This article is a spin-off piece from the paper “Do We Need Improved Code Quality Metrics?” by myself and Prof. Diomidis Spinellis.
Earlier, I wrote an article about issues with code quality metrics; in another article I presented how all the variants of LCOMmetric misrepresent simple cases of class …
This article is a spin-off piece from the paper "Do We Need Improved Code Quality Metrics?" by myself and Prof. Diomidis Spinellis.
Software metrics have always been on a roller-coaster ride. On one hand, researchers and practitioners have adopted metrics not only to reveal quality characteristics of their programs, but …
I recently completed my Ph.D. (thesis, defense presentation) and currently, I am cherishing my beautiful days back in Athens. This is also a laid back time (well.. not so much) to ponder about the last three and half years of investment. The pondering revealed that I learned many things …
Code smells indicate the presence of quality issues in source code. An excessive number of smells make a software system hard to evolve and maintain. In this article, we apply deep learning models based on CNN and RNN to detect code smells without extensive feature engineering, just by feeding the …
Kent Beck coined the term "code smell" in the popular Refactoring book by Martin Fowler and defined it informally as certain structures in the code that suggest (sometimes they scream for) the possibility of refactoring. Since then, various smells have been reported that impair software quality in one or more …
Check out my post YALCOM and our paper for more refined information, experiments, and results.
Along with other metrics, LCOM (Lack of Cohesion in Methods) was first defined by C&K in the OOPSLA paper [1] that invented a new field of object-oriented metrics. LCOM shows the degree of lack …
If code-quality is one of your concerns, you must be aware of code smells and design smells. Similarly, code written in configuration management systems such as Puppet and Chef is also prone to such maintainability smells.
Recently, we (myself, Prof. Diomidis Spinellis, and Marios Fragkoulis) have worked on configuration smells …
This is an inspirational and thought-provoking lecture by Richard Hamming. I would strongly recommend it to anybody who is researching as a professional or as a student.
Some of the gems from the talk are as follows.
Machine Learning for Source Code Analysis (ML4SCA)