Browsing by Author "Melo, Leandro T. C."

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    Inference of static semantics for incomplete C programs.
    (2018) Melo, Leandro T. C.; Ribeiro, Rodrigo Geraldo; Araújo, Marcos Roberto de; Pereira, Fernando Magno Quintao
    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.
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    Type inference for C : applications to the static analysis of incomplete programs.
    (2020) Melo, Leandro T. C.; Ribeiro, Rodrigo Geraldo; Guimarães, Breno Campos Ferreira; Pereira, Fernando Magno Quintao
    Type inference is a feature that is common to a variety of programming languages. While, in the past, it has been prominently present in functional ones (e.g., ML and Haskell), today, many object-oriented/ multi-paradigm languages such as C# and C++ offer, to a certain extent, such a feature. Nevertheless, type inference still is an unexplored subject in the realm of C. In particular, it remains open whether it is possible to devise a technique that encompasses the idiosyncrasies of this language. The first difficulty encountered when tackling this problem is that parsing C requires, not only syntactic, but also semantic information. Yet, greater challenges emerge due to C’s intricate type system. In this work, we present a unification-based framework that lets us infer the missing struct, union, enum, and typedef declarations in a program. As an application of our technique, we investigate the reconstruction of partial programs. Incomplete source code naturally appears in software development: during design and while evolving, testing, and analyzing programs; therefore, understanding it is a valuable asset. With a reconstructed well-typed program, one can: (i) enable static analysis tools in scenarios where components are absent; (ii) improve precision of “zero setup” static analysis tools; (iii) apply stub generators, symbolic executors, and testing tools on code snippets; and (iv) provide engineers with an assortment of compilable benchmarks for performance and correctness validation. We evaluate our technique on code from a variety of C libraries, including GNU’s Coreutils and on snippets from popular projects such as CPython, FreeBSD, and Git.