Section 1 Reverse Engineering

In this Section, reverse engineering and user interface modelling aspects are described (Campos, 2004 Duke Harrison, 1993). Section 2.1 provides details about the reverse engineering area. Then, the type of GUIs models to be used is discussed in Section 2.2. Finally, the last Section summarizes the Section presenting some conclusions. 

This result, called the Carnot efficiency or the thermodynamic efficiency, places a fundamental limit on the efficiency with which heat can be converted to mechanical work. Only if the high temperature, T, were infinite or the low temperature, T , were zero would it be possible to have a heat engine operate with 100% efficiency. To maximize efficiency, the greatest possible temperature difference should be used. Although we derived this result specifically for the ideal gas, we will show later in this section that it applies to any reversible engine operating between two temperatures. For a real engine, which must operate irreversibly, the actual efficiency must be lower than the thermodynamic efficiency. 

Whereas in the previous section we reviewed various model formalisms and the questions they can answer, in this section we concentrate on the more difficult and challenging problem of how such models can be obtained. Model construction is usually intercepted as a tedious manual task accomplished by experienced professionals. In some cases, however, this task can be automated, and a model can be computationally inferred directly from experimental data, a problem usually referred to as reverse engineering. 

A number of reviews of reverse-engineering approaches can be found in the literature [D haeseleer, Liang, and Somogyi 2000 Bolouri and Davidson 2002 Hasty et al. 2001], Here, we discuss well-established techniques for inferring models as those discussed in the previous section. 

Work has been done to infer differential equation models of cellular networks from time-series data. As we explained in the previous section, the general form of the differential equation model is deceit = f(Cj, c2,. cN), where J] describes how each element of the network affects the concentration rate of the network element. If the functions f are known, that is, the individual reaction and interaction mechanisms in the network are available, a wealth of techniques can be used to fit the model to experimental data and estimate the unknown parameters [Mendes 2002]. In many cases, however, the functions f are unknown, nonlinear functions. A common approach for reverse engineering ordinary differential equations is to linearize the functions f around the equilibrium [Stark, Callard, and Hubank 2003] and obtain... 

For a reversible engine, both the efficiency and the ratio QJQi can be calculated directly from the measurable quantities of work and heat flowing to the surroundings. Therefore we have measurable properties that depend on temperatures only and are independent of the properties of any special kind of substance. Consequently, it is possible to establish a scale of temperature independent of the properties of any individual substance. This overcomes the difficulty associated with empirical scales of temperature described in Section 6.5. This scale is the absolute, or the thermodynamic, temperature scale. 

Carnot s reversible engine-consists of an ideal gas that operates between a hot reservoir and a cold reservoir, at temperatures 0i and 02 respectively. Until their identity has been is established, we shall use 0 for the temperature that appears in the ideal gas equation and T for the absolute temperature (which, as we shall see in the next section, is defined by the efficiency of a reversible cycle). Thus, the ideal gas equation is written as pV = NRQ, in which 0 is the temperature measured by noting the change of some quantity such as volume or pressure. (Note that measuring temperature by volume expansion is purely empirical each... 

In this section we describe the background that is relevant for the subsequent discussion. We first give a brief introduction to reverse engineering and then characterize (complex) embedded systems. 

Based on the review of reverse engineering literature (cf. Section 3) and our own expertise in the domain of complex embedded system we try to establish the current state-of-the-art/practice and identify research challenges. 

This Section describes GUISURFER, a tool developied as a testbed for the reverse engineering approach proposed in the previous Section. The tool automatically extracts GUI behavioural models from the applications source code, and automates some of the activities involved in the analisys of these models. 

In this Section a reverse engineering tool was described. The GUISURFER tool enables extraction of different behavioural models from application s source code. The tool is flexible, indeed the same techniques has already been applied to extract similar models from different programming paradigm. 

The reverse engineering approach described in this Chapter allows for the extraction of GUI behavioural models from source code. This Section describes an approach to GUI reasoning from these models. To this end, the QuickCheck Haskell library (Claessen Hughes, 2000), graph theory, and the Graph-Tool are used. 

In this section we analyze traditional reverse engineering techniques based on static and dynamic analysis. We show how to reverse engineering object-oriented code to models, in... 

So far we have discussed the elements that constitute a platform independent model (PIM). To derive PIM models from implementation artifacts one typacally develops model driven transformations. These transformations codify the rules that can be applied on implementation artifacts to derive models in the case of reverse engineering. In the case of forward engineering, the transformation rules codify how to translate the PIM models into implementation artifacts. In the next section, we present transformation authoring framework. 

Rapid Prototyping Tooling - Reverse Engineering Laboratory Mechanical Design Control Systems Section, School of Mechanical Engineering, National Technical University of Athens (NTUA)... 

---