The C programming language does not prevent out-ofbounds memory accesses. There exist several techniques to secure C programs; however, these methods tend to slow down these programs substantially, because they populate the binary code with runtime checks. To deal with this problem, we have designed and tested two static analyses -symbolic region and range analysis -which we combine to remove the majority of these guards. In addition to the analyses themselves, we bring two other contributions. First, we describe live range splitting strategies that improve the efficiency and the precision of our analyses. Secondly, we show how to deal with integer overflows, a phenomenon that can compromise the correctness of static algorithms that validate memory accesses. We validate our claims by incorporating our findings into AddressSanitizer. We generate SPEC CINT 2006 code that is 17% faster and 9% more energy efficient than the code produced originally by this tool. Furthermore, our approach is 50% more effective than Pentagons, a stateof-the-art analysis to sanitize memory accesses.

Simultaneous use of multiple programming languages (polyglot programming) assists in creating efficient, coherent, modern programs in the face of legacy code. However, manually creating bindings to low-level languages like C is tedious and error-prone. We offer relief in the form of an automated suite of analyses, designed to enhance the quality of automatically produced bindings. These analyses recover high-level array length information that is missing from C's type system. We emit annotations in the style of GObject-Introspection, which produces bindings from annotations on function signatures. We annotate each array argument as terminated by a special sentinel value, fixed-length, or of length determined by another argument. These properties help produce more idiomatic, efficient bindings. We correctly annotate at least 70% of all arrays with these length types, and our results are comparable to those produced by human annotators, but take far less time to produce. CCS Concepts •Software and its engineering → Automated static analysis; Software libraries and repositories; Data types and structures; Software maintenance tools; •Theory of computation → Type structures; Pattern matching;

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Software Security is key for the overall security of information systems. Day by day, more and more software exploitations happen and thus Software Security increasingly relevant. At the same time, Embedded Systems are becoming not only ubiquitous but also pervasive. As a result, it is paramount that those systems are secured. The problem, however, is that existing solutions -as is -are inadequate to Embedded Systems. This course therefore aims at giving an overview on the state-of-the-art of Software Security and, subsequently, show how these solutions can be adapted and evaluated in the context of Embedded Systems. ResumoSegurança de Software é um tema central na segurança de sistemas como um todo. Ataques que exploram vulnerabilidades em código são cada vez mais frequentes e Segurança de Software, então, é cada vez mais relevante. Paralelamente, Sistemas Embarcados fazem cada vez mais parte de nossas vidas e tendem a se tornar, na prática, onipresentes. Assim sendo, a segurança desses dispositivos é de suma importância. As propostas de

The C programming language does not prevent out-ofbounds memory accesses. There exist several techniques to secure C programs; however, these methods tend to slow down these programs substantially, because they populate the binary code with runtime checks. To deal with this problem, we have designed and tested two static analyses-symbolic region and range analysis-which we combine to remove the majority of these guards. In addition to the analyses themselves, we bring two other contributions. First, we describe live range splitting strategies that improve the efficiency and the precision of our analyses. Secondly, we show how to deal with integer overflows, a phenomenon that can compromise the correctness of static algorithms that validate memory accesses. We validate our claims by incorporating our findings into AddressSanitizer. We generate SPEC CINT 2006 code that is 17% faster and 9% more energy efficient than the code produced originally by this tool. Furthermore, our approach is 50% more effective than Pentagons, a stateof-the-art analysis to sanitize memory accesses.