SCAN: An Approach to Label and Relate Execution Trace Segments

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.

SCAN: an approach to label and relate execution trace segments

“…This paper extends our previous work , which proposed a preliminary approach to label segments and identify relations among them. The novel contributions of this paper are as follows:An approach to reduce segment size by retaining only the most important method calls using tf‐idf and vector space model (VSM) IR techniques.…”

“…In our previous work, we considered all method calls as being equals when splitting the traces and labeling their segments.An algorithm to automatically identify relations among segments using FCA and lattice partitioning. In our previous work , this identification was performed manually by partitioning concept lattices produced by FCA.An empirical evaluation involving 31 participants and six programs of the following: (i) the impact of segment size reduction on the labels; (ii) the accuracy of the labels generated by SCAN; and (iii) the accuracy of the relations among segments reported by SCAN.An empirical study of the usefulness of SCAN using two other real‐world programs and their execution traces and bug reports. We provide evidence that SCAN is effective in retrieving relevant methods and reducing the quantity of information that developers must process to locate features.…”

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.…”

A selection of distinguished papers from the 19th Working Conference on Reverse Engineering 2012

“…The second paper ‘SCAN: An Approach to Label and Relate Execution Trace Segments’ presents Segment Concept AssigNer (SCAN), an approach for supporting developers in feature location. SCAN is able to split execution traces into cohesive segments (using a search‐based approach), label the segments with relevant keywords, and identify relations among segments (using formal concept analysis).…”