Abstract:
Code smell can negatively affect software quality. It can be the indication of the bad design or coding, however the relation between code smell and software quality is not characterized. Therefore, developers may not be convinced to avoid code smell in the source code. Knowing
the correlation between code smell and software quality is a way to support the awareness of this issue. This thesis focuses on extracting the correlation between long parameter list smell and understandability, one of characteristics of software quality. Understandability in
the source code is important. Not only a computer but also developers uses the source code. They have to understand the source code so that they can modify, add functionalities, and find errors. HVOC metric is chosen to be a proxy of understandability. Besides extracting
the correlation, the experiment was conducted to examine the effectiveness of HVOC as a proxy of understandability so that the result will support the correlation that is extracted in the first part of the thesis.
