活动简介

Software systems have been playing important roles in business, scientific research, and our everyday lives. It is critical to improve both software productivity and quality, which are major challenges to software engineering researchers and practitioners. In recent years, software mining has emerged as a promising means to address these challenges. It has been successfully applied to discover knowledge from software artifacts (e.g., specifications, source code, documentations, execution logs, and bug reports) to improve software quality and development process (e.g., to obtain the insights for the causes leading to poor software quality, to help software engineers locate and identify problems quickly, and to help the managers optimize the resources for better productivity). Software mining has attracted much attention in both software engineering and data mining communities. 

The Sixth International Workshop on Software Mining aims to bridge research in the data mining community and software engineering community by providing an open and interactive forum for researchers who are interested in software mining to discuss the methodologies and technical foundations of software mining, approaches and techniques for mining various types of software-related data, applications of data mining to facilitate specialized tasks in software engineering. Participants of diverse background in either data mining or software engineering can benefit from this workshop by sharing their expertise, exchanging ideas and discussing new research results 

Authors who are interested in software mining are invited to submit their manuscripts related to all aspects of software mining including software mining foundations, mining specific software data, software mining in specialized tasks, etc.

征稿信息

重要日期

2017-08-18
初稿截稿日期
2017-08-30
初稿录用日期
2017-09-06
终稿截稿日期

征稿范围

Topics of interest include but are not limited to:

A. Data mining foundations for software analytics

A1. Emerging machine learning methods for software analytics 
A2. Predictive / descriptive modeling techniques for software analytics
A3. Novel frequent pattern mining techniques for software analytics
A4. Evolutionary computing techniques for software analytics 

B. Software mining techniques

B1. Software mining models and techniques
B2. Robust and Highly Scalable Algorithms for Mining Large Scale Software System
B3. Understanding and visualizing software mining results
B4. Privacy preserving software mining

C. Mining specific software data

C1. Mining software specifications 
C2. Mining source code 
C3. Mining execution traces and logs 
C4. Mining change patterns and trends 
C5. Mining bug and crash reports
C6. Mining natural language artifacts in software data

D. Software mining in specialized tasks

D1. Mining for software defect identification and characterization 
D2. Mining for software testing and debugging 
D3. Mining for cost/effort estimation
D4. Mining for software development and reuse
D5. Mining for resource allocation 
D6. Mining for process control 

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重要日期
  • 会议日期

    10月30日

    2017

    11月03日

    2017

  • 08月18日 2017

    初稿截稿日期

  • 08月30日 2017

    初稿录用通知日期

  • 09月06日 2017

    终稿截稿日期

  • 11月03日 2017

    注册截止日期

主办单位
IEEE
承办单位
University of Illinois
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