为什么Clojure规范会进入无限循环?

为什么Clojure规范会进入无限循环?,clojure,clojure.spec,Clojure,Clojure.spec,这是一个将视觉模式表示为形状集合的应用程序 Sshape(styled shape)是点列表和样式信息地图 Apartern是包含形状列表的记录 以下是规格: 在sshape.clj中 (spec/def ::stroke-weight int?) (spec/def ::color (spec/* int?)) (spec/def ::stroke ::color) (spec/def ::fill ::color) (spec/def ::hidden boolean?) (spec/def

这是一个将视觉模式表示为形状集合的应用程序

Sshape(styled shape)是点列表和样式信息地图

Apartern是包含形状列表的记录

以下是规格:

在sshape.clj中

(spec/def ::stroke-weight int?)
(spec/def ::color (spec/* int?))
(spec/def ::stroke ::color)
(spec/def ::fill ::color)
(spec/def ::hidden boolean?)
(spec/def ::bezier boolean?)
(spec/def ::style (spec/keys :opt-un [::stroke-weight ::stroke ::fill ::hidden ::bezier]))
(spec/def ::point (spec/* number?))
(spec/def ::points (spec/* ::point))
(spec/def ::SShape (spec/keys :req-un [::style ::points]))
在groups.clj中

(spec/def ::sshapes (spec/* :patterning.sshapes/SShape))
(spec/def ::APattern (spec/keys :req-un [::sshapes]))
然后在另一个文件中,我尝试测试将两个参数放在一起的叠加函数是否接受参数

(defn superimpose-layout "simplest layout, two patterns located on top of each other "
  [pat1 pat2]
  {:pre [(spec/valid? :patterning.groups/APattern pat1)]}
  (->APattern (concat (:sshapes pat1) (:sshapes pat2)))   )
如果没有先决条件,这将运行

通过这个前置条件,我得到了这个无限递归和堆栈溢出

Exception in thread "main" java.lang.StackOverflowError, compiling:(/tmp/form-init7774655152686087762.clj:1:73)
    at clojure.lang.Compiler.load(Compiler.java:7526)
    at clojure.lang.Compiler.loadFile(Compiler.java:7452)
    at clojure.main$load_script.invokeStatic(main.clj:278)
    at clojure.main$init_opt.invokeStatic(main.clj:280)
    at clojure.main$init_opt.invoke(main.clj:280)
    at clojure.main$initialize.invokeStatic(main.clj:311)
    at clojure.main$null_opt.invokeStatic(main.clj:345)
    at clojure.main$null_opt.invoke(main.clj:342)
    at clojure.main$main.invokeStatic(main.clj:424)
    at clojure.main$main.doInvoke(main.clj:387)
    at clojure.lang.RestFn.applyTo(RestFn.java:137)
    at clojure.lang.Var.applyTo(Var.java:702)
    at clojure.main.main(main.java:37)
Caused by: java.lang.StackOverflowError
    at clojure.spec.alpha$regex_QMARK_.invokeStatic(alpha.clj:81)
    at clojure.spec.alpha$regex_QMARK_.invoke(alpha.clj:78)
    at clojure.spec.alpha$maybe_spec.invokeStatic(alpha.clj:108)
    at clojure.spec.alpha$maybe_spec.invoke(alpha.clj:103)
    at clojure.spec.alpha$the_spec.invokeStatic(alpha.clj:117)
    at clojure.spec.alpha$the_spec.invoke(alpha.clj:114)
    at clojure.spec.alpha$dt.invokeStatic(alpha.clj:742)
    at clojure.spec.alpha$dt.invoke(alpha.clj:738)
    at clojure.spec.alpha$dt.invokeStatic(alpha.clj:739)
    at clojure.spec.alpha$dt.invoke(alpha.clj:738)
    at clojure.spec.alpha$deriv.invokeStatic(alpha.clj:1480)
    at clojure.spec.alpha$deriv.invoke(alpha.clj:1474)
    at clojure.spec.alpha$deriv.invokeStatic(alpha.clj:1491)
    at clojure.spec.alpha$deriv.invoke(alpha.clj:1474)
    at clojure.spec.alpha$deriv.invokeStatic(alpha.clj:1491)
    at clojure.spec.alpha$deriv.invoke(alpha.clj:1474)
    at clojure.spec.alpha$deriv.invokeStatic(alpha.clj:1492)
    at clojure.spec.alpha$deriv.invoke(alpha.clj:1474)
    at clojure.spec.alpha$deriv.invokeStatic(alpha.clj:1492)
    at clojure.spec.alpha$deriv.invoke(alpha.clj:1474)
    at clojure.spec.alpha$deriv.invokeStatic(alpha.clj:1492)
等等

更新:

嗯。我在repl中缩小了范围

假设点的向量被定义为
pts

[[-0.3 -3.6739403974420595E-17] [1.3113417037298127E-8 -0.2999999999999997] [0.2999999999999989 2.6226834037856828E-8] [-3.934025103841547E-8 0.29999999999999744] [-0.3 -3.6739403974420595E-17]]
然后打电话

(spec/valid? :patterning.sshapes/points pts)
给我堆栈溢出:

StackOverflowError   clojure.spec.alpha/regex? (alpha.clj:81)
所以它看起来像是因为我试图匹配一个spec/*的spec/*的数字


嵌套向量触发这种无限递归有什么原因吗?

我相信Clojure规范在这方面有一些缺陷

这一个看起来像一个例子。在符合以下条件时触发:

(s/conform (s/* (s/* number?)) [[]])  ; => StackOverflowError

为此,您可能应该使用
spec/coll of
而不是
s/*

(s/def ::point (s/coll-of number?))
(s/def ::points (s/coll-of ::point))
(s/def ::SShape (s/keys :req-un [::style ::points]))
(s/exercise (s/coll-of ::SShape))
;; => ([[] []] [[{:style {:hidden false, :bezier false}, :points [[1.0 -3.0 0     0.75 -1.0 -1.0 0 -1.5 1.0 3.0 -1 0] [-2.0 -1 2.0 2.0 0 ...