Browsing by Autor "Silvia Takahashi"

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Cross-language Clone Detection for Mobile Apps
(2023) Stephannie Jimenez; Gordana Rakić; Silvia Takahashi; Nicolás Cardozo
Clone detection provides insight about replicated fragments in a code base. With the rise of multi-language code bases, new techniques addressing cross-language code clone detection enable the analysis of polyglot systems. Such techniques have not yet been applied to the mobile apps’ domain, which are naturally polyglot. Native mobile app developers must synchronize their code base in at least two different programming languages. App synchronization is a difficult and time-consuming maintenance task, as features can rapidly diverge between platforms, and feature identification must be performed manually. Our goal is to provide an analysis framework to reduce the impact of app synchronization. A first step in this direction consists on a structural algorithm for cross-language clone detection exploiting the idea behind enriched concrete syntax trees. Such trees are used as a common intermediate representation built from programming languages’ grammars, to detect similarities between app code bases. Our technique finds code similarities with 79% precision for controlled tests where Type 1-3 clones are manually injected for the analysis of both single- and cross-language cases for Kotlin and Dart. We evaluate our tool on a corpus of 52 mobile apps identifying code similarities with a precision of 65% to 84% for the full application logic.
Soft computing techniques for analysis of kidnapping crimes in Colombia
(2005) Andrés Arciniegas; Silvia Takahashi; Andrés Vega Torres
Techniques associated with soft computing have been proven to be useful for solving problems where lack of information and uncertainties are present. The flaws of traditional methodologies stem from the fuzziness, partial true, lack of information, and event imprecision of problems related to crime analysis such as kidnapping. Case based reasoning and expert's knowledge are the main inputs of some soft computing techniques that may be applied for analysis of kidnapping crimes. Kidnapping is a problem framed by the lack of veracity, scarceness, fuzziness of information, and tacit, qualitative and unstructured knowledge in the minds of few experts. So, kidnapping is the kind of problem that could be modeled and analyzed by using some of the techniques included in the field of soft computing. This paper describes the use of fuzzy logic, fuzzy clustering and classification to analyze and evaluate kidnapping crimes in Colombia. These techniques are intended to predict the captivity duration, captor group and liberation conditions for any victim. Also, these techniques could be used to assess the impact of government security and economic policies on the evolution of the kidnapping crime