Writing by Peter Hilton

Paper review: Achieving Software Quality through Source Code Readability

A computer science paper reviewed from an industry perspective - 31 December 2016 #naming, #readability, #paper

This blog post reviews Achieving Software Quality through Source Code Readability, which Phillip Relf presented at Qualcon 2004, an Australian software quality conference. I found my way to this paper via a reference in one of the papers Felienne Hermans and I reviewed for What science says about naming.


Relf aimed to investigate whether software professionals would accept identifier naming guidelines that claim to improve source code readability. He expected to show that:

  1. software engineers would mostly accept the naming guidelines
  2. expert software engineers would, more than novices, accept naming guidelines that require greater cognitive effort to check for, in source code.

The experimental data supported both expectations.


The software engineers accepted the guidelines, in general, except for guideline 10 (see below). In addition, the expert software engineers accepted the guidelines more strongly than the novices.


The author collected 21 guidelines from previously published research. For each guideline, he constructed code examples in Ada and Java to illustrate compliance and non-compliance.

27 subjects rated each illustrated guideline on a scale of 1 (strong acceptance) to 5 (strong rejection). Academic, Novice, Intermediate, Expert or Quality.

The paper does not address the thorny problem of defining either ‘software engineer’ or ‘expert’, which I doubt anyone has a good definition for. However, the paper also does not explain how the subjects were selected and classified, in practice.

Naming guidelines

The includes the following identifier naming guidelines, to which I’ve added a column with my own rating. Unsurprisingly, because I like this kind of strictness, I strongly agree with half of the guidelines, and only reject four of them.

No Guideline Example violation R
1 Un-named Constant i.e., a numeric value other than -1, 0 or +1, used in an expression Radius * 3.141592 1
2 Multiple Underscore Characters Apple__Count 1
3 Outside Underscore Character _Apple_Count 1
4 Numeric Digit(s) i.e., identifier duplication differentiated only by a digit (for multiple identifiers an array should be defined) Apple_Count_1, Apple_Count_2 1
5 Naming Convention Anomaly i.e., a non-standard mixture of character case Apple_COUNT 1
6 Identifier Encoding i.e., the use of Hungarian notation to attach the identifier data type to the identifier name iApple_Count 1
7 Short Identifier Name i.e., an identifier name shorter than eight characters, excluding: i, j, k. l, m, n, t, x, y or z Count 4
8 Long Identifier Name i.e., an identifier name longer than twenty characters Foreign_And_Domestic_Apple_Count 2
9 Number of Words i.e., an identifier should consist of two, three or four words Count 3
10 Class/Type Qualification i.e., class names and type names should be qualified to identify their nature Fruit (FruitClass and Fruit_Tree is considered more readable) 5
11 Abstract Words i.e., the construction of an identifier only using abstract words Do_It 1
12 English Word(s) i.e., the use of ‘words’ not found in the English language App_Cnt 1
13 Constant/Variable Qualification i.e., numeric range constants should be fully qualified Minimum_Apple_Count (Apple_Count_Minimum is considered more readable) 2
14 Numeric Identifier Name i.e., the composition of an identifier from only numeric words and numeric values One_Hundred 1
15 Singular Word(s) i.e., identifier names should be composed of words in the singular Apple_Counts 5
16 Duplicate Identifier Names i.e., the appearance of two identical identifier names both in scope Apple_Count Procedure … Apple_Count 1
17 Similar Identifier Names i.e., the appearance of two similar identifier names both in scope Apple_Count Procedure … Apple_Counts 3
18 Unused Identifier i.e., an identifier declared by never used N/A 1
19 Same Words i.e., two identifiers composed of the same words but used in a different order Apple_CountCount_Apple 1
20 Enumeration Identifier Definition Order i.e., enumeration constants declared in non-alphabetical order Type Colour_Type is (Colour_Red, Colour_Blue, Colour_Green) 2
21 Enumeration Identifier Qualification i.e., the non-qualification of enumeration constants to identify their base type Type Colour_Type is (Blue, Green, Red) 5

To illustrate why someone might not accept all of these guidelines, the following paragraphs explain my rationale for those I do not ‘strongly accept’.

7. Short Identifier Name. I don’t use this guideline, in practice, because I’m more concerned about avoiding abbreviations (guideline 12) than that names should not be too short. In fact, I’d partly accept this guideline, were it not for its exception for single-letter names, which I consider the worst kind of abbreviation.

8. Long Identifier Name. I only partly accept this guideline, because I prefer names to be as long as necessary. However, I would also consider a name longer than twenty characters to be suspiciously long, and look for either a simpler name or extracting an intermediate declaration, which sometimes simplifies the thing with the long name.

9. Number of Words. As with the previous guidelines, I don’t use this because I prefer to let the other guidelines determine length. However, in his 2007 doctoral thesis, Relf reveals the neuroscience for limiting identifiers to four words, which suggests that may be a good idea. I don’t know what the objection to one-word names might be, especially when the correct term in a bounded context’s vocabulary (a subject domain term) might be a single word, such as a ‘shipment’ in a supply chain context.

10. Class/Type Qualification. I reject this guideline, as did the study participants. I would consider adding a class name Class suffix redundant. Many languages use a capitalisation convention for type names, and a class keyword for declarations. Furthermore, professional software developers tend to use tools (IDEs) that indicate which identifiers are types, or support navigation to the declaration. I have never heard of anyone systematically adopting this guideline.

13 | Constant/Variable Qualification. This guideline seems reasonable, but I probably prefer grammatical English word order sometimes.

15. Singular Word. I reject this guideline because it doesn’t consider collection types, but it’s easily fixed. Only use singular names for single values, and only use plural names for collections.

17. Similar Identifier Names. I don’t know whether to accept this guideline, because I don’t experience this as a problem in practice, and don’t know how onerous I would find it.

20. Enumeration Identifier Definition Order. I partly accept this guideline, which at least requires an order and thus prevents (apparently) random order. However, some enumerations, such as weekdays, have their own non-alphabetical natural order. Fortunately, we follow guidelines blindly.

21. Enumeration Identifier Qualification Order. Adding an enumeration type’s name to its constants’ name make as little sense as adding a class’ name to its instances’ names (or guideline come to that). Fortunately, I’ve never seen this in practice.

Industry relevance

This paper links written identifier naming guidelines to industrial practice by evaluating how strongly professional software engineers accept them. Naming guidelines’ relevance lies in their contributions to more maintainable code, and therefore reduced software maintenance cost. Naming, and source code readability in general, has a big impact on code maintainability.

This paper’s specific findings mean that you can expect to find numerous written guidelines that commercial software developers can use. However, don’t expect to find all guidelines equally acceptable. Furthermore, consider that novice developers may require more work explanation that more experienced developers.

Beyond the paper’s results, you may choose to the collected guidelines directly. This kind of of guideline belongs in a coding standards (code review) checklist, or as part of automated checks.


P. Relf, Achieving Software Quality through Source Code Readability (2004)

Further reading - from the paper’s references

Pearse, Troy; Oman, Paul (1995) Maintainability Measurements on Industrial Source Code Maintenance Activities. IEEE: Proceedings of the International Conference on Software Maintenance, 1995. October 1995, pp: 295-303

Spinellis, Diomidis (2003) Reading Writing and Code. ACM: Queue. October 2003, Vol: 1, No: 7, pp:84-89

Crutchfield, Richard; Workman, David A (1994) Quality Guidelines = Designer Metrics.

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