Aiko Yamashita

Quantifying the Effect of Code Smells on Maintenance Effort

Context: Code smells are assumed to indicate bad design that leads to less maintainable code. However, this assumption has not been investigated in controlled studies with professional software developers. Aim: This paper investigates the relationship between code smells and maintenance effort. Method: Six developers were hired to perform three maintenance tasks each on four functionally equivalent Java systems originally implemented by different companies. Each developer spent three to four weeks. In total, they modified 298 Java files in the four systems. An Eclipse IDE plug-in measured the exact amount of time a developer spent maintaining each file. Regression analysis was used to explain the effort using file properties, including the number of smells. Result: None of the 12 investigated smells was significantly associated with increased effort after we adjusted for file size and the number of changes; Refused Bequest was significantly associated with decreased effort. File size and the number of changes explained almost all of the modeled variation in effort. Conclusion: The effects of the 12 smells on maintenance effort were limited. To reduce maintenance effort, a focus on reducing code size and the work practices that limit the number of changes may be more beneficial than refactoring code smells.

Do code smells reflect important maintainability aspects

Code smells are manifestations of design flaws that can degrade code maintainability. As such, the existence of code smells seems an ideal indicator for maintainability assessments. However, to achieve comprehensive and accurate evaluations based on code smells, we need to know how well they reflect factors affecting maintainability. After identifying which maintainability factors are reflected by code smells and which not, we can use complementary means to assess the factors that are not addressed by smells. This paper reports on an empirical study that investigates the extent to which code smells reflect factors affecting maintainability that have been identified as important by programmers. We consider two sources for our analysis: (1) expert-based maintainability assessments of four Java systems before they entered a maintenance project, and (2) observations and interviews with professional developers who maintained these systems during 14 working days and implemented a number of change requests.

Exploring the impact of inter-smell relations on software maintainability: an empirical study

Code smells are indicators of issues with source code quality that may hinder evolution. While previous studies mainly focused on the effects of individual code smells on maintainability, we conjecture that not only the individual code smells but also the interactions between code smells affect maintenance. We empirically investigate the interactions amongst 12 code smells and analyze how those interactions relate to maintenance problems. Professional developers were hired for a period of four weeks to implement change requests on four medium-sized Java systems with known smells. On a daily basis, we recorded what specific problems they faced and which artifacts were associated with them. Code smells were automatically detected in the pre-maintenance versions of the systems and analyzed using Principal Component Analysis (PCA) to identify patterns of co-located code smells. Analysis of these factors with the observed maintenance problems revealed how smells that were co-located in the same artifact interacted with each other, and affected maintainability. Moreover, we found that code smell interactions occurred across coupled artifacts, with comparable negative effects as same-artifact co-location. We argue that future studies into the effects of code smells on maintainability should integrate dependency analysis in their process so that they can obtain a more complete understanding by including such coupled interactions.

To what extent can maintenance problems be predicted by code smell detection? - An empirical study

Context: Code smells are indicators of poor coding and design choices that can cause problems during software maintenance and evolution. Objective: This study is aimed at a detailed investigation to which extent problems in maintenance projects can be predicted by the detection of currently known code smells. Method: A multiple case study was conducted, in which the problems faced by six developers working on four different Java systems were registered on a daily basis, for a period up to four weeks. Where applicable, the files associated to the problems were registered. Code smells were detected in the pre-maintenance version of the systems, using the tools Borland Together and InCode. In-depth examination of quantitative and qualitative data was conducted to determine if the observed problems could be explained by the detected smells. Results: From the total set of problems, roughly 30% percent were related to files containing code smells. In addition, interaction effects were observed amongst code smells, and between code smells and other code characteristics, and these effects led to severe problems during maintenance. Code smell interactions were observed between collocated smells (i.e., in the same file), and between coupled smells (i.e., spread over multiple files that were coupled). Conclusions: The role of code smells on the overall system maintainability is relatively minor, thus complementary approaches are needed to achieve more comprehensive assessments of maintainability. Moreover, to improve the explanatory power of code smells, interaction effects amongst collocated smells and coupled smells should be taken into account during analysis.

Code smells as system-level indicators of maintainability: An empirical study

Abstract Context Code smells are manifestations of design flaws that can degrade code maintainability. So far, no research has investigated if these indicators are useful for conducting system-level maintainability evaluations. Aim The research in this paper investigates the potential of code smells to reflect system-level indicators of maintainability. Method We evaluated four medium-sized Java systems using code smells and compared the results against previous evaluations on the same systems based on expert judgment and the Chidamber and Kemerer suite of metrics. The systems were maintained over a period of up to 4 weeks. During maintenance, effort (person-hours) and number of defects were measured to validate the different evaluation approaches. Results Most code smells are strongly influenced by size; consequently code smells are not good indicators for comparing the maintainability of systems differing greatly in size. Also, from the comparison of the different evaluation approaches, expert judgment was found as the most accurate and flexible since it considered effects due to the systems size and complexity and could adapt to different maintenance scenarios. Conclusion Code smell approaches show promise as indicators of the need for maintenance in a way that other purely metric-based approaches lack.

Assessing the capability of code smells to explain maintenance problems: an empirical study combining quantitative and qualitative data

Code smells are indicators of deeper design problems that may cause difficulties in the evolution of a software system. This paper investigates the capability of twelve code smells to reflect actual maintenance problems. Four medium-sized systems with equivalent functionality but dissimilar design were examined for code smells. Three change requests were implemented on the systems by six software developers, each of them working for up to four weeks. During that period, we recorded problems faced by developers and the associated Java files on a daily basis. We developed a binary logistic regression model, with “problematic file” as the dependent variable. Twelve code smells, file size, and churn constituted the independent variables. We found that violation of the Interface Segregation Principle (a.k.a. ISP violation) displayed the strongest connection with maintenance problems. Analysis of the nature of the problems, as reported by the developers in daily interviews and think-aloud sessions, strengthened our view about the relevance of this code smell. We observed, for example, that severe instances of problems relating to change propagation were associated with ISP violation. Based on our results, we recommend that code with ISP violation should be considered potentially problematic and be prioritized for refactoring.

Maintenance and agile development: Challenges, opportunities and future directions

Software entropy is a phenomenon where repeated changes gradually degrade the structure of the system, making it hard to understand and maintain. This phenomenon imposes challenges for organizations that have moved to agile methods from other processes, despite agiles focus on adaptability and responsiveness to change. We have investigated this issue through an industrial case study, and reviewed the literature on addressing software entropy, focussing on the detection of “code smells” and their treatment by refactoring. We found that in order to remain agile despite of software entropy, developers need better support for understanding, planning and testing the impact of changes. However, it is exactly work on refactoring decision support and task complexity analysis that is lacking in literature. Based on our findings, we discuss strategies for dealing with entropy in this context and present avenues for future research.

Software Entropy in Agile Product Evolution

As agile software development principles and methods are being adopted by large software product organizations it is important to understand the role of software entropy. That is, how the maintainability of a system may degrade over time due to continuous change. This may on one side affect the ability to act agile in planning and development. On the other side, an agile process may affect growth of entropy. We report from a case study of a successful software product line organization that has adopted the agile development method Evo, showing how agility and entropy are negatively related. We conclude this study by suggesting a two-step approach to manage entropy while maintaining process agility. First, the system needs to be restructured to establish a level of manageable entropy, and then, that the agile process must be complemented with continuous semi-automated quality monitoring and refactoring support.

Inter-smell relations in industrial and open source systems: A replication and comparative analysis

The presence of anti-patterns and code smells can affect adversely software evolution and quality. Recent work has shown that code smells that appear together in the same file (i.e., collocated smells) can interact with each other, leading to various types of maintenance issues and/or to the intensification of negative effects. It has also been found that code smell interactions can occur across coupled files (i.e., coupled smells), with comparable negative effects as the interaction of same-file (collocated) smells. Different inter-smell relations have been described in previous work, yet only few studies have evaluated them empirically. This study attempts to replicate the findings from previous work on inter-smell relations by analyzing larger systems, and by including both industrial and open source ones. We also include the analysis of coupled smells in addition to collocated smells, to achieve a more complete picture of inter-smell relations. Our results suggest that if coupled smells are not considered, one may risk increasing the number of false negatives when analysing inter-smells. A major finding is that patterns of inter-smell relations vary between open source and industrial systems, suggesting that contextual variables should be considered in further studies on code smells.

How Good Are Code Smells for Evaluating Software Maintainability? Results from a Comparative Case Study

An advantage of code smells over traditional software measures is that the former are associated with an explicit set of refactorings to improve the existing design. Past research on code smells has emphasized the formalization and automated detection of code smells, but much less has been done to empirically investigate how good are code smells for evaluating software maintainability. This paper presents a summary of the findings in the thesis by Yamashita, which aimed at investigating the strengths and limitations of code smells for evaluating software maintainability. The study conducted comprised an outsourced maintenance project involving four Java web systems with equivalent functionality but dissimilar implementation, six software professionals, and two software companies. A main result from the study is that the usefulness of code smells differs according to the granularity level (e.g., whether the assessment is done at file or system level) and the particular operationalization of maintainability (e.g., maintainability can be measured via maintenance effort, or problems encountered during maintenance, etc). This paper summarises the most relevant findings from the thesis, discusses a series of lessons learned from conducting this study, and discusses avenues for new research in the area of code smells.