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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.

Modular Product Programs

Many interesting program properties like determinism or information flow security are hyperproperties, that is, they relate multiple executions of the same program. Hyperproperties can be verified using relational logics, but these logics require dedicated tool support and are difficult to automate. Alternatively, constructions such as self-composition represent multiple executions of a program by one product program, thereby reducing hyperproperties of the original program to trace properties of the product. However, existing constructions do not fully support procedure specifications, for instance, to derive the determinism of a caller from the determinism of a callee, making verification non-modular. We present modular product programs, a novel kind of product program that permits hyperproperties in procedure specifications and, thus, can reason about calls modularly. We provide a general formalization of our product construction and prove it sound and complete. We demonstrate its expressiveness by applying it to information flow security with advanced features such as declassification and termination-sensitivity. Modular product programs can be verified using off-the-shelf verifiers; we have implemented our approach for both secure information flow and general hyperproperties using the Viper verification infrastructure. Our evaluation demonstrates that modular product programs can be used to prove hyperproperties for challenging examples in reasonable time.

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.

On the Impact of Programming Languages on Code Quality

This paper is a reproduction of work by Ray et al. which claimed to have uncovered a statistically significant association between eleven programming languages and software defects in projects hosted on GitHub. First we conduct an experimental repetition, repetition is only partially successful, but it does validate one of the key claims of the original work about the association of ten programming languages with defects. Next, we conduct a complete, independent reanalysis of the data and statistical modeling steps of the original study. We uncover a number of flaws that undermine the conclusions of the original study as only four languages are found to have a statistically significant association with defects, and even for those the effect size is exceedingly small. We conclude with some additional sources of bias that should be investigated in follow up 9 work and a few best practice recommendations for similar efforts.

Non-polynomial Worst-Case Analysis of Recursive Programs

We study the problem of developing efficient approaches for proving worst-case bounds of non-deterministic recursive programs. Ranking functions are sound and complete for proving termination and worst-case bounds of non-recursive programs. First, we apply ranking functions to recursion, resulting in measure functions. We show that measure functions provide a sound and complete approach to prove worst-case bounds of non-deterministic recursive programs. Our second contribution is the synthesis of measure functions in non-polynomial forms. We show that non-polynomial measure functions with logarithm and exponentiation can be synthesized through abstraction of logarithmic or exponentiation terms, Farkas' Lemma, and Handelman's Theorem using linear programming. While previous methods obtain polynomial worst-case bounds, our approach can synthesize bounds of various forms including $\mathcal{O}(n \log n)$ and $\mathcal{O}(n^r)$ where $r$ is not an integer. We present experimental results to demonstrate that our approach can efficiently obtain worst-case bounds of classical recursive algorithms such as (i)~Merge sort, Heap sort and the divide-and-conquer algorithm for the Closest Pair problem, where we obtain $\mathcal{O}(n \log n)$ worst-case bound, and (ii)~Karatsuba's algorithm for polynomial multiplication and Strassen's algorithm for matrix multiplication, for which we obtain $\mathcal{O}(n^r)$ bounds such that $r$ is not an integer and is close to the best-known bound for the respective algorithm. Besides the ability to synthesize non-polynomial bounds, we also show that our approach is equally capable of obtaining polynomial worst-case bounds for classical programs such as Quick sort and the dynamic programming algorithm for computing Fibonacci numbers.

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.

Environmental bisimulations for probabilistic higher-order languages

Environmental bisimulations for probabilistic higher-order languages are studied. In contrast with applicative bisimulations, environmental bisimulations are known to be more robust and do not require sophisticated techniques such as Howes in the proofs of congruence. As representative calculi, call-by-name and call-by-value »-calculus, and a (call-by-value) »-calculus extended with references (i.e., a store) are considered. In each case full abstraction results are derived for probabilistic environmental similarity and bisimilarity with respect to contextual preorder and contextual equivalence, respectively. Some possible enhancements of the (bi)simulations, as up-to techniques, are also presented. Probabilities force a number of modifications to the definition of environmental bisimulations in non-probabilistic languages. Some of these modifications are specific to probabilities, others may be seen as general refinements of environmental bisimulations, applicable also to non-probabilistic languages. Several examples are presented, to illustrate the modifications and the differences.

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