دورية أكاديمية

Log statements generation via deep learning: Widening the support provided to developers.

التفاصيل البيبلوغرافية
العنوان: Log statements generation via deep learning: Widening the support provided to developers.
المؤلفون: Mastropaolo, Antonio1 (AUTHOR) antonio.mastropaolo@usi.ch, Ferrari, Valentina1 (AUTHOR) valentina.ferrari@usi.ch, Pascarella, Luca2 (AUTHOR) lpascarella@ethz.ch, Bavota, Gabriele1 (AUTHOR) gabriele.bavota@usi.ch
المصدر: Journal of Systems & Software. Apr2024, Vol. 210, pN.PAG-N.PAG. 1p.
مصطلحات موضوعية: *INFORMATION retrieval, *TEST methods, DEEP learning, LOGGING, DATA recorders & recording
مستخلص: Logging assists in monitoring events that transpire during the execution of software. Previous research has highlighted the challenges confronted by developers when it comes to logging, including dilemmas such as where to log, what data to record, and which log level to employ (e.g., info, fatal). In this context, we introduced LANCE, an approach rooted in deep learning (DL) that has demonstrated the ability to correctly inject a log statement into Java methods in ∼ 15% of cases. Nevertheless, LANCE grapples with two primary constraints: (i) it presumes that a method necessitates the inclusion of logging statements and; (ii) it allows the injection of only a single (new) log statement, even in situations where the injection of multiple log statements might be essential. To address these limitations, we present LEONID, a DL-based technique that can distinguish between methods that do and do not require the inclusion of log statements. Furthermore, LEONID supports the injection of multiple log statements within a given method when necessary, and it also enhances LANCE's proficiency in generating meaningful log messages through the combination of DL and Information Retrieval (IR). • We propose LEONID a deep learning and information retrieval technique for logging. • LEONID discriminates between method needing logs to those that do not. • LEONID accurately injects multiple log statements in 17% of test methods. • LEONID overcomes several limitations of previous state-of-the-art approaches. [ABSTRACT FROM AUTHOR]
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قاعدة البيانات: Business Source Index
الوصف
تدمد:01641212
DOI:10.1016/j.jss.2023.111947