Benefits of Session Types for software Development

Session types are a formalism used to specify and check the correctness of communication based systems. Within their scope, they can guarantee the absence of communication errors such as deadlock, sending an unexpected message or failing to handle an incoming message. Introduced over two decades ago, they have developed into a significant theme in programming languages. In this paper we examine the beliefs that drive research into this area and make it popular. We look at the claims and motivation behind session types throughout the literature. We identify the hypotheses upon which session types have been designed and implemented, and attempt to clarify and formulate them in a more suitable manner for testing

An Approach to Static Performance Guarantees for Programs with Run-time Checks

Instrumenting programs for performing run-time checking of properties, such as regular shapes, is a common and useful technique that helps programmers detect incorrect program behaviors. This is specially true in dynamic languages such as Prolog. However, such run-time checks inevitably introduce run-time overhead (in execution time, memory, energy, etc.). Several approaches have been proposed for reducing such overhead, such as eliminating the checks that can statically be proved to always succeed, and/or optimizing the way in which the (remaining) checks are performed. However, there are cases in which it is not possible to remove all checks statically (e.g., open libraries which must check their interfaces, complex properties, unknown code, etc.) and in which, even after optimizations, these remaining checks still may introduce an unacceptable level of overhead. It is thus important for programmers to be able to determine the additional cost due to the run-time checks and compare it to some notion of admissible cost. The common practice used for estimating run-time checking overhead is profiling, which is not exhaustive by nature. Instead, we propose a method that uses static analysis to estimate such overhead, with the advantage that the estimations are functions parameterized by input data sizes. Unlike profiling, this approach can provide guarantees for all possible execution traces, and allows assessing how the overhead grows as the size of the input grows. Our method also extends an existing assertion verification framework to express "admissible" overheads, and statically and automatically checks whether the instrumented program conforms with such specifications. Finally, we present an experimental evaluation of our approach that suggests that our method is feasible and promising.Comment: 15 pages, 3 tables; submitted to ICLP'18, accepted as technical communicatio

Exploiting Term Hiding to Reduce Run-time Checking Overhead

One of the most attractive features of untyped languages is the flexibility in term creation and manipulation. However, with such power comes the responsibility of ensuring the correctness of these operations. A solution is adding run-time checks to the program via assertions, but this can introduce overheads that are in many cases impractical. While static analysis can greatly reduce such overheads, the gains depend strongly on the quality of the information inferred. Reusable libraries, i.e., library modules that are pre-compiled independently of the client, pose special challenges in this context. We propose a technique which takes advantage of module systems which can hide a selected set of functor symbols to significantly enrich the shape information that can be inferred for reusable libraries, as well as an improved run-time checking approach that leverages the proposed mechanisms to achieve large reductions in overhead, closer to those of static languages, even in the reusable-library context. While the approach is general and system-independent, we present it for concreteness in the context of the Ciao assertion language and combined static/dynamic checking framework. Our method maintains the full expressiveness of the assertion language in this context. In contrast to other approaches it does not introduce the need to switch the language to a (static) type system, which is known to change the semantics in languages like Prolog. We also study the approach experimentally and evaluate the overhead reduction achieved in the run-time checks.Comment: 26 pages, 10 figures, 2 tables; an extension of the paper version accepted to PADL'18 (includes proofs, extra figures and examples omitted due to space reasons

Gradual structuring: Evolving the spreadsheet paradigm for expressiveness and learnability

© 2016 IEEE. Spreadsheets are arguably the most used form of programming and are frequently used in higher education to teach fundamental concepts about computation. Their success has shown that they are simple enough for a huge number of end users to learn and use. This is in contrast to traditional programming languages and the high dropout rate from introductory programming and computer science. However in comparison to traditional programming languages and structured modelling, spreadsheets are not expressive, placing a limit on the levels of computational thinking that can be taught using the spreadsheet paradigm. This limitation is imposed by the lack of programming language features and abstractions in the paradigm. Furthermore, more advanced spreadsheet features (e.g. array formulae, lookup formulae, R1C1 syntax) can be difficult to learn and use. This paper discusses the idea of adding language features to spreadsheets, enabling the gradual structuring of free-form spreadsheets to more structured models. We propose that this concept is termed Gradual Structuring, and is analogous to the programming language concept of gradual typing. In this analogy, spreadsheets take the place of dynamic programming and structured modelling of static programming. In programming languages, gradual typing allows dynamic programming to be mixed with static programming. It is our contention that dynamic programming is more learnable while static programming is more expressive and abstract. Gradual typing could be used to mitigate the issues in the teaching of traditional programming. Likewise Gradual Structuring can mitigate the conceptual limits that can be taught using current spreadsheets. The key language feature required to enable Gradual Structuring is the ability to logically group cells together so that a single formula can be applied to the grouped cells. This concept, termed cell grouping diminishes and can even eliminate the need for the ubiquitous and error-prone use of copy-pasted in spreadsheets. Moreover, it makes the structure present in spreadsheet models explicit. Cell grouping requires a cascade of other new languages features. Namely a more expressive referencing style, which in turned requires enabling labels to be moved to the row and column headers, and the hierarchical structuring of these headers. Respectively these language features are termed enhanced referencing and semantic axes. The ongoing research focusses on the usability and learnability of these language features. Spreadsheet applications exist that contain aspects of the features mentioned. However these applications do not enable Gradual Structuring and have taken a mainly technical, not human behavioural, approach to evolving the spreadsheet

Refinement type contracts for verification of scientific investigative software

Our scientific knowledge is increasingly built on software output. User code which defines data analysis pipelines and computational models is essential for research in the natural and social sciences, but little is known about how to ensure its correctness. The structure of this code and the development process used to build it limit the utility of traditional testing methodology. Formal methods for software verification have seen great success in ensuring code correctness but generally require more specialized training, development time, and funding than is available in the natural and social sciences. Here, we present a Python library which uses lightweight formal methods to provide correctness guarantees without the need for specialized knowledge or substantial time investment. Our package provides runtime verification of function entry and exit condition contracts using refinement types. It allows checking hyperproperties within contracts and offers automated test case generation to supplement online checking. We co-developed our tool with a medium-sized ($\approx$3000 LOC) software package which simulates decision-making in cognitive neuroscience. In addition to helping us locate trivial bugs earlier on in the development cycle, our tool was able to locate four bugs which may have been difficult to find using traditional testing methods. It was also able to find bugs in user code which did not contain contracts or refinement type annotations. This demonstrates how formal methods can be used to verify the correctness of scientific software which is difficult to test with mainstream approaches

Migratory Typing: Ten Years Later

In this day and age, many developers work on large, untyped code repositories. Even if they are the creators of the code, they notice that they have to figure out the equivalent of method signatures every time they work on old code. This step is time consuming and error prone. Ten years ago, the two lead authors outlined a linguistic solution to this problem. Specifically they proposed the creation of typed twins for untyped programming languages so that developers could migrate scripts from the untyped world to a typed one in an incremental manner. Their programmatic paper also spelled out three guiding design principles concerning the acceptance of grown idioms, the soundness of mixed-typed programs, and the units of migration. This paper revisits this idea of a migratory type system as implemented for Racket. It explains how the design principles have been used to produce the Typed Racket twin and presents an assessment of the project\u27s status, highlighting successes and failures