TESNA Method


The overall Method consists of several steps.

  • First, we assume that the Project Manager has a fairly good idea about the different Socio/Technical Patterns and about which specific pattern or groups of Patterns have to be applied in the current project situation.
  • Next, TESNA accepts input for the Social Network as well as the Software Architecture (and the software code), and the tool provides a visual description of the networks and metrics, based on the Socio/Technical Patterns selected.
  • If the Project Manager identifies an STSC, he can decide whether his planned software process model is good or needs to be changed.

The Project Manager can also decide to alter the social network as well as the software architecture and then carry out this process iteratively until he is satisfied. Figure 1 indicates two labelled loops, namely loop SN (the Social Network loop) and loop ST (the Socio/Technical loop). The SN loop corresponds to the Social Network Module of TESNA. The Social Network Module reads input on the Social Network, by mining Chat/Mail/Bug tracker Repositories. The Social Network data can later be confirmed through more qualitative interviews and questionnaires. 

Figure 1: The TESNA Method and the Planned Software Process

The tool then creates social network images and calculates metrics to show the changes of the networks over time.  The ST loop corresponds to the Socio/Technical Module of TESNA. The Socio/Technical module reads input on the Socio/Technical aspects of the software development process. In order to read the technical network the tool reads the source code (currently TESNA can handle java source code) and in order to find out the Socio-Technical links the tool mines Software Configuration Management Systems like CVS (Concurrent Versioning System) and SVN (SubVersion). TESNA uses different displays to help identify the existence of STSCs related to the social network or the software call graph. The tool uses both qualitative as well as quantitative data to help in the identification of STSCs. The qualitative data is represented in the form of different kinds of visualizations of the social as well as the technical networks, while the quantitative data consists of various metrics that the tool calculates to augment the qualitative data. The display requires the manager to decide if a particular STSC is problematic and needs to be worked on while the metric related to the STSC shows the manager the extent of the problem.