Validation of memory accesses through symbolic analyses

Nazaré, Henrique; Maffra, Izabela; Santos, Willer; Barbosa, Leonardo Valentino Soares; Gonnord, Laure; Pereira, Fernando Magno Quintão

doi:10.1145/2660193.2660205

Cited by 21 publications

(34 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…There is previous work that attempt to recognize programming events by means of border detection algorithms. This is, for instance, the approach of Silva et al [Silva et al (2014)], or Nazare et al [Nazaré et al (2014)]. The idea is simple: if we assume that the hardware consumes more energy when it runs a program, then we can expect an isolated, flat-topped hill on its energy skyline.…”

Section: Related Workmentioning

confidence: 99%

JetsonLEAP: A framework to measure power on a heterogeneous system-on-a-chip device

Bessa

Gull

Quintão

et al. 2019

Science of Computer Programming

View full text Add to dashboard Cite

Computer science marches towards energy-aware practices. This trend impacts not only the design of computer architectures, but also the design of programs. However, developers still lack affordable and accurate technology to measure energy consumption in computing systems. The goal of this paper is to mitigate such problem. To this end, we introduce JetsonLEAP, a framework that supports the implementation of energy-aware programs. Jet-sonLEAP consists of an embedded hardware, in our case, the Nvidia Tegra TK1 System-on-a-chip device, a circuit to control the flow of energy, of our own design, plus a library to instrument program parts. We discuss two different circuit setups. The most precise setup lets us reliably measure the energy spent by 225,000 instructions, the least precise, although more affordable setup, gives us a window of 975,000 instructions. To probe the precision of our system, we use it in tandem with a high-precision, high-cost acquisition system, and show that results do not differ in any significant way from those that we get using our simpler apparatus. Our entire infrastructure -board, power meter and both circuits -can be reproduced with about $500.00. To demonstrate the efficacy of our framework, we have used it to measure the energy consumed by programs running on ARM cores, on the GPU, and on a remote server. Furthermore, we have studied the impact of OpenACC directives on the energy efficiency of high-performance applications.

show abstract

Section: Related Workmentioning

confidence: 99%

JetsonLEAP: A framework to measure power on a heterogeneous system-on-a-chip device

Bessa

Gull

Quintão

et al. 2019

Science of Computer Programming

View full text Add to dashboard Cite

show abstract

“…Since such domains might not be determined in terms of integer constants only, we shall found their definition on the notion of symbolic ranges [4]. As we want to simplify state constraints the most, we define them in terms of the symbolic range algebra proposed by Nazaré et al [14]. Our definitions are nonetheless significantly different, even though inspired from their work.…”

Section: State Constraintsmentioning

confidence: 99%

“…State Constraints as Symbolic Ranges with Runtime Checks Symbolic ranges capture most minimal requirements over the C left-values of a function precondition: for integer typed left-values, a symbolic range represents the integer variation domain, while for pointer typed left-values, it represents a region of valid offsets. They are commonly used in abstract interpreters for range [7,13] and region analysis [14,18], respectively.…”

Section: Lattice Of Symbolic Expression Rangesmentioning

confidence: 99%

Context Generation from Formal Specifications for C Analysis Tools

Alberti¹,

Signoles

2018

Logic-Based Program Synthesis and Transformation

View full text Add to dashboard Cite

Analysis tools like abstract interpreters, symbolic execution tools and testing tools usually require a proper context to give useful results when analyzing a particular function. Such a context initializes the function parameters and global variables to comply with function requirements. However it may be error-prone to write it by hand: the handwritten context might contain bugs or not match the intended specification. A more robust approach is to specify the context in a dedicated specification language, and hold the analysis tools to support it properly. This may mean to put significant development efforts for enhancing the tools, something that is often not feasible if ever possible. This paper presents a way to systematically generate such a context from a formal specification of a C function. This is applied to a subset of the ACSL specification language in order to generate suitable contexts for the abstract interpretationbased value analysis plug-ins of Frama-C, a framework for analysis of code written in C. The idea here presented has been implemented in a new Frama-C plugin which is currently in use in an operational industrial setting.

show abstract

“…As an example, currently we do not associate size information with array types, they are made plain pointers like int*. Yet, current state-of-the-art symbolic range analysis, à la Nazaré et al [Nazaré et al 2014] should let us associate conservative size expressions with such type; hence, giving us int [42] or int [N+M], for instance. As another example of future work, it might be possible to establish guarantees about the dynamic semantics of the partial program to be reconstructed.…”

Section: Final Thoughtsmentioning

confidence: 99%

Inference of static semantics for incomplete C programs

Melo

Ribeiro

Araújo

et al. 2017

Proc. ACM Program. Lang.

View full text Add to dashboard Cite

Incomplete source code naturally emerges in software development: during the design phase, while evolving, testing and analyzing programs. Therefore, the ability to understand partial programs is a valuable asset. However, this problem is still unsolved in the C programming language. Difficulties stem from the fact that parsing C requires, not only syntax, but also semantic information. Furthermore, inferring types so that they respect C's type system is a challenging task. In this paper we present a technique that lets us solve these problems. We provide a unification-based type inference capable of dealing with C intricacies. The ideas we present let us reconstruct partial C programs into complete well-typed ones. Such program reconstruction has several applications: enabling static analysis tools in scenarios where software components may be absent; improving static analysis tools that do not rely on build-specifications; allowing stub-generation and testing tools to work on snippets; and assisting programmers on the extraction of reusable data-structures out of the program parts that use them. Our evaluation is performed on source code from a variety of C libraries such as GNU's Coreutils, GNULib, GNOME's GLib, and GDSL; on implementations from Sedgewick's books; and on snippets from popular open-source projects like CPython, FreeBSD, and Git.

show abstract

Validation of memory accesses through symbolic analyses

Cited by 21 publications

References 32 publications

JetsonLEAP: A framework to measure power on a heterogeneous system-on-a-chip device

JetsonLEAP: A framework to measure power on a heterogeneous system-on-a-chip device

Context Generation from Formal Specifications for C Analysis Tools

Inference of static semantics for incomplete C programs

Contact Info

Product

Resources

About