The Statechart Workbench: Enabling Scalable Software Event Log Analysis using Process Mining

被引：0
|
作者：
Leemans, Maikel [1 ]
van der Aalst, Wil M. P. [1 ]
van den Brand, Mark G. J. [1 ]
机构：
[1] Eindhoven Univ Technol, Eindhoven, Netherlands
来源：
2018 25TH IEEE INTERNATIONAL CONFERENCE ON SOFTWARE ANALYSIS, EVOLUTION AND REENGINEERING (SANER 2018) | 2018年
关键词：
Reverse Engineering; Process Mining; Behavior Exploration; Performance Analysis; Usage Analysis; Deviation Analysis; Program Analysis; Model-driven Analysis;
D O I：
暂无
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
To understand and maintain the behavior of a (legacy) software system, one can observe and study the system's behavior by analyzing event data. For model-driven reverse engineering and analysis of system behavior, operation and usage based on software event data, we need a combination of advanced algorithms and techniques. In this paper, we present the Statechart Workbench: a novel software behavior exploration tool. Our tool provides a rich and mature integration of advanced (academic) techniques for the analysis of behavior, performance (timings), frequency (usage), conformance and reliability in the context of various formal models. The accompanied Eclipse plugin allows the user to interactively link all the results from the Statechart Workbench back to the source code of the system and enables users to get started right away with their own software. The work can be positioned in-between reverse engineering and process mining. Implementations, documentation, and a screen-cast (https://youtu.be/xR4XfU3E5mk) of the proposed approach are available, and a user study demonstrates the novelty and usefulness of the tool.
引用
收藏
页码：502 / 506
页数：5
相关论文
共 50 条
  • [31] Quality-informed semi-automated event log generation for process mining
    Andrews, R.
    van Dun, C. G. J.
    Wynn, M. T.
    Kratsch, W.
    Roeglinger, M. K. E.
    ter Hofstede, A. H. M.
    DECISION SUPPORT SYSTEMS, 2020, 132
  • [32] Opportunities for Process Improvement: A Cross-Clientele Analysis of Event Data Using Process Mining
    Bose, R. P. Jagadeesh Chandra
    Gupta, Avantika
    Chander, Deepthi
    Ramanath, Ajith
    Dasgupta, Koustuv
    SERVICE-ORIENTED COMPUTING, (ICSOC 2015), 2015, 9435 : 444 - 460
  • [33] Generating event logs from non-process-aware systems enabling business process mining
    Perez-Castillo, Ricardo
    Weber, Barbara
    Pinggera, Jakob
    Zugal, Stefan
    Garcia-Rodriguez de Guzman, Ignacio
    Piattini, Mario
    ENTERPRISE INFORMATION SYSTEMS, 2011, 5 (03) : 301 - 335
  • [34] Business Process Event Log use for Activity Sequence Analysis
    Savickas, Titas
    Vasilecas, Olegas
    2015 OPEN CONFERENCE OF ELECTRICAL, ELECTRONIC AND INFORMATION SCIENCES (ESTREAM), 2015,
  • [35] Enabling semantics-aware process mining through the automatic annotation of event logs
    Rebmann, Adrian
    van der Aa, Han
    INFORMATION SYSTEMS, 2022, 110
  • [36] The Impact of Process Complexity on Process Performance: A Study Using Event Log Data
    Vidgof, Maxim
    Wurm, Bastian
    Mendling, Jan
    BUSINESS PROCESS MANAGEMENT, BPM 2023, 2023, 14159 : 413 - 429
  • [37] Using text mining and link analysis for software mining
    Grcar, Miha
    Grobehlik, Marko
    Mladenic, Dunja
    MINING COMPLEX DATA, 2008, 4944 : 1 - 12
  • [38] A Distributed Framework for Event Log Analysis using MapReduce
    Dewangan, Sandeep Kumar
    Pandey, Shikha
    Verma, Toran
    PROCEEDINGS OF 2016 INTERNATIONAL CONFERENCE ON ADVANCED COMMUNICATION CONTROL AND COMPUTING TECHNOLOGIES (ICACCCT), 2016, : 503 - 506
  • [39] Visual Process Mining: Event Data Exploration and Analysis
    Bodesinsky, Peter
    Alsallakh, Bilal
    Gschwandtner, Theresia
    Miksch, Silvia
    2014 IEEE CONFERENCE ON VISUAL ANALYTICS SCIENCE AND TECHNOLOGY (VAST), 2014, : 229 - 230
  • [40] Process mining using BPMN: relating event logs and process models
    Kalenkova, Anna A.
    van der Aalst, Wil M. P.
    Lomazova, Irina A.
    Rubin, Vladimir A.
    SOFTWARE AND SYSTEMS MODELING, 2017, 16 (04): : 1019 - 1048
12345