Improving problem-oriented mailing list archives with MCS

ABSTRACT

Developers often use electronic mailing lists when seeking assistance with a particular software application. The archives of these mailing lists provide a rich repository of problem-solving knowledge. Developers seeking a quick answer to a problem find these archives inconvenient, because they lack efficient searching mechanisms, and retain the structure of the original conversational threads which are rarely relevant to the knowledge seeker.We present a system called MCS which improves mailing list archives through a process called condensation. Condensation involves several tasks: extracting only messages of longer-term relevance, adding metadata to those messages to improve searching, and potentially editing the content of the messages when appropriate to clarify. The condensation process is performed by a human editor (assisted by a tool), rather than by an artificial intelligence (AI) system.We describe the design and implementation of MCS, and compare it to rlated systems. We also present our experiences condensing a 1428 message mailing list archive to an archive containing only 177 messages (an 88% reduction). The condensation required only 1.5 minutes of editor effort per message. The condensed archive was adopted by the users of the mailing list.

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INDEX TERMS

Primary Classification:
  K. Computing Milieux
  K.6 MANAGEMENT OF COMPUTING AND INFORMATION SYSTEMS
      K.6.3 Software Management
          Subjects: Software development

Additional Classification:
  H. Information Systems
  H.4 INFORMATION SYSTEMS APPLICATIONS

General Terms:
Design, Management, Measurement, Performance, Theory

Keywords:
archives, collective memory, knowledge condensation, mailing lists