Blaze

Krämer, Jan-Peter; Kurz, Joachim; Karrer, Thorsten; Borchers, Jan

doi:10.1145/2212776.2223775

Cited by 7 publications

(2 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Typically questions asked by program comprehension literature relate to the mental and physical processes that developers follow [36,46]. Examples of mental processes include targeting how code is connected [45,52,81,83]. Physical processes include taking of notes [3] and pa erns of movements of the eyes [73,80].…”

Section: Studies Of Program Comprehensionmentioning

confidence: 99%

Detecting speech act types in developer question/answer conversations during bug repair

Wood

Rodeghero

Armaly

et al. 2018

Proceedings of the 2018 26th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of

View full text Add to dashboard Cite

is paper targets the problem of speech act detection in conversations about bug repair. We conduct a "Wizard of Oz" experiment with 30 professional programmers, in which the programmers x bugs for two hours, and use a simulated virtual assistant for help. en, we use an open coding manual annotation procedure to identify the speech act types in the conversations. Finally, we train and evaluate a supervised learning algorithm to automatically detect the speech act types in the conversations. In 30 two-hour conversations, we made 2459 annotations and uncovered 26 speech act types. Our automated detection achieved 69% precision and 50% recall. e key application of this work is to advance the state of the art for virtual assistants in so ware engineering. Virtual assistant technology is growing rapidly, though applications in so ware engineering are behind those in other areas, largely due to a lack of relevant data and experiments. is paper targets this problem in the area of developer Q/A conversations about bug repair. CCS CONCEPTS•So ware and its engineering → Maintaining so ware;

show abstract

Section: Studies Of Program Comprehensionmentioning

confidence: 99%

Detecting speech act types in developer question/answer conversations during bug repair

Wood

Rodeghero

Armaly

et al. 2018

Proceedings of the 2018 26th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of

View full text Add to dashboard Cite

show abstract

“…In contrast, an "opportunistic" strategy aims to find only the section of code that is needed for a particular change [26], [27], [28], [4]. In either strategy, studies suggest that programmers form a mental model of the software [1], specifically including the relationships between different sections of source code [29], [30], [12], [31]. Documentation and note-taking is widely viewed as important because programmers tend to forget the knowledge they have gained about the software [32], [33].…”

Section: Studies Of Program Comprehensionmentioning

confidence: 99%

An Eye-Tracking Study of Java Programmers and Application to Source Code Summarization

Rodeghero

Liu

McBurney

et al. 2015

IIEEE Trans. Software Eng.

View full text Add to dashboard Cite

Source Code Summarization is an emerging technology for automatically generating brief descriptions of code. Current summarization techniques work by selecting a subset of the statements and keywords from the code, and then including information from those statements and keywords in the summary. The quality of the summary depends heavily on the process of selecting the subset: a high-quality selection would contain the same statements and keywords that a programmer would choose. Unfortunately, little evidence exists about the statements and keywords that programmers view as important when they summarize source code. In this paper, we present an eye-tracking study of 10 professional Java programmers in which the programmers read Java methods and wrote English summaries of those methods. We apply the findings to build a novel summarization tool. Then, we evaluate this tool. Finally, we further analyze the programmers' method summaries to explore specific keyword usage and provide evidence to support the development of source code summarization systems.

show abstract

Mining Software Information Sites to Recommend Cross-Language Analogical Libraries

Nafi

Asaduzzaman

Roy

et al. 2022

2022 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER)

View full text Add to dashboard Cite

Blaze

Cited by 7 publications

References 9 publications

Detecting speech act types in developer question/answer conversations during bug repair

Detecting speech act types in developer question/answer conversations during bug repair

An Eye-Tracking Study of Java Programmers and Application to Source Code Summarization

Mining Software Information Sites to Recommend Cross-Language Analogical Libraries

Contact Info

Product

Resources

About