Dynamic languages such as Ruby, Python, and JavaScript have many compelling benefits, but the lack of static types means subtle errors can remain latent in code for a long time. While many researchers have developed various systems to bring some of the benefits of static types to dynamic languages, prior approaches have trouble dealing with metaprogramming, which generates code as the program executes. In this paper, we propose Hummingbird, a new system that uses a novel technique, just-in-time static type checking, to type check Ruby code even in the presence of metaprogramming. In Hummingbird, method type signatures are gathered dynamically at run-time, as those methods are created. When a method is called, Hummingbird statically type checks the method body against current type signatures. Thus, Hummingbird provides thorough static checks on a per-method basis, while also allowing arbitrarily complex metaprogramming. For performance, Hummingbird memoizes the static type checking pass, invalidating cached checks only if necessary. We formalize Hummingbird using a core, Ruby-like language and prove it sound. To evaluate Hummingbird, we applied it to six apps, including three that use Ruby on Rails, a powerful framework that relies heavily on metaprogramming. We found that all apps typecheck successfully using Hummingbird, and that Hummingbird’s performance overhead is reasonable. We applied Hummingbird to earlier versions of one Rails app and found several type errors that had been introduced and then fixed. Lastly, we demonstrate using Hummingbird in Rails development mode to typecheck an app as live updates are applied to it.
@cite_29 propose a system for type checking programs that use JQuery, a very sophisticated Javascript framework. The proposed type system has special support for JQuery's abstractions, making it quite effective in that domain. On the other hand, it does not easily apply to other frameworks.
@cite_29
2106355420 1760484232 2091335641 2003751975
This paper introduces the Checker Framework, which supports adding pluggable type systems to the Java language in a backward-compatible way. A type system designer defines type qualifiers and their semantics, and a compiler plug-in enforces the semantics. Programmers can write the type qualifiers in their programs and use the plug-in to detect or prevent errors. The Checker Framework is useful both to programmers who wish to write error-free code, and to type system designers who wish to evaluate and deploy their type systems. The Checker Framework includes new Java syntax for expressing type qualifiers; declarative and procedural mechanisms for writing type-checking rules; and support for flow-sensitive local type qualifier inference and for polymorphism over types and qualifiers. The Checker Framework is well-integrated with the Java language and toolset. We have evaluated the Checker Framework by writing 5 checkers and running them on over 600K lines of existing code. The checkers found real errors, then confirmed the absence of further errors in the fixed code. The case studies also shed light on the type systems themselves. The jQuery library defines a powerful query language for web applications' scripts to interact with Web page content. This language is exposed as jQuery's api, which is implemented to fail silently so that incorrect queries will not cause the program to halt. Since the correctness of a query depends on the structure of a page, discrepancies between the page's actual structure and what the query expects will also result in failure, but with no error traces to indicate where the mismatch occurred. This work proposes a novel type system to statically detect jQuery errors. The type system extends Typed JavaScript with local structure about the page and with multiplicities about the structure of containers. Together, these two extensions allow us to track precisely which nodes are active in a jQuery object, with minimal programmer annotation effort. We evaluate this work by applying it to sample real-world jQuery programs. Current proposals for adding gradual typing to JavaScript, such as Closure, TypeScript and Dart, forgo soundness to deal with issues of scale, code reuse, and popular programming patterns. We show how to address these issues in practice while retaining soundness. We design and implement a new gradual type system, prototyped for expediency as a 'Safe' compilation mode for TypeScript. Our compiler achieves soundness by enforcing stricter static checks and embedding residual runtime checks in compiled code. It emits plain JavaScript that runs on stock virtual machines. Our main theorem is a simulation that ensures that the checks introduced by Safe TypeScript (1) catch any dynamic type error, and (2) do not alter the semantics of type-safe TypeScript code. Safe TypeScript is carefully designed to minimize the performance overhead of runtime checks. At its core, we rely on two new ideas: differential subtyping, a new form of coercive subtyping that computes the minimum amount of runtime type information that must be added to each object; and an erasure modality, which we use to safely and selectively erase type information. This allows us to scale our design to full-fledged TypeScript, including arrays, maps, classes, inheritance, overloading, and generic types. We validate the usability and performance of Safe TypeScript empirically by type-checking and compiling around 120,000 lines of existing TypeScript source code. Although runtime checks can be expensive, the end-to-end overhead is small for code bases that already have type annotations. For instance, we bootstrap the Safe TypeScript compiler (90,000 lines including the base TypeScript compiler): we measure a 15 runtime overhead for type safety, and also uncover programming errors as type safety violations. We conclude that, at least during development and testing, subjecting JavaScript TypeScript programs to safe gradual typing adds significant value to source type annotations at a modest cost. Many data-intensive applications dynamically construct queries in response to client requests and execute them. Java servlets, for example, can create strings that represent SQL queries and then send the queries, using JDBC, to a database server for execution. The servlet programmer enjoys static checking via Java's strong type system. However, the Java type system does little to check for possible errors in the dynamically generated SQL query strings. Thus, a type error in a generated selection query (e.g., comparing a string attribute with an integer) can result in an SQL runtime exception. Currently, such defects must be rooted out through careful testing, or (worse) might be found by customers at runtime. In this article, we present a sound, static program analysis technique to verify that dynamically generated query strings do not contain type errors. We describe our analysis technique and provide soundness results for our static analysis algorithm. We also describe the details of a prototype tool based on the algorithm and present several illustrative defects found in senior software-engineering student-team projects, online tutorial examples, and a real-world purchase order system written by one of the authors.