An early study showed that indentation is not a matter of style, but provides actual support for program comprehension. In this paper, we present a non-exact replication of this study. Our aim is to provide empirical evidence for the suggested level of indentation made by many style guides. Following Miara and others, we also included the perceived difficulty, and we extended the original design to gain additional insights into the influence of indentation on visual effort by employing an eye-tracker. In the course of our study, we asked 22 participants to calculate the output of Java code snippets with different levels of indentation, while we recorded their gaze behavior. We did not find any indication that the indentation levels affect program comprehension or visual effort, so we could not replicate the findings of Miara and others. Nevertheless, our modernization of the original experiment design is a promising starting point for future studies in this field.

Background Researchers have recently started to validate decades-old program-comprehension models using functional magnetic resonance imaging (fMRI). While fMRI helps us to understand neural correlates of cognitive processes during program comprehension, its comparatively low temporal resolution (i.e., seconds) cannot capture fast cognitive subprocesses (i.e., milliseconds).

Reading and understanding source code is a major task in software development. Code comprehension depends on the quality of code, which is impacted by code structure and identifier naming. In this paper we empirically investigated whether longer but more descriptive identifier names improve code comprehension compared to short names, as they represent useful information in more detail. In a web-based study 88 Java developers were asked to locate a semantic defect in source code snippets. With descriptive identifier names, developers spent more time in the lines of code before the actual defect occurred and changed their reading direction less often, finding the semantic defect about 14% faster than with shorter but less descriptive identifier names. These effects disappeared when developers searched for a syntax error, i.e., when no in-depth understanding of the code was required. Interestingly, the style of identifier names had a clear impact on program comprehension for more experienced developers but not for less experienced developers.

Most modern software programs cannot be understood in their entirety by a single programmer. Instead, programmers must rely on a set of cognitive processes that aid in seeking, filtering, and shaping relevant information for a given programming task. Several theories have been proposed to explain these processes, such as ``beacons,' for locating relevant code, and ``plans,'' for encoding cognitive models. However, these theories are decades old and lack validation with modern cognitive-neuroscience methods. In this paper, we report on a study using functional magnetic resonance imaging (fMRI) with 11 participants who performed program comprehension tasks. We manipulated experimental conditions related to beacons and layout to isolate specific cognitive processes related to bottom-up comprehension and comprehension based on semantic cues. We found evidence of semantic chunking during bottom-up comprehension and lower activation of brain areas during comprehension based on semantic cues, confirming that beacons ease comprehension.

Developers spend the majority of their time comprehending code, a process in which identifier names play a key role. Although many identifier naming styles exist, they often lack an empirical basis and it is not quite clear whether short or long identifier names facilitate comprehension. In this paper, we investigate the effect of different identifier naming styles (letters, abbreviations, words) on program comprehension, and whether these effects arise because of their length or their semantics. We conducted an experimental study with 72 professional C# developers, who looked for defects in source-code snippets. We used a within-subjects design, such that each developer saw all three versions of identifier naming styles and we measured the time it took them to find a defect. We found that words lead to, on average, 19% faster comprehension speed compared to letters and abbreviations, but we did not find a significant difference in speed between letters and abbreviations. The results of our study suggest that defects in code are more difficult to detect when code contains only letters and abbreviations. Words as identifier names facilitate program comprehension and can help to save costs and improve software quality.