Software projects use Issue Tracking Systems (ITS) like JIRA to track issues and organize the workflows around them. Issues are often inter-connected via different links such as the default JIRA link types Duplicate, Relate, Block, or Subtask. While previous research has mostly focused on analyzing and predicting duplication links, this work aims at understanding the various other link types, their prevalence, and characteristics towards a more reliable link type prediction. For this, we studied 607,208 links connecting 698,790 issues in 15 public JIRA repositories. Besides the default types, the custom types Depend, Incorporate, Split, and Cause were also common. We manually grouped all 75 link types used in the repositories into five general categories: General Relation, Duplication, Composition, Temporal / Causal, and Workflow. Comparing the structures of the corresponding graphs, we observed several trends. For instance, Duplication links tend to represent simpler issue graphs often with two components and Composition links present the highest amount of hierarchical tree structures (97.7%). Surprisingly, General Relation links have a significantly higher transitivity score than Duplication and Temporal / Causal links.

Organisations use issue tracking systems (ITSs) to track and document their projects' work in units called issues. This style of documentation encourages evolutionary refinement, as each issue can be independently improved, commented on, linked to other issues, and progressed through the organisational workflow. Commonly studied ITSs so far include GitHub, GitLab, and Bugzilla, while Jira, one of the most popular ITS in practice with a wealth of additional information, has yet to receive similar attention. Unfortunately, diverse public Jira datasets are rare, likely due to the difficulty in finding and accessing these repositories. With this paper, we release a dataset of 16 public Jiras with 1822 projects, spanning 2.7 million issues with a combined total of 32 million changes, 9 million comments, and 1 million issue links. We believe this Jira dataset will lead to many fruitful research projects investigating issue evolution, issue linking, cross-project analysis, as well as cross-tool analysis when combined with existing well-studied ITS datasets.

We report on an exploratory study, which aims at understanding how development tutorials are structured, what types of tutorials exist, and how official tutorials differ from tutorials written by development communities. We analyzed over 1.200 tutorials for mobile application development provided by six different sources for the three major platforms: Android, Apple iOS, and Windows Phone. We found that a typical tutorial contains around 2700 words distributed over 4 pages and including a list of instructions with 18 items. Overall, 70% of the tutorials contain source code examples and a similar fraction contain images. On average, one tutorial has 6 images. When analyzing the images, we found that the studied iOS community posted the largest number of images, 14 images per tutorial, on average, from which 74% are plain images, i.e., mainly screenshots without stencils, diagrams, or highlights. In contrast, 36% of the images included in the official tutorials by Apple were diagrams or images with stencils. Community sites seem to follow a similar structure to the official sites but include items and images which are rather underrepresented in the official tutorials. From the analysis of the tutorials content by means of natural language processing combined with manual content analysis, we derived four categories for mobile development tutorials: infrastructure and design, application and services, distribution and maintenance, and development platform. Our categorization can help tutorial writers to better organize and evaluate the content of their tutorials and identify missing tutorials.

We report on an exploratory study, which aims at understanding how software developers use social media compared to conventional development infrastructures. We analyzed the blogging and the committing behavior of 1,100 developers in four large open source communities. We observed that these communities intensively use blogs with one new entry about every 8 hours. A blog entry includes 14 times more words than a commit message. When analyzing the content of the blogs, we found that most popular topics represent high-level concepts such as functional requirements and domain concepts. Source code related topics are covered in less than 15% of the posts. Our results also show that developers are more likely to blog after corrective engineering and management activities than after forward engineering and re-engineering activities. Our findings call for a hypothesis-driven research to further understand the role of social media in software engineering and integrate it into development processes and tools.

Work descriptions are informal notes taken by developers to summarize work achieved in a particular session. Existing studies indicate that maintaining them is a distracting task, which costs a developer more than 30 min. a day. The goal of this research is to analyze the purposes of work descriptions, and find out if automated tools can assist developers in efficiently creating them. For this, we mine a large dataset of heterogeneous work descriptions from open source and commercial projects. We analyze the semantics of these documents and identify common information entities and granularity levels. Information on performed actions, concerned artifacts, references and new work, shows the work management purpose of work descriptions. Information on problems, rationale and experience shows their knowledge sharing purpose. We discuss how work description information, in particular information used for work management, can be generated by observing developers' interactions. Our findings have many implications for next generation software engineering tools.

Developers take notes about their work sessions, either to remember the work status and share it with collaborators, or because employers explicitly require this for project management matters. We report on an exploratory study which aims at understanding how software developers describe their work. We analyzed more than 750,000 work descriptions of about 2,000 professionals taken over 8 years in three settings. We observed several similarities in the content and time meta-data of work descriptions. Most frequent terms, such as top-30 performed activities, are used consistently. Particular templates such as ldquoACTION concerning ARTIFACT because of CAUSErdquo occur frequently. Developers described sessions that last 30-120 min. 4-16 times a day. Maintaining diaries seems to consume between 3-6% of the total work time, and in 10% of the sessions, developers did not describe their work in sufficient detail. We argue that our results make the first step towards automatically generating work diaries for software developers.