[2208.05266] Empirical Formal Methods: Guidelines for Performing Empirical Studies on Formal Methods
Skip to main content
We gratefully acknowledge support from the Simons Foundation, member institutions, and all contributors. Donate
arXiv logo
Cornell University Logo

Computer Science > Software Engineering

arXiv:2208.05266 (cs)
[Submitted on 10 Aug 2022 (v1), last revised 11 Aug 2022 (this version, v2)]

Title:Empirical Formal Methods: Guidelines for Performing Empirical Studies on Formal Methods

Authors:Maurice H. ter Beek, Alessio Ferrari
View PDF
Abstract:Empirical studies on formal methods and tools are rare. In this paper, we provide guidelines for such studies. We mention their main ingredients and then define nine different study strategies (laboratory experiments with software and human subjects, usability testing, surveys, qualitative studies, judgment studies, case studies, systematic literature reviews, and systematic mapping studies) and discuss for each of them their crucial characteristics, the difficulties of applying them to formal methods and tools, typical threats to validity, their maturity in formal methods, pointers to external guidelines, and pointers to studies in other fields. We conclude with a number of challenges for empirical formal methods.
Subjects: Software Engineering (cs.SE); Formal Languages and Automata Theory (cs.FL)
ACM classes: D.2; D.2.4; F.3.1; F.4; F.4.3; D.3.1; D.2.2
Cite as: arXiv:2208.05266 [cs.SE]
  (or arXiv:2208.05266v2 [cs.SE] for this version)
  https://doi.org/10.48550/arXiv.2208.05266

Submission history

From: Alessio Ferrari [view email]
[v1] Wed, 10 Aug 2022 10:49:59 UTC (227 KB)
[v2] Thu, 11 Aug 2022 09:26:12 UTC (215 KB)
Full-text links:

Access Paper:

  • View PDF
  • TeX Source
  • Other Formats
view license
Current browse context:
cs.SE
< prev   |   next >
new | recent | 2022-08
Change to browse by:
cs
cs.FL

References & Citations

export BibTeX citation

Bookmark

BibSonomy logo Reddit logo

Bibliographic and Citation Tools

Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)

Code, Data and Media Associated with this Article

alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
Papers with Code (What is Papers with Code?)
ScienceCast (What is ScienceCast?)

Demos

Replicate (What is Replicate?)
Hugging Face Spaces (What is Spaces?)
TXYZ.AI (What is TXYZ.AI?)

Recommenders and Search Tools

Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)