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add ESEM and TSE paper
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@@ -123,6 +123,75 @@ <h1>Brains On Code</h1>
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<section>
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<h2>Papers</h2>
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<article>
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<header>
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<h3>A Look into Programmers’ Heads (TSE)</h3>
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</header>
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<ul class="authors">
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<li>Norman Peitek</li>
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<li><a href="http://www.infosun.fim.uni-passau.de/se/people-jsiegmund.php">Janet Siegmund</a></li>
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<li><a href="http://www.infosun.fim.uni-passau.de/spl/apel/">Sven Apel</a></li>
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<li><a href="http://www.cs.cmu.edu/~ckaestne/">Christian Kaestner</a></li>
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<li><a href="http://www.chrisparnin.me">Chris Parnin</a></li>
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<li>Anja Bethmann</li>
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<li>Thomas Leich</li>
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<li>Gunter Saake</li>
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<li>Andre Brechmann</li>
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</ul>
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<summary>
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Program comprehension is an important, but hard to measure cognitive process. This makes it difficult to provide suitable
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programming languages, tools, or coding conventions to support developers in their everyday work. Here, we explore whether
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<i>functional magnetic resonance imaging (fMRI)</i> is feasible for soundly measuring program comprehension. To this end, we observed 17
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participants inside an fMRI scanner while they were comprehending source code. The results show a clear, distinct activation of five
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brain regions, which are related to working memory, attention, and language processing, which all fit well to our understanding of
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program comprehension. Furthermore, we found reduced activity in the default mode network, indicating the cognitive effort necessary
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for program comprehension. We also observed that familiarity with Java as underlying programming language reduced cognitive effort
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during program comprehension. To gain confidence in the results and the method, we replicated the study with 11 new participants and
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largely confirmed our findings. Our results encourage us and, hopefully, others to use fMRI to observe programmers and, in the long
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run, answer questions, such as: How should we train programmers? Can we train someone to become an excellent programmer? How
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effective are new languages and tools for program comprehension?
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</summary>
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<h4>Resources</h4>
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<ul class="resources">
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<li><a href="https://doi.org/10.1109/TSE.2018.2863303">DOI: 10.1109/TSE.2018.2863303</a></li>
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<li><a href="https://www.infosun.fim.uni-passau.de/publications/docs/PSA+18tse.pdf">Paper - A Look into Programmers’ Heads, PDF, 2MB</a></li>
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</ul>
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</article>
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<article>
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<header>
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<h3>Simultaneous Measurement of Program Comprehension with fMRI and Eye Tracking: A Case Study (ESEM 18)</h3>
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</header>
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<ul class="authors">
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<li>Norman Peitek</li>
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<li><a href="http://www.infosun.fim.uni-passau.de/se/people-jsiegmund.php">Janet Siegmund</a></li>
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<li><a href="http://www.chrisparnin.me">Chris Parnin</a></li>
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<li><a href="http://www.infosun.fim.uni-passau.de/spl/apel/">Sven Apel</a></li>
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<li><a href="http://www.cessor.de">Johannes C. Hofmeister</a></li>
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<li>Andre Brechmann</li>
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</ul>
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<summary>
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<b>Background</b> Researchers have recently started using functional magnetic resonance imaging (fMRI) to validate decades-old programcomprehension models. While fMRI helps us to understand neuronal correlates of cognitive processes during program comprehension, its comparatively low temporal resolution (i.e., seconds)
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cannot capture the fast cognitive subprocesses (i.e., milli seconds).</br>
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<b>Aims</b> To increase the explanatory power of fMRI measurement of programmers, we are exploring the feasibility of adding simultaneous eye tracking to the fMRI measurement. By observing programmers with two complementary methods, we aim at obtaining
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a more holistic understanding of program comprehension.</br>
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<b>Method</b> We conducted a controlled fMRI experiment of 22 student participants with simultaneous eye tracking.</br>
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<b>Results</b> We could successfully capture fMRI and eye-tracking data, although with some limitations, including spatial imprecision and
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a negligible drift. The biggest issue that we experienced is the partial loss of data, such that for only 10 participants, we could
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collect a complete set of high-precision eye-tracking data. Since some participants of fMRI studies show excessive head motion, the
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proportion of full and high-quality data on fMRI and eye tracking is rather low. Still, the remaining data allowed us to confrm our
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prior hypothesis of semantic recall during program comprehension, which was not possible with fMRI alone.</br>
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<b>Conclusions</b> Simultaneous measurement of program comprehension with fMRI and eye tracking is feasible and promising. By adding
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simultaneous eye tracking to our fMRI study framework, we can conduct more fne-grained fMRI analyses, which in turn helps us
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to understand programmer behavior better.
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</summary>
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<h4>Resources</h4>
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<ul class="resources">
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<li><a href="https://github.com/brains-on-code/simultaneous-fmri-and-eyetracking">Replication Package</a></li>
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<li><a href="https://www.infosun.fim.uni-passau.de/publications/docs/PSP+18b.pdf">Paper - Simultaneous Measurement of Program Comprehension with fMRI and Eye Tracking: A Case Study, PDF, 6MB</a></li>
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</ul>
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</article>
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<article>
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<header>
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<h3>Shorter Identifier Names Take Longer To Comprehend (EMSE 18)</h3>

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