RE journal

📢 The Requirements Engineering Journal is now on LinkedIn! 🎉 Follow us there to stay updated on accepted papers, special issues, and community news. We’ll be discontinuing our presence on X, so make sure to connect with us on LinkedIn 👇 🔗 linkedin.com/company/reen-j…

A new article on RE and SE challenges in automotive has been published with us! Check it out!

#re23 @ieee_re RE'23 officially starting!

Also this year, we are collaborating with @ieee_re . The best papers accepted at #re23 will be invited to submit an extended version at our journal! Hope everyone is enjoy the conference!

Arnon Sturm presents a journal first paper on instability in user stories at #re23 published in the @ReqEngJ journal: link.springer.com/article/10.100…

The third issue of the year is now out, with papers on RE and #devops, prioritization, model-driven RE, and more buff.ly/3XSSppv

The special issue on REFSQ 2021 is out! buff.ly/3knOVMi Through the reviewing process guided by the guest editors Spoletini and Dalpiaz, we present four articles on self-adaptive systems, requirements similarity, causality, and user feedback! @FabianoDalpiaz @PaolaSpo

We are looking for a new social media chair! Are you a senior PhD student, postdoc, or assistant professor with an interest in RE? Are you willing to drive the social media visibility of REJ? @ieee_re @wc_refsq Reach out by mail: reenjournal@gmail.com or DM @FabianoDalpiaz

Did you know? Thanks to @SpringerNature, we also welcome corrections to previously published articles. For an example, see our latest issue, which includes two of such cases buff.ly/3AM0cKC How to? Contact us buff.ly/3cKHWJx

Tizard @TizardJames, Rietz, Liu, and Blincoe @KellyBlincoe conduct a study on user feedback. Which channels are used? Are there differences depending on demographic factors? Read more at: buff.ly/3RanaST

Chitchyan @ruzanna_c and Caroline Bird, based on their best paper at @ieee_re in 2020, present an extended article that argues for the use of (grounded) theory in requirements engineering, showing the interesting information it may reveal. Link: buff.ly/3eixARw

A classic topic in RE research is ambiguity detection. And one of its classic task is the detection of coreferences. Using a #deeplearning #bert model, Wang and colleagues achieve excellent performance Link: buff.ly/3Rvb6uZ

In our September issue, Carvalho, de Castro Andrade and de Oliveira present a catalog of invisibility correlations that focuses on NFRs in ubiquitous computing and IoT #IoT. Can transparency (useful for #xai be a domain where NFRs are crucial? Paper: buff.ly/3CSDKlV

As we are now in September, it is time to announce our third issue of 2022. This is a special issue of best papers from the 2020 @ieee_re conference, with guest editors Travis Breaux and Andrea Zisman. Check out the articles online: buff.ly/3AM0cKC

Second journal-first article: "Empirical research on requirements quality: a systematic mapping study" by @LloydThinks @dfucci_ Bourrafa Scholz and @maalejw

First journal-first article from our journal published at @iee_re: "How assurance case development and requirements engineering interplay: a study with practitioners" will be presented on Wednesday 17/8 at 14:10 CET time

Two papers published in our journal will appear in the @ieee_re conference this week: one on Wednesday, one on Friday. Stay tuned for the individual paper announcements!

Assurance case development (ACD) can demonstrate if a system is safe for use. In the current issue, Almendra, C., Silva, C., et al present the results of their study on how ACD interplays with requirements engineering. It's worth reading it! buff.ly/3yWpBlL #reqeng

Quality requirements are critical for the development of quality software. In the current issue, Olsson, T., Sentilles, S. & Papatheocharous, E. present a systematic literature review on this issue. It's worth reading it. #reqeng buff.ly/3GlNhSh

User stories is a common way to describe requirements in Agile s/w development. Levy, Y., Stern, R., Sturm, A., Mordoch, A. & Bitan, Y, describe how they create prediction models to identify user stories with high instability before development. #reqeng buff.ly/3LAvS96