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Divya Muppaneni

dblp:11/8523 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2010
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Software engineering, system software, and programming languages
1 paper
Software maintenance and evolution · 33% Program synthesis and code generation · 33% Compilers and program optimization · 33%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Program synthesis and code generation › code documentation generation
code comment generation
0.112010
Towards automatically generating summary comments for Java methods · ASE 2010
Compilers and program optimization
code generation
0.112010
Towards automatically generating summary comments for Java methods · ASE 2010
Software maintenance and evolution
program comprehension
0.112010
Towards automatically generating summary comments for Java methods · ASE 2010

Methods — techniques the papers use, named apart from their topics

natural language generation · 0.1
YearPublicationVenuePosition
2010 Towards automatically generating summary comments for Java methods
abstract
Studies have shown that good comments can help programmers quickly understand what a method does, aiding program comprehension and software maintenance. Unfortunately, few software projects adequately comment the code. One way to overcome the lack of human-written summary comments, and guard against obsolete comments, is to automatically generate them. In this paper, we present a novel technique to automatically generate descriptive summary comments for Java methods. Given the signature and body of a method, our automatic comment generator identifies the content for the summary and generates natural language text that summarizes the method's overall actions. According to programmers who judged our generated comments, the summaries are accurate, do not miss important content, and are reasonably concise.
Giriprasad Sridhara, Emily Hill 0001, Divya Muppaneni, Lori L. Pollock, K. Vijay-Shanker
ASE3