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The challenge of inferring state machines from log data or execution traces is well-established, and has led to the development of several powerful techniques. Current approaches tend to focus on the inference of conventional finite state machines or, in few cases, state machines with guards. However, these machines are ultimately only partial, because they fail to model how any underlying variables...
This artifact captures the workflow that we adopted for our experimental evaluation in our ICSME paper on inferring state transition functions during EFSM inference. To summarise, the paper uses Genetic Programming to infer data transformations, to enable the inference of fully 'computational' extended finite state machine models. This submission shows how we generated, transformed, analysed, and...
Automatically generated state machines are constrained by their complexity, which can be reduced via hierarchy generation. A technique has been demonstrated for hierarchy generation, although evaluation of this technique has proved difficult. There are a variety of metrics that can be used to provide indicators of how complicated a state machine or statechart is, one such example is cyclomatic...
Current software remodularisation tools only operate on abstractions of a software system. In this paper, we investigate the actual impact of automated remodularisation on source code using a tool that automatically applies remodularisations as refactorings. This shows us that a typical remodularisation (as computed by the Bunch tool) will require changes to thousands of lines of code, spread throughout...
LegUp [1] is an open-source high-level synthesis (HLS) tool that accepts a C program as input and automatically synthesizes it into a hybrid system. The hybrid system comprises an embedded processor and custom accelerators that realize user-designated compute-intensive parts of the program with improved throughput and energy efficiency. In this paper, we overview the LegUp framework and describe several...
This paper is concerned with the challenge of reorganising a software system into modules that both obey sound design principles and are sensible to domain experts. The problem has given rise to several unsupervised automated approaches that use techniques such as clustering and Formal Concept Analysis. Although results are often partially correct, they usually require refinement to enable the developer...
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