SCAN: an approach to label and relate execution trace segments

Abstract

Abstract-Identifying concepts in execution traces is a task often necessary to support program comprehension or maintenance activities. Several approaches-static, dynamic or hybrid-have been proposed to identify cohesive, meaningful sequence of methods in execution traces. However, none of the proposed approaches is able to label such segments and to identify relations between segments of the same trace.This paper present SCAN (Segment Concept AssigNer) an approach to assign labels to sequences of methods in execution traces, and to identify relations between such segments. SCAN uses information retrieval methods and formal concept analysis to produce sets of words helping the developer to understand the concept implemented by a segment. Specifically, formal concept analysis allows SCAN to discover commonalities between segments in different trace areas, as well as terms more specific to a given segment and high level relations between segments.The paper describes SCAN along with a preliminary manual validation-upon execution traces collected from usage scenarios of JHotDraw and ArgoUML-of SCAN accuracy in assigning labels representative of concepts implemented by trace segments.

Program understanding using ontologies and dynamic analysis

“…However, sometimes it is not clear how the research work contributes in the right direction. For example, while the clusters of methods obtained in [Asadi et al, 2010] and [Medini et al, 2012] could indeed correspond to the features executed by the program, the sets of terms mapped to the methods in each identified cluster do not represent a single notion or concept (in the sense that Biggerstaff gives to that word) that a developer could easily identify.…”

“…However, even if demonstrated, the resulting kind of concept mapping represents very little help in program comprehension because these concepts do not represent anything that developers would readily understand. The authors might have recognized this problem since they introduce later on, in [Medini et al, 2012], a technique to label the obtained execution trace segments. However, while their technique improves their previous results, the obtained labels are simply smaller sets of terms than those obtained in [Asadi et al, 2010].…”

Using High-Rising Cities to Visualize Performance in Real-Time

“…Voigt et al [11] proposed a plot to visualize active objects in an execution trace. Medini et al [12] proposed an effective algorithm that extract meaningful labels for detected phases. For a real-time profiler, Reiss [13] proposed a technique to compare active methods between a pair of consecutive time slots.…”