Improving the Precision of Fowler's Definitions of Bad Smells

Zhang, Min; Baddoo, Nathan; Wernick, Paul; Hall, Tracy

doi:10.1109/sew.2008.26

Cited by 16 publications

(8 citation statements)

References 11 publications

(8 reference statements)

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“…Though there is a great deal effort on program refactoring research (see e.g. [5,34]), to our best knowledge, meta-program refactoring is restricted either by homogeneous meta-programming (such as logic meta-programming [36]), or aspect-oriented programming [25].…”

Section: Related Workmentioning

confidence: 99%

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Refactoring of Heterogeneous Meta-Program into k-stage Meta-Program

Štuikys

Bespalova

Burbaitė

2014

ITC

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The paper presents: (1) a graph-based theoretical background to refactoring a correct heterogeneous meta-program into its k-stage representation; (2) the refactoring method; (3) refactoring experiments with tasks taken from different domains, including real world tasks, such as meta-programs to teach Computer Science (CS) topics using educational robots. Refactoring meta-programs by staging enables to flexibly adapt them to the different context of use. To do that (semi-)automatically, we use the contextual information as a priority relation (e.g. highest, lowest, etc.) introduced within the meta-program specification. We implement the refactoring method using the so-called activating/de-activating label (index) to change the role of metalanguage constructs at different stages. The contribution of the paper is: (1) applying the known (in programming) staging concept to heterogeneous metaprogramming; (2) a theoretical background, properties and the method to solve tasks of this kind of refactoring.

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Section: Related Workmentioning

confidence: 99%

“…Refactoring changes the program's structure only, without affecting its external behaviour. The improvements typically eliminate redundancy, bad smell of code [25], improve maintainability and may improve performance and reduce space [10,22].…”

Section: Introductionmentioning

confidence: 99%

Refactoring of Heterogeneous Meta-Program into k-stage Meta-Program

Štuikys

Bespalova

Burbaitė

2014

ITC

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“…These smells describe in the informal way and need interpretation with a manual detection process. The classification of design flaws is proposed in many works [20,21]. These taxonomies are introduced to provide better understanding of the smells and to recognize the relationships between smells.…”

Section: Related Workmentioning

confidence: 99%

The Influence Factors of Inherent Structure in e-LearningProcess

Sfenrianto¹

2011

IJEEEE

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“…It may cause duplication in the system too. If any switch statement has more than two switch cases it is considered to be a "Switch Statements" smell (Baddoo, Hall, Wernick, & Zhang, 2008).…”

Section: • • • • Switch Statementsmentioning

confidence: 99%

“…Polymorphism helps to avoid this problem. Zhang, Baddoo, Wernick, & Hall (2008) suggested that if any "Type Code" consists of more than two cases, it is considered as code smell. For example, in the below code snapshot, the switch case, movie.getTypeCode, consists of more than three cases.…”

Section: Descriptionmentioning

confidence: 99%

Java Smell Detector

Mathur

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Code Smell" or "Bad Smell", at the very least, is an indicator of badly written code and is often indicative of deeper problems in software design. In layman terms, it signals flaws in the core foundation or architecture of the software that can cause any number of more serious problems-from usability and runtime performance to supportability and enhancement. These problems can mostly be prevented by the systematic refactoring of the code. Refactoring is the process (and according to some, an 'art') of making incremental changes to existing source code to improve its nonfunctional attributes, without modifying its external functional behavior. Code smells are symptoms of deep-rooted problems in design, which, in most common cases, inhibit the understandability of the system for present and future programmers, hence rendering the program un-maintainable. The later these problems are identified, the costlier they are to correct as it is much harder to refactor a system in production and regression. Issues caused by refactoring can spiral out of control in advanced stages of the software development life cycle. So far, identification of these code smells has been thought of as an intuitive art rather than an exact science, as there are very few empirical measures or methodologies for doing so. In this project, I will examine each of the 22 code smells identified in prior research. I will implement Java Smell Detector (JSD), which will follow a scientific approach to detect five of these 22 code smells. JSD will give suggestions to refactor the code for all five of these smells. Further, the tool will provide an interactive process to refactor two of these cases; while for the rest, it will suggest an ideal refactoring technique that would need to be applied manually. I will be using Java code written by students of San Jose State University (SJSU) as test data for JSD and will compare its output against the code smells identified by the graduate students.

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Improving the Precision of Fowler's Definitions of Bad Smells

Cited by 16 publications

References 11 publications

Refactoring of Heterogeneous Meta-Program into k-stage Meta-Program

Refactoring of Heterogeneous Meta-Program into k-stage Meta-Program

The Influence Factors of Inherent Structure in e-LearningProcess

Java Smell Detector

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