Recently, Brachypodium distachyon has emerged as a model plant for studying monocot grasses and cereal crops. Using assembled expressed transcript sequences and subsequent mapping to the corresponding genome, we identified 1219 alternative splicing (AS) events spanning across 2021 putatively assembled transcripts generated from 941 genes. Approximately, 6.3% of expressed genes are alternatively spliced in B. distachyon. We observed that a majority of the identified AS events were related to retained introns (55.5%), followed by alternative acceptor sites (16.7%). We also observed a low percentage of exon skipping (5.0%) and alternative donor site events (8.8%). The ‘complex event’ that consists of a combination of two or more basic splicing events accounted for ∼14.0%. Comparative AS transcript analysis revealed 163 and 39 homologous pairs between B. distachyon and Oryza sativa and between B. distachyon and Arabidopsis thaliana, respectively. In all, we found 16 AS transcripts to be conserved in all 3 species. AS events and related putative assembled transcripts annotation can be systematically browsed at Plant Alternative Splicing Database ().

What are software developers doing during a change task? While an answer to this question opens countless opportunities to support developers in their work, only little is known about developers' detailed navigation behavior for realistic change tasks. Most empirical studies on developers performing change tasks are limited to very small code snippets or are limited by the granularity or the detail of the data collected for the study. In our research, we try to overcome these limitations by combining user interaction monitoring with very fine granular eye-tracking data that is automatically linked to the underlying source code entities in the IDE.In a study with 12 professional and 10 student developers working on three change tasks from an open source system, we used our approach to investigate the detailed navigation of developers for realistic change tasks. The results of our study show, amongst others, that the eye-tracking data does indeed capture different aspects than user interaction data and that developers focus on only small parts of methods that are often related by data flow. We discuss our findings and their implications for better developer tool support.

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The paper presents a novel approach for recovering software traceability links from developers' eye gazes. An eye tracker is used to capture eye gazes while developers perform software maintenance tasks within the Eclipse IDE. An algorithm is presented that establishes a set of traceability links from the eye-gaze data of several developer sessions. A preliminary study assesses the feasibility and validity of the approach. The links generated by the approach were validated by another set of developers. Results indicate that our algorithm achieves strong recall when developers accurately perform bug-localization tasks.

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