Descriptive compound identifier names improve source code comprehension

Schankin, Andrea; Berger, Annika; Holt, Daniel V.; Hofmeister, Johannes C.; Riedel, Till; Beigl, Michael

doi:10.1145/3196321.3196332

Cited by 52 publications

(18 citation statements)

References 20 publications

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“…Liblit et al [32] discusses naming in several programming languages and makes observations about how natural language influences the use of words in these languages. Schankin et al [6] focus on investigating the impact of more informative identifiers on code comprehension. Their findings show an advantage of descriptive identifiers over non-descriptive ones.…”

Section: Identifier Structure and Semantics Analysismentioning

confidence: 99%

On the generation, structure, and semantics of grammar patterns in source code identifiers

Newman

Alsuhaibani

Decker

et al. 2020

Journal of Systems and Software

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Identifiers make up a majority of the text in code. They are one of the most basic mediums through which developers describe the code they create and understand the code that others create. Therefore, understanding the patterns latent in identifier naming practices and how accurately we are able to automatically model these patterns is vital if researchers are to support developers and automated analysis approaches in comprehending and creating identifiers correctly and optimally. This paper investigates identifiers by studying sequences of partof-speech annotations, referred to as grammar patterns. This work advances our understanding of these patterns and our ability to model them by 1) establishing common naming patterns in different types of identifiers, such as class and attribute names; 2) analyzing how different patterns influence comprehension; and 3) studying the accuracy of state-of-the-art techniques for part-of-speech annotations, which are vital in automatically modeling identifier naming patterns, in order to establish their limits and paths toward improvement. To do this, we manually annotate a dataset of 1,335 identifiers from 20 open-source systems and use this dataset to study naming patterns, semantics, and tagger

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Section: Identifier Structure and Semantics Analysismentioning

confidence: 99%

On the generation, structure, and semantics of grammar patterns in source code identifiers

Newman

Alsuhaibani

Decker

et al. 2020

Journal of Systems and Software

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“…Studies on the length of identifier names by Lawrie et al [6] and Hofmeister et al [5] show that names consisting of abbreviations are harder to comprehend than full-word identifiers. Similarly, a study by Schankin et al [34] shows that descriptive names improve program comprehension. Studies on systems using camel case and underscores for identifier names [35], [36] have shown that developer experience plays an important part in comprehending such names.…”

Section: B Identifier Qualitymentioning

confidence: 83%

Towards a Model to Appraise and Suggest Identifier Names

Peruma

2019

2019 IEEE International Conference on Software Maintenance and Evolution (ICSME)

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Unknowingly, identifiers in the source code of a software system play a vital role in determining the quality of the system. Ambiguous and confusing identifier names lead developers to not only misunderstand the behavior of the code but also increases comprehension time and thereby causes a loss in productivity. Even though correcting poor names through rename operations is a viable option for solving this problem, renaming itself is an act of rework and is not immune to defect injection.In this study, we aim to understand the motivations that drive developers to name and rename identifiers and the decisions they make in determining the name. Using our results, we propose the development of a linguistic model that determines identifier names based on the behavior of the identifier. As a prerequisite to constructing the model, we conduct multiple studies to determine the features that should feed into the model. In this paper, we discuss findings from our completed studies and justify the continuation of research on this topic through further studies.

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“…However, other studies claimed that abbreviations are detrimental to comprehension. Takang et al find that full names are better than abbreviations [41], and Hofmeister et al and Schankin et al claim that comprehension is faster with full and descriptive names [21], [36].…”

Section: Related Workmentioning

confidence: 99%

How Developers Choose Names

Feitelson

Mizrahi

Noy

et al. 2022

IIEEE Trans. Software Eng.

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The names of variables and functions serve as implicit documentation and are instrumental for program comprehension. But choosing good meaningful names is hard. We perform a sequence of experiments in which a total of 334 subjects are required to choose names in given programming scenarios. The first experiment shows that the probability that two developers would select the same name is low: in the 47 instances in our experiments the median probability was only 6.9%. At the same time, given that a specific name is chosen, it is usually understood by the majority of developers. Analysis of the names given in the experiment suggests a model where naming is a (not necessarily cognizant or serial) three-step process:(1) selecting the concepts to include in the name, (2) choosing the words to represent each concept, and (3) constructing a name using these words. A followup experiment, using the same experimental setup, then checked whether using this model explicitly can improve the quality of names. The results were that names selected by subjects using the model were judged by two independent judges to be superior to names chosen in the original experiment by a ratio of two-to-one. Using the model appears to encourage the use of more concepts and longer names.

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Descriptive compound identifier names improve source code comprehension

Cited by 52 publications

References 20 publications

On the generation, structure, and semantics of grammar patterns in source code identifiers

On the generation, structure, and semantics of grammar patterns in source code identifiers

Towards a Model to Appraise and Suggest Identifier Names

How Developers Choose Names

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