Detecting Important Terms in Source Code for Program Comprehension

Software Engineering research has become extremely dependent on terms (words in textual data) extracted from source code. Different techniques have been proposed to extract the most important\u27\u27 terms from code. These terms are typically used as input to research prototypes: the quality of the output of these prototypes will depend on the quality of the term extraction technique. At present no consensus exists about which technique predicts the best terms for code comprehension. We perform a literature review, and propose a unified prediction model based on a Naive Bayes algorithm. We evaluate our model in a field study with professional programmers, as well as a standard 10-fold synthetic study. We found our model predicts the top quartile of the most-important terms with approximately 50% precision and recall, outperforming other popular techniques. We found the predictions from our model to help programmers to the same degree as the gold set

Structured Review of the Evidence for Effects of Code Duplication on Software Quality

This report presents the detailed steps and results of a structured review of code clone literature. The aim of the review is to investigate the evidence for the claim that code duplication has a negative effect on code changeability. This report contains only the details of the review for which there is not enough place to include them in the companion paper published at a conference (Hordijk, Ponisio et al. 2009 - Harmfulness of Code Duplication - A Structured Review of the Evidence)

Overcoming Language Dichotomies: Toward Effective Program Comprehension for Mobile App Development

Mobile devices and platforms have become an established target for modern software developers due to performant hardware and a large and growing user base numbering in the billions. Despite their popularity, the software development process for mobile apps comes with a set of unique, domain-specific challenges rooted in program comprehension. Many of these challenges stem from developer difficulties in reasoning about different representations of a program, a phenomenon we define as a "language dichotomy". In this paper, we reflect upon the various language dichotomies that contribute to open problems in program comprehension and development for mobile apps. Furthermore, to help guide the research community towards effective solutions for these problems, we provide a roadmap of directions for future work.Comment: Invited Keynote Paper for the 26th IEEE/ACM International Conference on Program Comprehension (ICPC'18

Structured Review of Code Clone Literature

This report presents the results of a structured review of code clone literature. The aim of the review is to assemble a conceptual model of clone-related concepts which helps us to reason about clones. This conceptual model unifies clone concepts from a wide range of literature, so that findings about clones can be compared with each other

Harmfulness of Code Duplication - A Structured Review of the Evidence

Duplication of code has long been thought to decrease changeability of systems, but recently doubts have been expressed whether this is true in general. This is a problem for researchers because it makes the value of research aimed against clones uncertain, and for practitioners as they cannot be sure whether their effort in reducing duplication is well-spent. In this paper we try to shed light on this is-sue by collecting empirical evidence in favor and against the nega-tive effects of duplication on changeability. We go beyond the flat yes/no-question of harmfulness and present an explanatory model to show the mechanisms through which duplication is suspected to affect quality. We aggregate the evidence for each of the causal links in the model. This sheds light on the current state of duplication re-search and helps practitioners choose between the available mitiga-tion strategies

A comparative evaluation of dynamic visualisation tools

Despite their potential applications in software comprehension, it appears that dynamic visualisation tools are seldom used outside the research laboratory. This paper presents an empirical evaluation of five dynamic visualisation tools - AVID, Jinsight, jRMTool, Together ControlCenter diagrams and Together ControlCenter debugger. The tools were evaluated on a number of general software comprehension and specific reverse engineering tasks using the HotDraw objectoriented framework. The tasks considered typical comprehension issues, including identification of software structure and behaviour, design pattern extraction, extensibility potential, maintenance issues, functionality location, and runtime load. The results revealed that the level of abstraction employed by a tool affects its success in different tasks, and that tools were more successful in addressing specific reverse engineering tasks than general software comprehension activities. It was found that no one tool performs well in all tasks, and some tasks were beyond the capabilities of all five tools. This paper concludes with suggestions for improving the efficacy of such tools

RePOR: Mimicking humans on refactoring tasks. Are we there yet?

Refactoring is a maintenance activity that aims to improve design quality while preserving the behavior of a system. Several (semi)automated approaches have been proposed to support developers in this maintenance activity, based on the correction of anti-patterns, which are `poor' solutions to recurring design problems. However, little quantitative evidence exists about the impact of automatically refactored code on program comprehension, and in which context automated refactoring can be as effective as manual refactoring. Leveraging RePOR, an automated refactoring approach based on partial order reduction techniques, we performed an empirical study to investigate whether automated refactoring code structure affects the understandability of systems during comprehension tasks. (1) We surveyed 80 developers, asking them to identify from a set of 20 refactoring changes if they were generated by developers or by a tool, and to rate the refactoring changes according to their design quality; (2) we asked 30 developers to complete code comprehension tasks on 10 systems that were refactored by either a freelancer or an automated refactoring tool. To make comparison fair, for a subset of refactoring actions that introduce new code entities, only synthetic identifiers were presented to practitioners. We measured developers' performance using the NASA task load index for their effort, the time that they spent performing the tasks, and their percentages of correct answers. Our findings, despite current technology limitations, show that it is reasonable to expect a refactoring tools to match developer code