inferring state-based behavior models
Dynamic analysis helps to extract important information about software systems useful in testing, debugging and maintenance activities. Popular dynamic analysis techniques synthesize either information on the values of the variables or information on relations between invocation of methods. Thus, these approaches do not capture the important relations that exist between data values and invocation sequences.In this paper, we introduce a technique, called GK-tail, for generating models that represent the interplay between program variables and method invocations. GK-tail extends the k-tail algorithm for extracting finite state automata from execution traces, to the case of finite state automata with parameters.The paper presents the technique and the results of some preliminary experiments that indicate the potentialities of the proposed approach.
behavioral models model dynamic analysis extraction informal software systems test debugging maintenance activation values variability method data sequence paper algorithm automata traces case experience finite-state machines verification inference algorithms