Spec 39;s Mp3 Download

June 26, 2023: RG News - Nominations for the SPEC Kaivalya Dixit Distinguished Dissertation Award are now open to dissertations that have been defended between October 2021 and September 2023. A thesis can be nominated only once, which means that a 2022 thesis nominated in 2023 cannot be nominated again in 2024. Questions about the application process can be e-mailed to: nominations@spec.org.

In Clojure we gain power by dynamically composing,merging and building up maps. We routinely deal with optional and partial data, data produced by unreliableexternal sources, dynamic queries etc. These maps represent various sets, subsets, intersections and unionsof the same keys, and in general ought to have the same semantic for the same key wherever it is used. Definingspecifications of every subset/union/intersection, and then redundantly stating the semantic of each key is both anantipattern and unworkable in the most dynamic cases.

Download File 🔥 https://urluss.com/2y7OOO 🔥

Yet property based testing requires thedefinition of properties, which require extra effort and expertise to produce, and which,at the function-level, have substantial overlap with function specifications.Many interesting properties at the function level would already be captured by structural+predicative specs.Ideally, specs should integrate with generative testing and provide certain categories of generative tests 'for free'.

A specification is about how something 'looks', but is, most importantly, something that is looked at.Specs should be readable, composed of 'words' (predicate functions) programmers are already using,and integrated in documentation.

There is no reason to limit our specifications to what we can prove, yet that is primarily what type systems do.There is so much more we want to communicate and verify about our systems. This goes beyondstructural/representational types and tagging to predicates that e.g. narrow domains or detail relationshipsbetween inputs or between inputs and output.Additionally, the properties we care most about are often those of the runtime values, not some static notion.Thus spec is not a type system.

In Lisps (and thus Clojure), code is data. But data is not code until you define a language around it. Many DSLs inthis space drive at a data representation for schemas. But predicative specs have an open and large vocabulary,and most of the useful predicates already exist and are well known as functions in the core and other namespaces,or can be written as simple expressions. Having to 'datafy', possibly renaming, all of these predicates addslittle value, and has a definite cost in understanding precise semantics. spec instead leverages the fact thatthe original predicates and expressions are data in the first place and captures that data for use in communicatingwith the users in documentation and error reporting. Yes, this means that more of thesurface area of clojure.spec will be macros, but specs are overwhelmingly written by people and,when composed, manually so.

As per above, maps defining the details of the values at their keys is a fundamental complecting of concerns that willnot be supported. Map specs detail required/optional keys (i.e. set membership things) and keyword/attr/valuesemantics are independent. Map checking is two-phase, required key presence then key/value conformance.The latter can be done even when the (namespace-qualified) keys present at runtime are not in the map spec.This is vital for composition and dynamicity.

Invariably, people will try to use a specification system to detail implementation decisions, but they do soto their detriment. The best and most useful specs (and interfaces) are related to purely information aspects.Only information specs work over wires and across systems. We will always prioritize, andwhere there is a conflict, prefer, the information approach.

The generative testing underpinning of spec will leverage test.check and not reinvent it.But spec users should not need to know anything about test.check until and unless they want to write their owngenerators or supplement spec's generated tests with further property-based tests of their own. There should be noproduction runtime dependency on test.check.

The basic idea is that specs are nothing more than a logical composition of predicates. At the bottom we are talkingabout the simple boolean predicates you are used to like int? or symbol?, or expressions you build yourselflike #(< 42 % 66).spec adds logical ops like spec/and and spec/or which combine specs in a logical way and offer deep reporting,generation and conform support and, in the case of spec/or, tagged returns.

Specs for map keysets provide for the specification of required and optional key sets. A spec for a map isproduced by calling keys with :req and :opt keyword arguments mapping to vectors of key names.

One of the most visible differences between spec and other systems is that there is no place in that map spec forspecifying the values e.g. ::x can take. It is the (enforced) opinion of spec that the specification of valuesassociated with a namespaced keyword, like :my.ns/k, should be registered under that keyword itself,and applied in any map in which that keyword appears. There are a number of advantages to this:

This last point is vital when dynamically building up, composing, or generating maps. Creating a spec for every mapsubset/union/intersection is unworkable. It also facilitates fail-fast detection of bad data - when it is introducedvs when it is consumed.

This specs a map that requires the unqualified keys :a and :b but validates and generates them using specs(when defined) named :my.ns/a and :my.ns/b respectively. Note that this cannot convey the same powerto unqualified keywords as have namespaced keywords - the resulting maps are not self-describing.

Note that cat and alt require all of their components be labeled, and the return value of each is a map withthe keys corresponding to the matched components. In this way spec regexes act as destructuring and parsing tools.

The primary operations for defining specs are s/def, s/and, s/or, s/keys and the regex ops. There is a spec functionthat can takea predicate function or expression, a set, or a regex op, and can also take an optional generator which would overridethe generator implied by the predicate(s).

Note however, that def, and, or, keys spec fns and the regex ops can all take and use predicate functions and sets directly -and do not need them to be wrapped by spec. spec should only be needed when you want to override a generator or tospecify that a nested regex starts anew, vs being included in the same pattern.

In order for a spec to be reusable by name, it has to be registered via def.def takes a namespace-qualified keyword/symbol and a spec/predicate expression. By convention, specs for data shouldbe registered underkeywords and attribute values should be registered under their attribute name keyword. Once registered, the name canbe used anywhere a spec/predicate is called for in any of the spec operations.

The args spec for a fn is always going to be a regex that specs the arguments as if they were a list, i.e. thelist one would pass to apply the function. In this way, a single spec can handle functions with multiple arities.

The (optional) fn spec is a further specification of the relationship between the arguments and the return, i.e. thefunction of the function. It will be passed (e.g. during testing) a map containing{:args conformed-args :ret conformed-ret} and will generally contain predicates that relate those values - e.g. itcould ensure that all keys of an input map are present in the returned map.

You can selectively instrument functions and namespaces with instrument, which swaps outthe fn var with a wrapped version of the fn that tests the :args spec. unstrument returns a fn to itsoriginal version. You can generate data for interactive testing with gen/sample.

You can run a suite of spec-generative tests on an entire ns with check. You can get a test.check compatible generatorfor a spec by calling gen. There are built-in associations between many of the clojure.core data predicates and correspondinggenerators, and the composite ops of spec know how to build generators atop those. If you call gen on a spec and it isunable to construct a generator for some subtree, it will throw an exception that describes where. You can pass generator-returning fns tospec in order to supply generators for things spec does not know about, and you can pass an override map to gen in order to supplyalternative generators for one or more subpaths of a spec.

In addition to the destructuring use cases above, you can make calls to conform or valid? anywhere you wantruntime checking, and can make lighter-weight internal-only specs for tests you intend to run in production.

conform is the basic operation for consuming specs, and does both validation and conforming/destructuring.Note that conforming is 'deep' and flows through all of the spec and regex operations, map specs etc.Since nil and false are legitimate conformed values, conform returns the distinguished :clojure.spec.alpha/invalidwhen a value cannot be made to conform. valid? can be used instead as a fully-boolean predicate.

When a value fails to conform to a spec you can call explain or explain-data with the same spec+value tofind out why. These explanations are not produced during conform because they might perform additional work and thereis no reason to incur that cost for non-failing inputs or when no report is desired. An important component ofexplanations is the path. explain extends the path as it navigates through e.g. nested maps or regex patterns,so you get better information than just the entire or leaf value. explain-data will return a map of paths to problems.

Due to the fact that all branching points in specs are labeled, i.e. map keys, choices in or and alt, and(possibly elided) elements of cat, every subexpression in a spec can be referred to via a path (vector of keys) naming the parts.These paths are used in explain, gen overrides and various error reporting. 006ab0faaa