Clone Removal in Java Programs as a Process of Stepwise Unification

Cloned code is one of the most important obstacles against consistent software maintenance and evolution. Although today's clone detection tools find a variety of clones, they do not offer any advice how to remove such clones. We explain the problems involved in finding a sequence of changes for clone removal and suggest to view this problem as a process of stepwise unification of the clone instances. Consequently the problem can be solved by backtracking over the possible unification steps

How do Developers Improve Code Readability? An Empirical Study of Pull Requests

Readability models and tools have been proposed to measure the effort to read code. However, these models are not completely able to capture the quality improvements in code as perceived by developers. To investigate possible features for new readability models and production-ready tools, we aim to better understand the types of readability improvements performed by developers when actually improving code readability, and identify discrepancies between suggestions of automatic static tools and the actual improvements performed by developers. We collected 370 code readability improvements from 284 Merged Pull Requests (PRs) under 109 GitHub repositories and produce a catalog with 26 different types of code readability improvements, where in most of the scenarios, the developers improved the code readability to be more intuitive, modular, and less verbose. Surprisingly, SonarQube only detected 26 out of the 370 code readability improvements. This suggests that some of the catalog produced has not yet been addressed by SonarQube rules, highlighting the potential for improvement in Automatic static analysis tools (ASAT) code readability rules as they are perceived by developers

Energy efficient software in an engineering course

Sustainable development has become an increasingly important theme not only in the world politics, but also an increasingly central theme for the engineering professions around the world. Software engineers are no exception as shown in various recent research studies. Despite the intensive research on green software, today’s undergraduate computing education often fails to address our environmental responsibility. We present a module on energy efficient software that we introduced as part of an advanced course on software analysis and testing. In this module we study techniques and tools to analyze and optimize energy consumption of software systems. Preliminary results of the first four instances of this course show that students are able to optimize the energy consumption of software systems.ERDF European Regional Development Fund through the Operational Programme for Competitiveness and Internationalisation - COMPETE 2020 Programme within project POCI-01-0145-FEDER006961, and by National Funds through the Portuguese funding agency, FCT - Fundação para a Ciência e a Tecnologia within project POCI-01-0145-FEDER016718 and UID/EEA/50014/2013

Deuce: A Lightweight User Interface for Structured Editing

We present a structure-aware code editor, called Deuce, that is equipped with direct manipulation capabilities for invoking automated program transformations. Compared to traditional refactoring environments, Deuce employs a direct manipulation interface that is tightly integrated within a text-based editing workflow. In particular, Deuce draws (i) clickable widgets atop the source code that allow the user to structurally select the unstructured text for subexpressions and other relevant features, and (ii) a lightweight, interactive menu of potential transformations based on the current selections. We implement and evaluate our design with mostly standard transformations in the context of a small functional programming language. A controlled user study with 21 participants demonstrates that structural selection is preferred to a more traditional text-selection interface and may be faster overall once users gain experience with the tool. These results accord with Deuce's aim to provide human-friendly structural interactions on top of familiar text-based editing.Comment: ICSE 2018 Paper + Supplementary Appendice

Moving beyond Deletions: Program Simplification via Diverse Program Transformations

To reduce the complexity of software, Developers manually simplify program (known as developer-induced program simplification in this paper) to reduce its code size yet preserving its functionality but manual simplification is time-consuming and error-prone. To reduce manual effort, rule-based approaches (e.g., refactoring) and deletion-based approaches (e.g., delta debugging) can be potentially applied to automate developer-induced program simplification. However, as there is little study on how developers simplify programs in Open-source Software (OSS) projects, it is unclear whether these approaches can be effectively used for developer-induced program simplification. Hence, we present the first study of developer-induced program simplification in OSS projects, focusing on the types of program transformations used, the motivations behind simplifications, and the set of program transformations covered by existing refactoring types. Our study of 382 pull requests from 296 projects reveals that there exist gaps in applying existing approaches for automating developer-induced program simplification. and outlines the criteria for designing automatic program simplification techniques. Inspired by our study and to reduce the manual effort in developer-induced program simplification, we propose SimpT5, a tool that can automatically produce simplified programs (semantically-equivalent programs with reduced source lines of code). SimpT5 is trained based on our collected dataset of 92,485 simplified programs with two heuristics: (1) simplified line localization that encodes lines changed in simplified programs, and (2)checkers that measure the quality of generated programs. Our evaluation shows that SimpT5 are more effective than prior approaches in automating developer-induced program simplification

A heuristic-based approach to code-smell detection

Encapsulation and data hiding are central tenets of the object oriented paradigm. Deciding what data and behaviour to form into a class and where to draw the line between its public and private details can make the difference between a class that is an understandable, flexible and reusable abstraction and one which is not. This decision is a difficult one and may easily result in poor encapsulation which can then have serious implications for a number of system qualities. It is often hard to identify such encapsulation problems within large software systems until they cause a maintenance problem (which is usually too late) and attempting to perform such analysis manually can also be tedious and error prone. Two of the common encapsulation problems that can arise as a consequence of this decomposition process are data classes and god classes. Typically, these two problems occur together – data classes are lacking in functionality that has typically been sucked into an over-complicated and domineering god class. This paper describes the architecture of a tool which automatically detects data and god classes that has been developed as a plug-in for the Eclipse IDE. The technique has been evaluated in a controlled study on two large open source systems which compare the tool results to similar work by Marinescu, who employs a metrics-based approach to detecting such features. The study provides some valuable insights into the strengths and weaknesses of the two approache

Understanding the motivations, challenges, and practices of software rejuvenation

The continuous evolution of programming languages has brought benefits and new challenges for software developers. In recent years, we have witnessed a rapid release of new versions of mainstream programming languages like Java. While these advancements promise better security, enhanced performance, and increased developers’ productivity, the constant release of new language versions has posed a particular challenge for practitioners: how to keep their systems up-to-date with new language releases. This thesis aims to understand the pains, motivations, and practices developers follow during rejuvenating efforts—a particular kind of software maintenance whose goal is to avoid obsolesce due to the evolution of programming languages. To this end, we are building and validating a theory using a mixed methods study. In the first study, we interviewed 23 software developers and used the Constructivist Grounded Theory Method to identify recurrent challenges and practices used in rejuvenation efforts. In the second study, we mined the software repositories of open-source projects written in C++ and JavaScript to identify the adoption of new language features and whether or not software developers conduct large rejuvenation efforts. The first study highlights the benefits of new feature adoption and rejuvenation, revealing developer methods and challenges. The second study emphasizes open-source adoption trends and patterns for modern features. In the third and final study, our goal is to share our theory on software rejuvenation with practitioners through the Focus Group method with industrial patterns.(undefined

Code smells detection and visualization: A systematic literature review

Context: Code smells (CS) tend to compromise software quality and also demand more effort by developers to maintain and evolve the application throughout its life-cycle. They have long been catalogued with corresponding mitigating solutions called refactoring operations. Objective: This SLR has a twofold goal: the first is to identify the main code smells detection techniques and tools discussed in the literature, and the second is to analyze to which extent visual techniques have been applied to support the former. Method: Over 83 primary studies indexed in major scientific repositories were identified by our search string in this SLR. Then, following existing best practices for secondary studies, we applied inclusion/exclusion criteria to select the most relevant works, extract their features and classify them. Results: We found that the most commonly used approaches to code smells detection are search-based (30.1%), and metric-based (24.1%). Most of the studies (83.1%) use open-source software, with the Java language occupying the first position (77.1%). In terms of code smells, God Class (51.8%), Feature Envy (33.7%), and Long Method (26.5%) are the most covered ones. Machine learning techniques are used in 35% of the studies. Around 80% of the studies only detect code smells, without providing visualization techniques. In visualization-based approaches several methods are used, such as: city metaphors, 3D visualization techniques. Conclusions: We confirm that the detection of CS is a non trivial task, and there is still a lot of work to be done in terms of: reducing the subjectivity associated with the definition and detection of CS; increasing the diversity of detected CS and of supported programming languages; constructing and sharing oracles and datasets to facilitate the replication of CS detection and visualization techniques validation experiments.Comment: submitted to ARC

Quality-Driven Detection and Resolution of Metamodel Smells

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