Mihir Mathur

dblp:228/5734 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · none

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

Software engineering, systems software and programming languages · 2

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
2 papers
Software maintenance and evolution · 35% Empirical software engineering · 30% Program verification · 20%
Computer graphics and multimedia
1 paper
Visualization and visual analytics · 100%

Topics — the 6 heaviest of 7, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Program verification › model checking › state space exploration
reachability analysis
0.412020
WebJShrink: a web service for debloating Java bytecode · ESEC/SIGSOFT FSE 2020
Software maintenance and evolution › software reengineering
software debloating
0.412020
WebJShrink: a web service for debloating Java bytecode · ESEC/SIGSOFT FSE 2020
Software maintenance and evolution
API usage
0.312018
Augmenting stack overflow with API usage patterns mined from GitHub · ESEC/SIGSOFT FSE 2018
Program analysis › error detection
API usage error detection
0.312018
Augmenting stack overflow with API usage patterns mined from GitHub · ESEC/SIGSOFT FSE 2018
Empirical software engineering › mining software repositories
API usage patterns
0.312018
Augmenting stack overflow with API usage patterns mined from GitHub · ESEC/SIGSOFT FSE 2018
Empirical software engineering
mining software repositories
0.312018
Augmenting stack overflow with API usage patterns mined from GitHub · ESEC/SIGSOFT FSE 2018

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

visual analytics · 0.9static analysis · 0.9dynamic analysis · 0.9pattern mining · 0.3chrome extension · 0.3
YearPublicationVenuePosition
2020 WebJShrink: a web service for debloating Java bytecode
abstract
As software projects grow in complexity, they come packaged with under-utilized libraries and therefore become bloated. Though several software debloating tools exist, none of them help developers gain insights into how under-utilized those libraries are nor help developers build confidence in the behavior preservation of software after debloating. To bridge this gap, we developed WebJShrink, a visual analytics tool for analyzing and pruning bloated software projects. WebJShrink is built on JShrink which uses static and dynamic reachability analysis to determine the extent of software bloat. WebJShrink provides rich visualizations of the bloat lurking within a target project's internal structure. It then removes unused features, and returns a safer, slimmer variant of the software project. To illustrate the target project's behavior preservation, WebJShrink examines the debloated software with its JUnit tests and visualizes the test results. In evaluating WebJShrink against 26 real world systems, we found WebJShrink could reduce software size by up to 42%, 11% on average, while still passing 100% of unit tests after debloating. We provide a video demonstrating WebJShrink at https://youtu.be/yzVzcd-MJ1w.
Konner Macias, Mihir Mathur, Bobby R. Bruce, Tianyi Zhang 0001, Miryung Kim
ESEC/SIGSOFT FSE2
2018 Augmenting stack overflow with API usage patterns mined from GitHub
abstract
Programmers often consult Q&A websites such as Stack Overflow (SO) to learn new APIs. However, online code snippets are not always complete or reliable in terms of API usage. To assess online code snippets, we build a Chrome extension, ExampleCheck that detects API usage violations in SO posts using API usage patterns mined from 380K GitHub projects. It quantifies how many GitHub examples follow common API usage and illustrates how to remedy the detected violation in a given SO snippet. With ExampleCheck, programmers can easily identify the pitfalls of a given SO snippet and learn how much it deviates from common API usage patterns in GitHub. The demo video is at https://youtu.be/WOnN-wQZsH0.
Anastasia Schaadhardt, Tianyi Zhang 0001, Mihir Mathur, Miryung Kim
ESEC/SIGSOFT FSE3