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EasyView: Bringing Performance Profiles into Integrated Development Environments (2312.16598v1)

Published 27 Dec 2023 in cs.SE and cs.PF

Abstract: Dynamic program analysis (also known as profiling) is well-known for its powerful capabilities of identifying performance inefficiencies in software packages. Although a large number of dynamic program analysis techniques are developed in academia and industry, very few of them are widely used by software developers in their regular software developing activities. There are three major reasons. First, the dynamic analysis tools (also known as profilers) are disjoint from the coding environments such as IDEs and editors; frequently switching focus between them significantly complicates the entire cycle of software development. Second, mastering various tools to interpret their analysis results requires substantial efforts; even worse, many tools have their own design of graphical user interfaces (GUI) for data presentation, which steepens the learning curves. Third, most existing tools expose few interfaces to support user-defined analysis, which makes the tools less customizable to fulfill diverse user demands. We develop EasyView, a general solution to integrate the interpretation and visualization of various profiling results in the coding environments, which bridges software developers with profilers to provide easy and intuitive dynamic analysis during the code development cycle. The novelty of EasyView is three-fold. First, we develop a generic data format, which enables EasyView to support mainstream profilers for different languages. Second, we develop a set of customizable schemes to analyze and visualize the profiles in intuitive ways. Third, we tightly integrate EasyView with popular coding environments, such as Microsoft Visual Studio Code, with easy code exploration and user interaction. Our evaluation shows that EasyView is able to support various profilers for different languages and provide unique insights into performance inefficiencies in different domains.

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Authors (3)
  1. Qidong Zhao (5 papers)
  2. Milind Chabbi (12 papers)
  3. Xu Liu (213 papers)

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