8 datasets and, overall, a median AUC (area under the true negatives, true positives curve) of 92%.
Wed 13 SepDisplayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change
10:30 - 12:00 | Code Quality and Code SmellsTool Demonstrations / Journal-first Papers / Research Papers at Plenary Room 2 Chair(s): Bernd Fischer Stellenbosch University | ||
10:30 12mTalk | Contextuality of Code Representation Learning Research Papers Yi Li New Jersey Institute of Technology, Shaohua Wang New Jersey Institute of Technology, Tien N. Nguyen University of Texas at Dallas | ||
10:42 12mTalk | On-the-fly Improving Performance of Deep Code Models via Input Denoising Research Papers Pre-print File Attached | ||
10:54 12mTalk | Using Deep Learning to Automatically Improve Code Readability Research Papers Antonio Vitale University of Molise, Italy, Valentina Piantadosi University of Molise, Simone Scalabrino University of Molise, Rocco Oliveto University of Molise Pre-print | ||
11:06 12mTalk | Towards Automatically Addressing Self-Admitted Technical Debt: How Far Are We? Research Papers Antonio Mastropaolo Università della Svizzera italiana, Massimiliano Di Penta University of Sannio, Italy, Gabriele Bavota Software Institute, USI Università della Svizzera italiana Pre-print File Attached | ||
11:18 12mTalk | How to Find Actionable Static Analysis Warnings: A Case Study with FindBugs Journal-first Papers Rahul Yedida , Hong Jin Kang UCLA, Huy Tu North Carolina State University, USA, Xueqi Yang NCSU, David Lo Singapore Management University, Tim Menzies North Carolina State University Link to publication DOI Authorizer link Pre-print | ||
11:30 12mTalk | Polyglot Code Smell Detection for Infrastructure as Code with GLITCH Tool Demonstrations Nuno Saavedra INESC-ID and IST, University of Lisbon, João Gonçalves INESC-ID and IST, University of Lisbon, Miguel Henriques INESC-ID and IST, University of Lisbon, João F. Ferreira INESC-ID and IST, University of Lisbon, Alexandra Mendes Faculty of Engineering, University of Porto & INESC TEC Pre-print File Attached | ||
11:42 12mTalk | Enhancing the defectiveness prediction of methods and classes via JIT Journal-first Papers Falessi Davide University of Rome Tor Vergata, Simone Mesiano Laureani University of Rome Tor Vergata, Jonida Çarka University of Rome Tor Vergata, Matteo Esposito University of Rome Tor Vergata, Daniel Alencar Da Costa University of Otago Link to publication DOI File Attached | ||