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EXTRACTPRO: A Data Mining Tool for Developer Profile Generation based on Source Code Analysis

Published: 05 October 2022 Publication History

Abstract

The search for software developers with specific skills is an arduous and expensive task. Nowadays, software developers report their skills on freelance platforms and professional social networks, such as Workana and LinkedIn. However, this information tends to be sparse and difficult to compare. This paper presents EXTRACTPRO, a tool that uses a Developer Information Provider (i.e., Workana) and a Git Repository Provider (i.e., GitHub) to build a searchable collection of developer profiles. This generated developer profile contains self-declared skills in programming languages and mined information, such as lines of code and commit count. In addition to mining profiles, the tool provides a search by the skills with ranked and visually comparable results. We demonstrate the proposed tool by showing examples of use and evidence that the tool can find developers with arbitrary skills. In complement to this paper, a short video demonstration of EXTRACTPRO is also available12.

Supplementary Material

Presentation video (EXTRACTPRO SBES PRESENTATION.pdf)
MOV File (EXTRACTPRO SBES PRESENTATION T2.mov)
Presentation video

References

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cover image ACM Other conferences
SBES '22: Proceedings of the XXXVI Brazilian Symposium on Software Engineering
October 2022
457 pages
ISBN:9781450397353
DOI:10.1145/3555228
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 05 October 2022

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Author Tags

  1. Expert Identification
  2. Mining Developer Public Profiles
  3. Mining Software Repositories
  4. Software Skills

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SBES 2022
SBES 2022: XXXVI Brazilian Symposium on Software Engineering
October 5 - 7, 2022
Virtual Event, Brazil

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Overall Acceptance Rate 147 of 427 submissions, 34%

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