Project description DEENESFRITPL 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. Show the project objective Hide the project objective 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. " Programme(s) H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC) Main Programme Topic(s) ERC-2020-COG - ERC CONSOLIDATOR GRANTS Call for proposal ERC-2020-COG See other projects for this call Funding Scheme ERC-COG - Consolidator Grant Coordinator THE CHANCELLOR MASTERS AND SCHOLARS OF THE UNIVERSITY OF CAMBRIDGE Net EU contribution € 1 999 998,00 Address Trinity lane the old schools CB2 1TN Cambridge GB See on map Region East of England East Anglia Cambridgeshire CC Activity type Higher or Secondary Education Establishments Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Other funding € 0,00 Beneficiaries (1) Sort alphabetically Sort by Net EU contribution Expand all Collapse all THE CHANCELLOR MASTERS AND SCHOLARS OF THE UNIVERSITY OF CAMBRIDGE GB Net EU contribution € 1 999 998,00 Address Trinity lane the old schools CB2 1TN Cambridge See on map Region East of England East Anglia Cambridgeshire CC Activity type Higher or Secondary Education Establishments Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Other funding € 0,00
