Context-sensitive points-to analysis is valuable for achieving high precision with good performance. The standard flavors of contextsensitivity are call-site-sensitivity (kCFA) and object-sensitivity. Combining both flavors of context-sensitivity increases precision but at an infeasibly high cost. We show that a selective combination of call-site-and object-sensitivity for Java points-to analysis is highly profitable. Namely, by keeping a combined context only when analyzing selected language features, we can closely approximate the precision of an analysis that keeps both contexts at all times. In terms of speed, the selective combination of both kinds of context not only vastly outperforms non-selective combinations but is also faster than a mere object-sensitive analysis. This result holds for a large array of analyses (e.g., 1-object-sensitive, 2-object-sensitive with a context-sensitive heap, type-sensitive) establishing a new set of performance/precision sweet spots.
We present the TIC (Transactions with Isolation and Cooperation) model for concurrent programming. TIC adds to standard transactional memory the ability for a transaction to observe the effects of other threads at selected points. This allows transactions to cooperate, as well as to invoke nonrepeatable or irreversible operations, such as I/O. Cooperating transactions run the danger of exposing intermediate state and of having other threads change the transaction's state. The TIC model protects against unanticipated interference by having the type system keep track of all operations that may (transitively) violate the atomicity of a transaction and require the programmer to establish consistency at appropriate points. The result is a programming model that is both general and simple. We have used the TIC model to re-engineer existing lock-based applications including a substantial multi-threaded web mail server and a memory allocator with coarse-grained locking. Our experience confirms the features of the TIC model: It is convenient for the programmer, while maintaining the benefits of transactional memory.
Recently, language extensions have been proposed for Java and C# to support pattern-based reflective declaration. These extensions introduce a disciplined form of meta-programming and aspectoriented programming to mainstream languages: They allow members of a class (i.e., fields and methods) to be declared by statically iterating over and pattern-matching on members of other classes. Such techniques, however, have been unable to safely express simple, but common, idioms such as declaring getter and setter methods for fields.In this paper, we present a mechanism that addresses the lack of expressiveness in past work without sacrificing safety. Our technique is based on the idea of nested patterns that elaborate the outer-most pattern with blocking or enabling conditions. We implemented this mechanism in a language, MorphJ. We demonstrate the expressiveness of MorphJ with real-world applications. In particular, the MorphJ reimplementation of DSTM2, a software transactional memory library, reduces 1,107 lines of Java reflection and bytecode engineering library calls to just 374 lines of MorphJ code. At the same time, the MorphJ solution is both high level and safer, as MorphJ can separately type check generic classes and catch errors early. We present and formalize the MorphJ type system, and offer a type-checking algorithm.
Stream processing is mainstream (again): Widely-used stream libraries are now available for virtually all modern OO and functional languages, from Java to C# to Scala to OCaml to Haskell. Yet expressivity and performance are still lacking. For instance, the popular, well-optimized Java 8 streams do not support the zip operator and are still an order of magnitude slower than hand-written loops. We present the first approach that represents the full generality of stream processing and eliminates overheads, via the use of staging. It is based on an unusually rich semantic model of stream interaction. We support any combination of zipping, nesting (or flat-mapping), sub-ranging, filtering, mapping—of finite or infinite streams. Our model captures idiosyncrasies that a programmer uses in optimizing stream pipelines, such as rate differences and the choice of a “for” vs. “while” loops. Our approach delivers hand-written–like code, but automatically. It explicitly avoids the reliance on black-box optimizers and sufficiently-smart compilers, offering highest, guaranteed and portable performance. Our approach relies on high-level concepts that are then readily mapped into an implementation. Accordingly, we have two distinct implementations: an OCaml stream library, staged via MetaOCaml, and a Scala library for the JVM, staged via LMS. In both cases, we derive libraries richer and simultaneously many tens of times faster than past work. We greatly exceed in performance the standard stream libraries available in Java, Scala and OCaml, including the well-optimized Java 8 streams.
This paper describes FC++: a rich library supporting functional programming in C++. Prior approaches to encoding higher order functions in C++ have suffered with respect to polymorphic functions from either lack of expressiveness or high complexity. In contrast, FC++ offers full and concise support for higher-order polymorphic functions through a novel use of C++ type inference.Another new element in FC++ is that it implements a subtype polymorphism policy for functions, in addition to the more common parametric polymorphism facilities. Subtype polymorphism is common in object oriented languages and ensures that functions in FC++ fit well within the C++ object model.Apart from these conceptual differences, FC++ is also an improvement in technical terms over previous efforts in the literature. Our function objects are reference-counted and can be aliased without needing to be copied, resulting in an efficient implementation. The reference-counting mechanism is also exported to the user as a general-purpose replacement of native C++ pointers. Finally, we supply a number of useful functional operators (a large part of the Haskell Standard Prelude) to facilitate programming with FC++. The end result is a library that is usable and efficient, while requiring no extensions to the base C++ language.
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