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Higher-order Demand-driven Program Analysis

Developing accurate and efficient program analyses for languages with higher-order functions is known to be difficult. Here we define a new higher-order program analysis, Demand-Driven Program Analysis (DDPA), which extends well-known demand-driven lookup techniques found in first-order program analyses to higher-order programs. This task presents... (more)

Failure Recovery in Resilient X10

Cloud computing has made the resources needed to execute large-scale in-memory distributed computations widely available. Specialized programming models, e.g., MapReduce, have emerged to offer transparent fault tolerance and fault recovery for specific computational patterns, but they sacrifice... (more)

PYE: A Framework for Precise-Yet-Efficient Just-In-Time Analyses for Java Programs

Languages like Java and C# follow a two-step process of compilation: static compilation and just-in-time (JIT) compilation. As the time spent in JIT compilation gets added to the execution-time of the application, JIT compilers typically sacrifice the precision of program analyses for efficiency. The alternative of performing the analysis for... (more)

Combinatorial Register Allocation and Instruction Scheduling

This article introduces a combinatorial optimization approach to register allocation and instruction scheduling, two central compiler problems.... (more)

Static Identification of Injection Attacks in Java

The most dangerous security-related software errors, according to the OWASP Top Ten 2017 list, affect web applications. They are potential injection attacks that exploit user-provided data to execute undesired operations: database access and updates (SQL injection); generation of malicious web pages (cross-site scripting injection); redirection to user-specified web pages (redirect injection); execution of OS commands and arbitrary scripts (command injection); loading of user-specified, possibly... (more)

Analysis and Optimization of Task Granularity on the Java Virtual Machine

Task granularity, i.e., the amount of work performed by parallel tasks, is a key performance attribute of parallel applications. On the one hand,... (more)

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Forthcoming Articles
Behavioural Equivalence via Modalities for Algebraic Effects

The paper investigates behavioural equivalence between programs in a call-by-value functional language extended with a signature of (algebraic) effect-triggering operations. Two programs are considered as being behaviourally equivalent if they enjoy the same behavioural properties. To formulate this, we define a logic whose formulas specify behavioural properties. A crucial ingredient is a collection of \emph{modalities} expressing effect-specific aspects of behaviour. We give a general theory of such modalities. If two conditions, \emph{openness} and \emph{decomposability}, are satisfied by the modalities then the logically specified behavioural equivalence coincides with a modality-defined notion of applicative bisimilarity, which can be proven to be a congruence by a generalisation of Howe's method. We show that the openness and decomposability conditions hold for several examples of algebraic effects: nondeterminism, probabilistic choice, global store and input/output.

Reasoning About a Machine with Local Capabilities: Provably Safe Stack and Return Pointer Management

Capability machines provide security guarantees at machine level which makes them an interesting target for secure compilation schemes that provably enforce properties such as control-flow correctness and encapsulation of local state. We provide a formalization of a representative capability machine with local capabilities and study a novel calling convention. We provide a logical relation that semantically captures the guarantees provided by the hardware (a form of capability safety) and use it to prove control-flow correctness and encapsulation of local state. The logical relation is not specific to our calling convention and can be used to reason about arbitrary programs.

Faster Algorithms for Dynamic Algebraic Queries in Basic RSMs with Constant Treewidth

Interprocedural analysis is at the heart of numerous applications in programming languages, such as alias analysis, constant propagation, etc. Recursive state machines (RSMs) are standard models for interprocedural analysis. We consider a general framework with RSMs where the transitions are labeled from a semiring, and path properties are algebraic with semiring operations. RSMs with algebraic path properties can model interprocedural dataflow analysis problems, the shortest path problem, the most probable path problem, etc. The traditional algorithms for interprocedural analysis focus on path properties where the starting point is fixed as the entry point of a specific method. In this work, we consider possible multiple queries as required in many applications such as in alias analysis. The study of multiple queries allows us to bring in a very important algorithmic distinction between the resource usage of the one-time preprocessing vs for each individual query. The second aspect that we consider is that the control flow graphs for most programs have constant treewidth. Our main contributions are simple and implementable algorithms that support multiple queries for algebraic path properties for RSMs that have constant treewidth. Our theoretical results show that our algorithms have small additional one-time preprocessing, but can answer subsequent queries significantly faster as compared to the current best-known solutions for several important problems, such as interprocedural reachability and shortest path. We provide a prototype implementation for interprocedural reachability and intraprocedural shortest path that gives a significant speed-up on several benchmarks.

Special Issue Dedicated to ESOP 2018 Editorial

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