Assessing the Capability of Code Smells to Support Software Maintainability Assessments: Empirical Inquiry and Methodological Approach

Code smells are indicators of software design shortcomings that can decrease software maintainability. An advantage of code smells over traditional software measures is that the former are associated with an explicit set of refactoring strategies to improve the existing design. As such, code smell analysis is a promising approach to address both the assessment and the improvement of maintainability. An important challenge in code smell analysis is understanding the interplay between code smells and different aspects of maintenance. Research on code smells conducted in the past decade has emphasized the formalization and automated detection of code smells. Much less research has been conducted to empirically investigate how comprehensive and informative code smells are for the assessment of software maintainability. If we are to use code smells to assess maintainability, we need to understand their potential in explaining and predicting different maintenance outcomes and their usefulness in industrial settings. Relevant questions in using code smells as maintainability indicators include: “What and how much can code smells tell me about the maintainability of a system as a whole?” and “How suitable are code smells in identifying code segments (i.e., files) with low software maintainability?” The main goal of this thesis is to empirically investigate, from different perspectives and in a realistic setting, the strengths and limitations of code smells in supporting software maintainability assessments. The secondary goal is to suggest approaches to address the limitations of code smells and the assessments based on them. Both goals are reflected in our attempt to answer the following research questions: • Research Question 1: How good are code smells as indicators of system-level maintainability of software, and how well do code-smell-based assessments perform compared with other assessment approaches? • Research Question 2: How good are code smells in distinguishing source code files that are likely to require more maintenance effort than others? • Research Question 3: How good are code smells in discriminating between source code files that are likely to be problematic and those that are not likely to be so during maintenance?