Static program analysis for string manipulation languages

In recent years, dynamic languages, such as JavaScript or Python, have been increasingly used in a wide range of fields and applications. Their tricky and misunderstood behaviors pose a hard challenge for static analysis of these programming languages. A key aspect of any dynamic language program is the multiple usage of strings, since they can be implicitly converted to another type value, transformed by string-to-code primitives or used to access an object-property. Unfortunately, string analyses for dynamic languages still lack precision and do not take into account some important string features. Moreover, string obfuscation is very popular in the context of dynamic language malicious code, for example, to hide code information inside strings and then to dynamically transform strings into executable code. In this scenario, more precise string analyses become a necessity. This paper is placed in the context of static string analysis by abstract interpretation and proposes a new semantics for string analysis, placing a first step for handling dynamic languages string features

Static Analysis for ECMAScript String Manipulation Programs

In recent years, dynamic languages, such as JavaScript or Python, have been increasingly used in a wide range of fields and applications. Their tricky and misunderstood behaviors pose a great challenge for static analysis of these languages. A key aspect of any dynamic language program is the multiple usage of strings, since they can be implicitly converted to another type value, transformed by string-to-code primitives or used to access an object-property. Unfortunately, string analyses for dynamic languages still lack precision and do not take into account some important string features. In this scenario, more precise string analyses become a necessity. The goal of this paper is to place a first step for precisely handling dynamic language string features. In particular, we propose a new abstract domain approximating strings as finite state automata and an abstract interpretation-based static analysis for the most common string manipulating operations provided by the ECMAScript specification. The proposed analysis comes with a prototype static analyzer implementation for an imperative string manipulating language, allowing us to show and evaluate the improved precision of the proposed analysis

Static analysis for ECMAscript string manipulation programs

In recent years, dynamic languages, such as JavaScript or Python, have been increasingly used in a wide range of fields and applications. Their tricky and misunderstood behaviors pose a great challenge for static analysis of these languages. A key aspect of any dynamic language program is the multiple usage of strings, since they can be implicitly converted to another type value, transformed by string-to-code primitives or used to access an object-property. Unfortunately, string analyses for dynamic languages still lack precision and do not take into account some important string features. In this scenario, more precise string analyses become a necessity. The goal of this paper is to place a first step for precisely handling dynamic language string features. In particular, we propose a new abstract domain approximating strings as finite state automata and an abstract interpretation-based static analysis for the most common string manipulating operations provided by the ECMAScript specification. The proposed analysis comes with a prototype static analyzer implementation for an imperative string manipulating language, allowing us to show and evaluate the improved precision of the proposed analysis

From types to type requirements: Genericity for model-driven engineering

The final publication is available at Springer via http://dx.doi.org/10.1007/s10270-011-0221-0Model-driven engineering (MDE) is a software engineering paradigm that proposes an active use of models during the development process. This paradigm is inherently type-centric, in the sense that models and their manipulation are defined over the types of specific meta-models. This fact hinders the reuse of existing MDE artefacts with other meta-models in new contexts, even if all these meta-models share common characteristics. To increase the reuse opportunities of MDE artefacts, we propose a paradigm shift from type-centric to requirement-centric specifications by bringing genericity into models, meta-models and model management operations. For this purpose, we introduce so-called concepts gathering structural and behavioural requirements for models and meta-models. In this way, model management operations are defined over concepts, enabling the application of the operations to any meta-model satisfying the requirements imposed by the concept. Model templates rely on concepts to define suitable interfaces, hence enabling the definition of reusable model components. Finally, similar to mixin layers, templates can be defined at the meta-model level as well, to define languages in a modular way, as well as layers of functionality to be plugged-in into other meta-models. These ideas have been implemented in MetaDepth, a multi-level meta-modelling tool that integrates action languages from the Epsilon family for model management and code generation.This work has been sponsored by the Spanish Ministry of Science and Innovation with projects METEORIC (TIN2008-02081) and Go Lite (TIN2011-24139), and by the R&D program of the Community of Madrid with project “e-Madrid” (S2009/TIC-1650)

Static Program Analysis for String Manipulation Languages

In recent years, dynamic languages, such as JavaScript or Python, have been increasingly used in a wide range of fields and applications. Their tricky and misunderstood behaviors pose a hard challenge for static analysis of these programming languages. A key aspect of any dynamic language program is the multiple usage of strings, since they can be implicitly converted to another type value, transformed by string-to-code primitives or used to access an object-property. Unfortunately, string analyses for dynamic languages still lack precision and do not take into account some important string features. Moreover, string obfuscation is very popular in the context of dynamic language malicious code, for example, to hide code information inside strings and then to dynamically transform strings into executable code. In this scenario, more precise string analyses become a necessity. This paper is placed in the context of static string analysis by abstract interpretation and proposes a new semantics for string analysis, placing a first step for handling dynamic languages string features.Comment: In Proceedings VPT 2019, arXiv:1908.0672