Abstract-Object-oriented applications of significant size are often complex and therefore costly to maintain. Indeed, they rely on the concept of class which has low granularity with varied dependencies not always explicit. The component paradigm provides a projection space well-structured and of highest level for a better understanding through abstract architectural views. But it is possible to go further. It may also be the ultimate target of a complete process of re engineering. The end-to-end automation of this process is a subject on which literature has made very little attention. In this paper, we propose such a method to automatically transform an object-oriented application in an operational component-oriented application. We illustrate this method on a real Java application which is transformed in an operational OSGi application.
Abstract. Software systems should evolve in order to respond to changing client requirements and their evolving environments. But unfortunately, the evolution of legacy applications generates an exorbitant cost. In this paper, we propose an approach to restructure legacy objectoriented applications into component-based applications. Our approach is based on dynamic dependencies between classes to identify potential components. In this way, the composition is dictated by the context of the application to improve its evolvability. We validate our approach through the study of three legacy Java applications.
The predictability of program execution provides attackers a rich source of knowledge who can exploit it to spy or remotely control the program. Moving target defense addresses this issue by constantly switching between many diverse variants of a program, which reduces the certainty that an attacker can have about the program execution. The effectiveness of this approach relies on the availability of a large number of software variants that exhibit different executions. However, current approaches rely on the natural diversity provided by off-the-shelf components, which is very limited. In this paper, we explore the automatic synthesis of large sets of program variants, called sosies. Sosies provide the same expected functionality as the original program, while exhibiting different executions. They are said to be computationally diverse.This work addresses two objectives: comparing different transformations for increasing the likelihood of sosie synthesis (densifying the search space for sosies); demonstrating computation diversity in synthesized sosies. We synthesized 30 184 sosies in total, for 9 large, real-world, open source applications. For all these programs we identified one type of program analysis that systematically increases the density of sosies; we measured computation diversity for sosies of 3 programs and found diversity in method calls or data in more than 40% of sosies. This is a step towards controlled massive unpredictability of software.
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