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Full-Text Articles in Physical Sciences and Mathematics

Break The Dead End Of Dynamic Slicing: Localizing Data And Control Omission Bug, Yun Lin, Jun Sun, Lyly Tran, Guangdong Bai, Haijun Wang, Jin Song Dong Sep 2018

Break The Dead End Of Dynamic Slicing: Localizing Data And Control Omission Bug, Yun Lin, Jun Sun, Lyly Tran, Guangdong Bai, Haijun Wang, Jin Song Dong

Research Collection School Of Computing and Information Systems

Dynamic slicing is a common way of identifying the root cause when a program fault is revealed. With the dynamic slicing technique, the programmers can follow data and control flow along the program execution trace to the root cause. However, the technique usually fails to work on omission bugs, i.e., the faults which are caused by missing executing some code. In many cases, dynamic slicing over-skips the root cause when an omission bug happens, leading the debugging process to a dead end. In this work, we conduct an empirical study on the omission bugs in the Defects4J bug repository. Our …


Proactive Empirical Assessment Of New Language Feature Adoption Via Automated Refactoring: The Case Of Java 8 Default Methods, Raffi T. Khatchadourian, Hidehiko Masuhara Apr 2018

Proactive Empirical Assessment Of New Language Feature Adoption Via Automated Refactoring: The Case Of Java 8 Default Methods, Raffi T. Khatchadourian, Hidehiko Masuhara

Publications and Research

Programming languages and platforms improve over time, sometimes resulting in new language features that offer many benefits. However, despite these benefits, developers may not always be willing to adopt them in their projects for various reasons. In this paper, we describe an empirical study where we assess the adoption of a particular new language feature. Studying how developers use (or do not use) new language features is important in programming language research and engineering because it gives designers insight into the usability of the language to create meaning programs in that language. This knowledge, in turn, can drive future innovations …


Proactive Empirical Assessment Of New Language Feature Adoption Via Automated Refactoring: The Case Of Java 8 Default Methods, Raffi T. Khatchadourian, Hidehiko Masuhara Apr 2018

Proactive Empirical Assessment Of New Language Feature Adoption Via Automated Refactoring: The Case Of Java 8 Default Methods, Raffi T. Khatchadourian, Hidehiko Masuhara

Publications and Research

Programming languages and platforms improve over time, sometimes resulting in new language features that offer many benefits. However, despite these benefits, developers may not always be willing to adopt them in their projects for various reasons. In this paper, we describe an empirical study where we assess the adoption of a particular new language feature. Studying how developers use (or do not use) new language features is important in programming language research and engineering because it gives designers insight into the usability of the language to create meaning programs in that language. This knowledge, in turn, can drive future innovations …