{'fraction_non_alphanumeric': 0.027127659574468086, 'fraction_numerical': 0.0015957446808510637, 'mean_word_length': 5.463917525773196, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 1, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Preliminary Evaluation of a Tag-Based Knowledge Condensation Tool in Agile and Distributed Teams

An important challenge in Agile Global Software Development (AGSD) is architectural knowledge vaporization, i.e., the loss of technical knowledge due to a lack of documentation. In a previous work we identified that technical knowledge is usually available in unstructured textual electronic means (e.g. chat, mail, blogs, etc. – also known as UTEMs) used by AGSD workers during development, although not necessarily easily accessible. Also, we proposed the concept of Knowledge Condensation as a means to recover knowledge from UTEMs, by introducing a structure to their contents along with means to retrieve knowledge. In this work we present our first step towards a Knowledge Condensation tool, through a prototype tagging mechanism to structure architectural knowledge during UTEM interactions. We evaluated the prototype and obtained the following results: (1) a high perception of usefulness and a high projected intention of use, and (2) the identification of 6 tagging behavior profiles from participants. These tagging behaviors can be grouped as (i) participants who tag as expected, (ii) participants who tag more than expected, and (ii) participants who tag less than expected. These results suggest that it is important to cope with "little or no tagging" and "excessive tagging" behaviors to implement knowledge condensation based on UTEM tagging. Furthermore, we identified that tagging could be a good option to structure UTEM interactions, and to retrieve architectural knowledge from UTEM logs. Future work includes improving the tagging mechanism prototype based on the participants' suggestions and overall evaluation results, and implementing a searcher prototype to further evaluate the concept of knowledge condensation based on tagging of UTEM interactions.