V:Issue:lizer: Exploring Clarification in Online Communication Over Time

In this post, I describe the V:Issue:lizer tool (the transcription of the video follows below). V:issue:lizer supports managers in their decision making process by analyzing

  • analyze stakeholder communication
  • analyze communication problems
  • identify domain and project experts.

Here is a preprint of our ICSE2013 Formal Tool Demonstration.

1. Select a Datasource: different types of online communication repositories

V:isue:lizer allows managers to analyze online communication as it is stored in typical repositories, such as Jira, Jazz, and similar issue trackers – or any SQL database.

2. The Basic Interface: Select and visualize discussions

A list of requirements is extracted from such repositories and shown on the left hand side. On selection, the stakeholders’ discussion of a given requirement is visualized in the center.

Let’s look at the details of one requirement, as it may be shown by any issue tracker. In addition to a summary and description, we see a list of stakeholder comments. V:Issue:lizer has an automatic classifier that allows to give a classification for each comment. We see clarification and coordination, as well as some other implementation specific comments.

This discussion on requirement 26709 is visualized. The timeline of the discussion in black and each comment is graphically shown as a box below (clarification comments  in red) and above the line (other comments in blue). The gray line shows the general trend of the discussion.

3. Explore Requirements Clarification over Time: Adjust parameters of visualization

Managers can adjust parameters of the visualization to explore clarification over time. Most important is the ability to adjust the time resolution of the visualization. Managers can choose between a fixed number of time intervals, for example 3, 8, or 32 and fixed time length, for example days, weeks, and month.

This particular trajectory looks suspicious to the manager, because of the high amount of clarification, even late in the lifecycle of this requirement. This might be problematic, because it indicates that the requirement is still not completely understood by the team.

4. Social Network Analysis: Explore requirements clarification over time

For closer investigation, our manager choses to explore the social network of this requirement. V:issue:lizer derives the social network by showing authors of comments as nodes and by adding a link between two authors, if their comments were recorded in the same time interval. Therefore, adjusting the time resolution of the trajectory results in different social networks. In this example, three time intervals lead to three subgraphs. Two of them are connected, because they have one actor in common. But there is no single stakeholder that participates in all phases of the discussion.

For further investigation, V:Issue:lizer offers a second algorithm to generate social networks which is not based on the time resolution. This algorithm generates a high number of weak links and also stronger links between active actors. Filtering weak links helps to identify the core group of this requirement discussion.

5. Aggregation: Exploring related requirements discussions

So far, we talked about single requirements and their discussion. Requirements and their discussions may be related and V:Issue:lizer offers to analyze a cluster of requirements together.

In our example, the manager selects related requirements from the same iteration. In the resulting social network, our manager looks for candidates who could take responsibility of our suspicious requirement. A good candidate should be experienced and knowledgable, so central actors in the network should be considered. The most central actors might already be too busy, but persons that connect subgraphs might be good candidates to get additional responsibilities.

Also, our manager looks for candidates that were both active in clarifying requirements and in coordinating their implementation. Nodes are shown as small pie charts that depict the percentage of clarification in red and coordination in blue.

In this tool demonstration I showed that V:Issue:lizer supports managers in analyzing stakeholder communication and communication problems, and identifying experts that might help to solve them. Thank you for your attention and feel free to contact us for questions or feedback.

Acknowledgements

We thank IBM Ottawa for providing an exciting case study, clarifications when needed, and invaluable feedback in interviews. We thank the ViaTec Software Management Round Table for great feedback and for requesting new features. Additional thanks for wonderful feedback, suggestions, great input and reviews of various versions of this work go to Adrian Schroeter, Alessia Knauss, Eirini KalliamvakouGermán Póo-CaamañoJane Cleland-Huang, and Remko Helms.

This video is part of a submission to the ICSE 2013 Formal Tool Demonstration track I co-authored with Daniela Damian. So last but not least I want to thank her for supporting my ideas, improving the way I express them, and generally for creating a research environment that supports creativity.

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8 thoughts on “V:Issue:lizer: Exploring Clarification in Online Communication Over Time

  1. Pingback: How can clarification patterns help developing software? | Eric's blog

  2. Pingback: ICSE’13 accepts our V:Issue:lizer tool demo paper | Eric's blog

  3. Pingback: Pre-Print for V:Issue:lizer @ ICSE Tool Demo | Eric Knauss

  4. Pingback: The SEGAL Group – How can clarification patterns help developing software?

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