Project description
A new type inference to meet future demands
All the data in a programme like Java or Scala is classified by its type (such as strings or integers). To inform compilers about the data types to check, programmers need to annotate programs. Type inference algorithms are necessary to transfer results from formal calculi to new programming languages. The EU-funded TypeFoundry project will use recent developments in proof theory and semantics (examples include polarised type theory and call-by-push-value) to identify the theoretical structure underpinning type inference. It will use this theory to build a collection of techniques for type inference capable of scaling up to advanced type system features in both modern and future languages.
Objective
"Many modern programming languages, whether developed in industry, like Rust or Java, or in academia, like Haskell or Scala, are typed. All the data in a program is classified by its type (e.g. as strings or integers), and at compile-time programs are checked for consistent usage of types, in a process called type checking. Thus, the expression 3 + 4 will be accepted, since the + operator takes two numbers as arguments, but the expression 3 + ""hello"" will be rejected, as it makes no sense to add a number and a string. Though this is a simple idea, sophisticated type system can track properties like algorithmic complexity, data-race freedom, differential privacy, and data abstraction.
In general, programmers must annotate programs to tell compilers the types to check. In theoretical calculi, it is easy to demand enough annotations to trivialize typechecking, but this can make the annotation burden unbearable: often larger than the program itself! So, to transfer results from formal calculi to new programming languages, we need type inference algorithms, which reconstruct missing data from partially-annotated programs.
However, the practice of type inference has outpaced its theory. Compiler authors have implemented many type inference systems, but the algorithms are often ad-hoc or folklore, and the specifications they are meant to meet are informal or nonexistent. The makes it hard to learn how to implement type inference, hard to build alternative implementations (whether for new compilers or analysis engines for IDEs), and hard for programmers to predict if refactorings will preserve typability.
In TypeFoundry, we will use recent developments in proof theory and semantics (like polarized type theory and call-by-push-value) to identify the theoretical structure underpinning type inference, and use this theory to build a collection of techniques for type inference capable of scaling up to the advanced type system features in both modern and future languages.
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Keywords
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Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC)
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Topic(s)
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Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
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Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
ERC-COG - Consolidator Grant
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Call for proposal
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(opens in new window) ERC-2020-COG
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CB2 1TN CAMBRIDGE
United Kingdom
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