3 research outputs found
Dynamic decision tree for legacy use-case recovery
In the context of reverse-engineering project we designed a use-case specification recovery technique for legacy information systems. With our technique, we can recover the alternative flows of each use-case of the system. It is based on a dynamic (i.e. runtime) analysis of the working of the system using execution traces. But "traditional" execution trace format do not contain enough information for this approach to work. Then we designed a new execution trace format together with the associated tool to get the program's dynamic decision tree corresponding to each of the use-case scenario. These trees are then processed to find the possible variants from the main scenario of each use-case. In this paper we first present our approach to the use-case specification recovery technique and the new trace format we designed. Then the decision tree compression technique is showed with a feasibility study. The contribution of the paper is our approach to the recovery of legacy systems' use-case, the new trace format and the decision tree processing technique
Identifying Components from Object-Oriented APIs Based on Dynamic Analysis
The reuse at the component level is generally more effective than the one at
the object-oriented class level. This is due to the granularity level where
components expose their functionalities at an abstract level compared to the
fine-grained object-oriented classes. Moreover, components clearly define their
dependencies through their provided and required interfaces in an explicit way
that facilitates the understanding of how to reuse these components. Therefore,
several component identification approaches have been proposed to identify
components based on the analysis object-oriented software applications.
Nevertheless, most of the existing component identification approaches did not
consider co-usage dependencies between API classes to identify classes/methods
that can be reused to implement a specific scenario. In this paper, we propose
an approach to identify reusable software components in object-oriented APIs,
based on the interactions between client applications and the targeted API. As
we are dealing with actual clients using the API, dynamic analysis allows to
better capture the instances of API usage. Approaches using static analysis are
usually limited by the difficulty of handling dynamic features such as
polymorphism and class loading. We evaluate our approach by applying it to
three Java APIs with eight client applications from the DaCapo benchmark.
DaCapo provides a set of pre-defined usage scenarios. The results show that our
component identification approach has a very high precision.Comment: 11 pages, 5 figure