Open Data-driven Usability Improvements of Static Code Analysis and its Challenges
Söderberg, Emma LU
; Church, Luke
LU
and Höst, Martin
LU
(2021)
25th International Conference on Evaluation and Assessment in Software Engineering, EASE
p.272-277
- Abstract
- Context: Software development is moving towards a place where data about development is gathered in a systematic fashion in order to improve the practice, for example, in tuning of static code analysis. However, this kind of data gathering has so far primarily happened within organizations, which is unfortunate as it tends to favor larger organizations with more resources for maintenance of developer tools. Objective: Over the years, we have seen a lot of benefits from open source and recently there has been a lot of development in open data. We see this as an opportunity for cross-organisation community building and wonder to what extent the views on using and sharing open source software developer tools carry across to open data-driven... (More)
- Context: Software development is moving towards a place where data about development is gathered in a systematic fashion in order to improve the practice, for example, in tuning of static code analysis. However, this kind of data gathering has so far primarily happened within organizations, which is unfortunate as it tends to favor larger organizations with more resources for maintenance of developer tools. Objective: Over the years, we have seen a lot of benefits from open source and recently there has been a lot of development in open data. We see this as an opportunity for cross-organisation community building and wonder to what extent the views on using and sharing open source software developer tools carry across to open data-driven tuning of software development tools. Method: An exploratory study with 11 participants divided into 3 focus groups discussing using and sharing of static code analyzers and data about these analyzers. Results: While using and sharing open-source code (analyzers in this case) is perceived in a positive light as part of the practice of modern software development, sharing data is met with skepticism and uncertainty. Developers are concerned about threats to the company brand, exposure of intellectual property, legal liabilities, and to what extent data is context-specific to a certain organisation. Conclusions: Sharing data in software development is different from sharing data about software development. We need to better understand how we can provide solutions for sharing of software development data in a fashion that reduces risk and enables openness. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/1a81e98d-3496-4b8e-b40e-a8454bdc5948
- author
- Söderberg, Emma
LU
; Church, Luke
LU
and Höst, Martin
LU
- organization
- publishing date
- 2021
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- EASE'21: Evaluation and Assessment in Software Engineering
- pages
- 272 - 277
- conference name
- 25th International Conference on Evaluation and Assessment in Software Engineering, EASE
- conference location
- Trondheim, Norway
- conference dates
- 2021-06-21 - 2021-06-24
- external identifiers
-
- scopus:85108907145
- ISBN
- 978-145039053-8
- DOI
- 10.1145/3463274.3463808
- project
- Adaptive Developer Tools
- Adaptive Developer Tools
- HATCH: Handling Vulnerabilities in the Value Chain
- language
- English
- LU publication?
- yes
- id
- 1a81e98d-3496-4b8e-b40e-a8454bdc5948
- date added to LUP
- 2021-05-03 15:14:36
- date last changed
- 2022-05-05 01:22:11
@inproceedings{1a81e98d-3496-4b8e-b40e-a8454bdc5948,
abstract = {{Context: Software development is moving towards a place where data about development is gathered in a systematic fashion in order to improve the practice, for example, in tuning of static code analysis. However, this kind of data gathering has so far primarily happened within organizations, which is unfortunate as it tends to favor larger organizations with more resources for maintenance of developer tools. Objective: Over the years, we have seen a lot of benefits from open source and recently there has been a lot of development in open data. We see this as an opportunity for cross-organisation community building and wonder to what extent the views on using and sharing open source software developer tools carry across to open data-driven tuning of software development tools. Method: An exploratory study with 11 participants divided into 3 focus groups discussing using and sharing of static code analyzers and data about these analyzers. Results: While using and sharing open-source code (analyzers in this case) is perceived in a positive light as part of the practice of modern software development, sharing data is met with skepticism and uncertainty. Developers are concerned about threats to the company brand, exposure of intellectual property, legal liabilities, and to what extent data is context-specific to a certain organisation. Conclusions: Sharing data in software development is different from sharing data about software development. We need to better understand how we can provide solutions for sharing of software development data in a fashion that reduces risk and enables openness.}},
author = {{Söderberg, Emma and Church, Luke and Höst, Martin}},
booktitle = {{EASE'21: Evaluation and Assessment in Software Engineering}},
isbn = {{978-145039053-8}},
language = {{eng}},
pages = {{272--277}},
title = {{Open Data-driven Usability Improvements of Static Code Analysis and its Challenges}},
url = {{https://lup.lub.lu.se/search/files/97373542/paper.pdf}},
doi = {{10.1145/3463274.3463808}},
year = {{2021}},
}