An investigation of misunderstanding code patterns in C open-source software projects

Medeiros, Flávio; Lima, Gabriel Donnantuoni; Amaral, Guilherme; Apel, Sven; Kästner, Christian; Ribeiro, Márcio; Gheyi, Rohit

doi:10.1007/s10664-018-9666-x

Cited by 29 publications

(22 citation statements)

References 31 publications

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“…Following the original studies, the notion of atoms of confusion has been shown to be common in practice and correlated with negative code quality indicators such as bug density and security vulnerabilities [12]. The concept has also been investigated with the open-source community through opinion surveys and pullrequests [17]. This line of investigation confirms that atoms of confusion are indeed confusing and prevalent across several dimensions.…”

Section: Related Workmentioning

confidence: 75%

Thinking aloud about confusing code: a qualitative investigation of program comprehension and atoms of confusion

Gopstein

Fayard

Apel

et al. 2020

Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Softw

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Section: Related Workmentioning

confidence: 75%

Thinking aloud about confusing code: a qualitative investigation of program comprehension and atoms of confusion

Gopstein

Fayard

Apel

et al. 2020

Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Softw

Self Cite

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“…Kernighan and Pike [20] state in their book that using the ternary operator to replace four lines of if-else code is a good idea. Interestingly, Medeiros et al [21] decided not to investigate the effects of this atom given its popularity in realworld codebases.…”

Section: F Conditional (Ternary) Operatormentioning

confidence: 99%

“…Their research is based on the analysis of 14 of the most popular and influential C and C++ software projects. Medeiros et al [21] also researched the rate of occurrences of most of the atoms and show that all but one occur in the analyzed projects. They based their numbers on a set of 50 open-source C projects using a mixed method approach including repository mining and developer surveys.…”

Section: Background and Related Workmentioning

confidence: 99%

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Atoms of Confusion in Java

Langhout

Aniche

2021

2021 IEEE/ACM 29th International Conference on Program Comprehension (ICPC)

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Although writing code seems trivial at times, problems arise when humans misinterpret what the code actually does. One of the potential causes are "atoms of confusion", the smallest possible patterns of misinterpretable source code. Previous research has investigated the impact of atoms of confusion in C code. Results show that developers make significantly more mistakes in code where atoms are present. In this paper, we replicate the work of Gopstein et al. to the Java language. After deriving a set of atoms of confusion for Java, we perform a two-phase experiment with 132 computer science students (i.e., novice developers). Our results show that participants are 2.7 up to 56 times more likely to make mistakes in code snippets affected by 7 out of the 14 studied atoms of confusion, and when faced with both versions of the code snippets, participants perceived the version affected by the atom of confusion to be more confusing and/or less readable in 10 out of the 14 studied atoms of confusion.Index Terms-software engineering, program comprehension, atoms of confusion, empirical software engineering.2 https://gcc.gnu.org/bugzilla/show bug.cgi?id=90885 3 https://gcc.gnu.org/bugzilla/show bug.cgi?id=90885#c6

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“…23 studies: [3]- [5], [10], [12], [13], [22], [45], [49], [55], [59], [61], [62], [64], [65], [67]- [74] answer if understood the code 4 studies: [42], [55], [59], [60] rate confidence in her answer 3 studies: [8], [20], [53] rate the task difficulty 7 studies: [5], [10], [20], [21], [45], [49], [51] and fix bugs in the code. Scanniello et al [11] asked subjects to do so in two programs with different identifier styles.…”

Section: Task Type Studiesmentioning

confidence: 99%

Evaluating Code Readability and Legibility: An Examination of Human-centric Studies

Oliveira

Bruno

Madeiral

et al. 2020

2020 IEEE International Conference on Software Maintenance and Evolution (ICSME)

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Reading code is an essential activity in software maintenance and evolution. Several studies with human subjects have investigated how different factors, such as the employed programming constructs and naming conventions, can impact code readability, i.e., what makes a program easier or harder to read and apprehend by developers, and code legibility, i.e., what influences the ease of identifying elements of a program. These studies evaluate readability and legibility by means of different comprehension tasks and response variables. In this paper, we examine these tasks and variables in studies that compare programming constructs, coding idioms, naming conventions, and formatting guidelines, e.g., recursive vs. iterative code. To that end, we have conducted a systematic literature review where we found 54 relevant papers. Most of these studies evaluate code readability and legibility by measuring the correctness of the subjects' results (83.3%) or simply asking their opinions (55.6%). Some studies (16.7%) rely exclusively on the latter variable. There are still few studies that monitor subjects' physical signs, such as brain activation regions (5%). Moreover, our study shows that some variables are multi-faceted. For instance, correctness can be measured as the ability to predict the output of a program, answer questions about its behavior, or recall parts of it. These results make it clear that different evaluation approaches require different competencies from subjects, e.g., tracing the program vs. summarizing its goal vs. memorizing its text. To assist researchers in the design of new studies and improve our comprehension of existing ones, we model program comprehension as a learning activity by adapting a preexisting learning taxonomy. This adaptation indicates that some competencies, e.g., tracing, are often exercised in these evaluations whereas others, e.g., relating similar code snippets, are rarely targeted.

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An investigation of misunderstanding code patterns in C open-source software projects

Cited by 29 publications

References 31 publications

Thinking aloud about confusing code: a qualitative investigation of program comprehension and atoms of confusion

Thinking aloud about confusing code: a qualitative investigation of program comprehension and atoms of confusion

Atoms of Confusion in Java

Evaluating Code Readability and Legibility: An Examination of Human-centric Studies

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