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This release encompasses two broad sets of changes: widening the pool of candidates for feeds and more carefully checking the origin of inbound activities (broadly FEP-fe34, Origin-based security model).
Candidates for feeds were originally limited to posts in the actor's mailboxes. This decision made authorization easy but omitted clearly acceptable posts (for example, posts addressed to the public collection) that arrived via other means (for example, filling in a thread).
Prior to this release, inbox processing did not consistently define an object's origin nor did it apply consistent rules to what it admitted based on the origin.
FEP-fe34 is still not fully enforced, and truth be told, I'm still reviewing some of its mandates, so I'm not yet listing it in Ktistec's federation documentation.
Here's the full list of changes:
Added
Fixed
Create and Update to update objects.Changed
Removed
proxyUrl property from the actor document.I am still working hard on the feed deck. Both notifications and feed ordering now work. It's now my preferred reading interface, and should be ready by the next release!

I will be presenting our latest #Fandango work at the #GOTO conference on September 30 in Copenhagen, Denmark. Let's meet at GOTO! https://gotocph.com/2026
In the past months, I have had a number of great PhD students pass their exams:
* Leon Bettscheider for "Input Grammars in Practice - Methods for Symbolic Mining, Systematic Evaluation, and Grey-Box Testing": https://scholar.google.com/citations?user=GNt3lsUAAAAJ&hl=en&oi=ao
* Masudul Hasan Masud for "Addressing Socio-Technical Blind Spots in Modern Software Systems": https://www.linkedin.com/feed/update/urn:li:activity:7471651787322634241/
* Abdullah AlHamdan for “Security Analysis of Modern JavaScript Runtimes”: https://www.linkedin.com/feed/update/urn:li:activity:7468044729646051329/
Big congratulations to all!
SIGPLAN’s treasurer, Alex Potanin, details where the money goes for running conferences and the SIG’s other community activities. 💸 https://blog.sigplan.org/2026/07/20/sigplan-budget/

New post: Test-case Reducers Are Underappreciated Debugging Tools. The more I've used these tools, the more ways I realise they can be used! This post starts at the basics and works up to things like reducing on properties other than just the length of the input. https://tratt.net/laurie/blog/2026/test_case_reducers_are_underappreciated_debugging_tools.html

I have been selected into the inaugural class of the ACM SIGSOFT Software Engineering Academy: https://www2.sigsoft.org/academy/inaugural-class.html
Can input reduction with delta debugging be faster without sacrificing 1-minimality?
We revisited the ddmin family and found the culprit: a chronic case of unnecessary restarts.
Meet Dr. DD: 1-Minimal Isolation of Failure Causes via Deferred Restarts
A drop-in replacement for ddmin that preserves 1-minimality while avoiding redundant oracle calls, accepted at ISSRE 2026. Joint work with Aarush Kumbhakern, Feiyang Chen, Danushka Liyanage, Xi Wu, Mohammad Amin Alipour, and Rahul Gopinath (me).
Read it here: https://rahul.gopinath.org/resources/issre2026/kumbhakern2026.pdf
Our work "Maximal Format-Free Data Repair" has been accepted for publication at ASE 2026. This is a joint work by Jack Luo, Xi Wu, Hong Jin Kang, Alan Fekete, and Rahul Gopinath (me). It shows how to repair syntactically rich text data with minimal effort even when the syntax specification is unavailable. It combines passive and active blackbox grammar inference to achieve this feat.
You can read it here.
A tutorial of the #TTT algorithm for inferring regular input grammars using active membership queries. I had posted the L* algorithm (active grammar inference using membership queries), and the RPNI algorithm (passive grammar inference using examples) earlier.
This is part of my ongoing effort to document various algorithms relating to grammars including various algorithms for parsing, random sampling of fixed size strings, and grammar fuzzing.
Note: Pyodide takes a little time to initialize, but it should be faster to initialize than spinning up the binder service from Jupyter (but slower to execute).
https://rahul.gopinath.org/post/2026/06/09/ttt-grammar-inference/
A Simple Runtime Invariant Miner: A tutorial on how to build a Daikon like program invariant miner for Python.