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#softwareengineering

16 posts14 participants0 posts today
Vassil Nikolov

An easy question about internet message headers (RFC 822 and subsequent revisions).

Take a message thread where each reply has a single parent message.
Such a thread is often shown as a tree, linking replies by their `References' header fields.
Why does _each_ such field contain _all_ parent message ids up to the "root" message of the thread?
Wouldn't the id just of the parent message be enough, as in the `In-Reply-To' header field?

#DistributedSystems
#InternetMessages
#SoftwareEngineering

Stefan Schmidt-Bilkenroth

KI wird die Softwareentwicklung revolutionieren.
Mag sein - aber anders als sich die meisten das denken, laut einer Studie der Carnell Universität.

#ai #ki #softwareengineering

arxiv.org/abs/2507.09089

arXiv logo
arXiv.orgMeasuring the Impact of Early-2025 AI on Experienced Open-Source Developer ProductivityDespite widespread adoption, the impact of AI tools on software development in the wild remains understudied. We conduct a randomized controlled trial (RCT) to understand how AI tools at the February-June 2025 frontier affect the productivity of experienced open-source developers. 16 developers with moderate AI experience complete 246 tasks in mature projects on which they have an average of 5 years of prior experience. Each task is randomly assigned to allow or disallow usage of early 2025 AI tools. When AI tools are allowed, developers primarily use Cursor Pro, a popular code editor, and Claude 3.5/3.7 Sonnet. Before starting tasks, developers forecast that allowing AI will reduce completion time by 24%. After completing the study, developers estimate that allowing AI reduced completion time by 20%. Surprisingly, we find that allowing AI actually increases completion time by 19%--AI tooling slowed developers down. This slowdown also contradicts predictions from experts in economics (39% shorter) and ML (38% shorter). To understand this result, we collect and evaluate evidence for 20 properties of our setting that a priori could contribute to the observed slowdown effect--for example, the size and quality standards of projects, or prior developer experience with AI tooling. Although the influence of experimental artifacts cannot be entirely ruled out, the robustness of the slowdown effect across our analyses suggests it is unlikely to primarily be a function of our experimental design.
Harald Klinke

Neue Studie: KI-Assistenten bremsen erfahrene Entwickler aus
Laut einer Mitte Juli veröffentlichten RCT-Studie der Cornell University verlängert der Einsatz von KI-Tools wie Cursor Pro und Claude 3.5/3.7 die Arbeitszeit erfahrener Open-Source-Programmierer um 19 % – statt wie erhofft 20 % einzusparen.

Grund ist vor allem die noch geringe Zuverlässigkeit der Tools im professionellen Alltag.
#AIProductivity #SoftwareEngineering #KIRealität

arxiv.org/abs/2507.09089

ThomasAPowell

It should be evident to all that in today's software engineering space, economic forces profoundly shape decision-making on all sides, from developers' career planning influencing approach to product managers' consideration of a system or feature. Sadly, we rarely discuss these influences adequately in SWE academic settings, so it is no wonder that hustle-bro economic thought patterns dominate the conversation.

#SoftwareEngineering
N-gated Hacker News

🚨 Breaking #news from the world of software engineering: file position impacts #code review! 🙄 Next, they might reveal that water is wet. Apparently, the order you read code matters—thank goodness for #scientific #rigor in discovering the obvious. 🎉
arxiv.org/abs/2208.04259 #softwareengineering #review #tech #developer #humor #HackerNews #ngated

arXiv logo
arXiv.orgFirst Come First Served: The Impact of File Position on Code ReviewThe most popular code review tools (e.g., Gerrit and GitHub) present the files to review sorted in alphabetical order. Could this choice or, more generally, the relative position in which a file is presented bias the outcome of code reviews? We investigate this hypothesis by triangulating complementary evidence in a two-step study. First, we observe developers' code review activity. We analyze the review comments pertaining to 219,476 Pull Requests (PRs) from 138 popular Java projects on GitHub. We found files shown earlier in a PR to receive more comments than files shown later, also when controlling for possible confounding factors: e.g., the presence of discussion threads or the lines added in a file. Second, we measure the impact of file position on defect finding in code review. Recruiting 106 participants, we conduct an online controlled experiment in which we measure participants' performance in detecting two unrelated defects seeded into two different files. Participants are assigned to one of two treatments in which the position of the defective files is switched. For one type of defect, participants are not affected by its file's position; for the other, they have 64% lower odds to identify it when its file is last as opposed to first. Overall, our findings provide evidence that the relative position in which files are presented has an impact on code reviews' outcome; we discuss these results and implications for tool design and code review. Data and materials: https://doi.org/10.5281/zenodo.6901285
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