Black-box transactional safety checker based on cycle detection
Isabelle · ClojureEPL-2.0★ 699 stars⑂ 40 forkssince Feb 2020View on GitHub ↗
jepsen-io/elle holds a health index of 52 out of 100, placing it in the Moderate band. It scores highest on Vitality (72/100) and lowest on AI Readiness (28/100). It was last updated 1 day ago. A single contributor accounts for most of its recent work.
52
overall / 100
Moderate
Software health index
Metrics are grouped into weighted categories on one standardized 1–100 scale. Overall starts as their weighted mean; when public evidence triggers the High-Risk Jurisdiction Policy, the rating is adjusted and receives an At risk ceiling of 49. AI Readiness sits outside the overall score.
52
Excellent85-100Exemplary; meets essentially all checked criteria
Good70-84Healthy; minor gaps
Moderate50-69Acceptable with notable gaps; review recommended
At risk30-49Significant weaknesses; adoption warrants caution
Critical1-29Severe problems (abandoned, single-maintainer, no hygiene)
Score profile
Each axis is a category. The shape matters more than the average — a healthy subject fills the whole shape, while a spike-and-crater profile means strength in one dimension is masking risk in another.
Excluded from scoring (no data or not applicable): dangerous_workflow, packaging, pinned_dependencies, signed_releases, token_permissions. Remaining weights renormalized.
How well is the repo equipped to be developed and maintained with AI coding agents? An independent, experimental badge — weight 0.0, so it is surfaced on its own and does not affect the overall health score.
Type-checkable code — Isabelle without a type-check config
55/55
Manageable file sizes — 0/2 source files over 60KB
Inputs used
primary_language
Isabelle
largest_source_bytes
11,147
source_files_sampled
2
oversized_source_files
0
Key facts
699GitHub stars
7contributors
31commits, last 12 months
1days since last push
16releases
1bus factor
7open issues
—package ecosystems
Data collection warnings
Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
More detail
Star and fork history 0 ★ / 40 ⇿
0Stars
40Forks
15Releases
When each star and fork was added, collected from GitHub and bucketed by day. Cumulative growth sits directly above the daily additions it is made of, so the two read against each other: steady organic accretion looks nothing like an abrupt, short-lived burst. Where that difference is measurable, it is reported as growth authenticity.
Major 0Minor 1Patch 14
Each point covers 6 days.
OpenSSF Scorecard 3.7 / 10
3.7aggregate
Independent, tool-agnostic security assessment from the open-source OpenSSF Scorecard. Each check rewards a security practice, not a specific vendor's tool. Checks Scorecard could not determine are marked n/a and excluded from the security score (never counted as zero).Scorecard v5.5.0 · 2026-07-23 09:46 UTC
Full resolved dependency set from the GitHub dependency graph: 0 direct and 0 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.
Registry
Package
Version
Relation
Dependency advisories not assessed
Advisory matching could not run for this report: No resolved dependencies to assess
Raw JSON report machine-readable
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"body": "We used to represent relationships as keywords or sets of keywords,\ne.g. :ww, #{:rw, :wr}. We now have a custom bitset representation,\nBitRels, which captures both a single rel and a set of rels in a single\nbyte, and provides primitive static functions for performing union,\nintersection, testing, et\n[…]\nstructing\nyour own relationship graphs, you'll need to name them using BitRels/WW,\nBitRels/REALTIME, etc., instead of :ww, :realtime, etc. You'll find\nconvenient references in the elle.rels namespace.",
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"body": "We burned a lot of time searching RelGraphs via Tarjan because the graph\nlazily computed vertices and out sets. We now perform this phase in\nparallel for a ~10% overall speedup on the sloppy list-append benchmark.",
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"headline": "txn: materialize graph before Tarjan search",
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"body": "When the BFS search finds a loop with a tail, it attempts to trim off\nthe tail and see if it can still find a loop in that subgraph.",
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"body": "These consistency levels correspond to strong/strong-session\nserializable, SI, etc. We already had G0-realtime and G1c-realtime\nanomalies, but now they actually mean something.\n\nThis also makes our anomaly search trimming process more efficient: if\nwe find no SCC in WW U RT, we can prove that it's unnecessary to check\nfor G0-realtime, and so on. Before we only trimmed G0 itself, not\nrealtime or process variants.",
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"body": "Had to patch some things in Bifurcan too, but we're now to the point\nwhere our RelGraphs actually use custom comparators throughout.",
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"headline": "RelGraph equality semantics are now preserved",
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"body": "We were burning tons of time in the cycle evaluator. This is a\nhand-optimized BFS search which supercedes all three of our previous\nsearch tactics, and is (presently) a tad faster. 50,000 ops/sec on the\nlist-append sloppy-perf-test.",
"is_bot": false,
"headline": "Work in progress: add a new elle.bfs cycle search algo",
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"body": "This adds a new, more precise, less informative, and more efficient\nphase to cycle detection in elle.txn. In addition to performing a series\nof BFS searches for specific exemplars of cycles, Elle now also computes\na series of graphs which must be acyclic under certain consistency\nmodels. For instanc\n[…]\napproximately 20%\nby adding this pass. We think it's still worth it. It catches several\nanomalies our test suite missed, and allows precise claims to be made in\nlinear, as opposed to exponential time.",
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"headline": "Add cycle-exists anomalies",
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"body": "Now that operation graphs directly support fast index-based hashing and\nequality, we can skip the graph renumbering process entirely.",
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"headline": "graph: remove graph renumbering.",
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"body": "Operations on op graphs are now significantly faster, thanks to custom\nequality semantics. This should hopefully let us get rid of graph\nrenumbering.",
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"headline": "Replace transaction graphs with index-based hash and equality",
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"headline": "rw-register: tweak iteration slightly, hoping for better perf",
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"body": "We use the severity order and implication graph to avoid checking for\n(e.g.) G0-realtime if we've already found a G0.",
"is_bot": false,
"headline": "txn: cycle search now skips implied anomalies",
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"body": "We now have a notion of sorting anomalies by implication and severity,\nwhich we'll use for guiding the search order in txn.",
"is_bot": false,
"headline": "consistency-model: move to DAGs, introduce severity ordering",
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"oid": "96dd4e54ba4dc9487905b54c44b6120f397355b7",
"body": "We used to specify cyclic anomalies in terms of first-rels/rest-rels,\nwrote out process and realtime variants of anomalies by hand, and\nchecked them by running a general-purpose cycle search, explaining the\nfound cycle, then filtering the explanation. This... worked, but it was\neasy to forget to upd\n[…]\nup.\n\nLater on it might be worth profiling this and rewriting the whole\npathstate system in Java. Transition functions, loop checks, and\npredicates could all be folded into PathState validity directly.",
"is_bot": false,
"headline": "txn: redesign core anomaly specifications and rewrite cycle search",
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"headline": "elle.txn: drop superfluous pmap for filtered graphs",
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"body": "We used to compute filtered graphs from the entire graph, then take each\nSCC and look for cycles in the whole graphs using just that SCC's\ntransactions. This meant we spent time materializing filtered graphs\nthat would never actually be used. This pulls the graph selection step\nall the way up: we fi\n[…]\nect, so there is no duplicated work. This also gets\nrid of the extra SCC arities for the various cycle-search routines in\ngraph: the graph IS the SCC. I'm also hopeful this gives improved\nparallelism.",
"is_bot": false,
"headline": "Txn: refactor cycle-search SCC partitioning approach",
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{
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{
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{
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{
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{
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{
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{
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{
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{
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"value": 55,
"inputs": {
"primary_language": "Isabelle",
"largest_source_bytes": 11147,
"source_files_sampled": 2,
"oversized_source_files": 0
},
"components": [
{
"key": "type_checkable_code",
"name": "Type-checkable code",
"detail": "Isabelle without a type-check config",
"points": 0,
"status": "missed",
"details": [
{
"code": "no_typecheck_config_language",
"params": {
"language": "Isabelle"
}
}
],
"max_points": 45
},
{
"key": "manageable_file_sizes",
"name": "Manageable file sizes",
"detail": "0/2 source files over 60KB",
"points": 55,
"status": "met",
"details": [
{
"code": "oversized_source_files",
"params": {
"kb": 60,
"sampled": 2,
"oversized": 0
}
}
],
"max_points": 55
}
]
}
],
"description": "How well is the repo equipped to be developed and maintained with AI coding agents? An independent, experimental badge — weight 0.0, so it is surfaced on its own and does not affect the overall health score."
}
],
"metrics_version": "1.13.0"
},
"warnings": [
"Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token"
],
"report_type": "repository",
"generated_at": "2026-07-23T09:46:47.458533Z",
"schema_version": "0.27.0",
"badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/j/jepsen-io/elle.svg",
"full_name": "jepsen-io/elle",
"license_state": "standard",
"license_spdx": "EPL-2.0"
}
Scores are signals, not warranties. They reflect publicly visible practices on GitHub — not a code audit, and not a security guarantee.
Missing data is excluded and weights renormalized, never scored as zero. Methodology is versioned and open: metrics v1.13.0, schema v0.27.0 — full methodology · metrics wiki.
