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opencc-by-4.0Mar 2020View details →

Replication Package for the paper: "Behind the Intents: An In-depth Empirical Study on Software Refactoring in Modern Code Review"

This is the replication package for the paper: "Behind the Intents: An In-depth Empirical Study on Software Refactoring in Modern Code Review", published at the 17th International Conference on Mining Software Repositories (MSR ’20).    It contains all the preliminary and final results of our empirical methodology. We highlight the manual classification of developers' intents behind code changes with refactoring operations. This might be used for further studies on developers' motivations when performing refactoring.    Feel free to use any part of this replication package in your study, please cite as: Matheus Paixão, Anderson Uchôa, Ana Carla Bibiano, Daniel Oliveira, Alessandro Garcia, Jens Krinke, and Emilio Arvonio. 2020. Behind the In-tents: An In-depth Empirical Study on Software Refactoring in Modern Code Review. In 17th International Conference on Mining Software Repositories (MSR ’20), October 5–6, 2020, Seoul, Republic of Korea. ACM, New York, NY,USA, 11 pages.

opencc-by-4.0Jul 2020View details →

An empirical study of automatically-generated tests from the perspective of test smells

Developing software test code can be as or more expensive than developing software production code. Commonly, developers use automated unit test generators to speed up software testing. The purpose of such tools is to shorten production time without decreasing code quality. Nonetheless, unit tests usually do not have a quality check layer above testing code, which might be hard to guarantee the quality of the generated tests. An emerging strategy to verify the tests quality is to analyze the presence of test smells in software test code. Test smells are characteristics in the test code that possibly indicate weaknesses in test design and implementation. The presence of test smells in unit test code could be used as an indicator of unit test quality. In this paper, we present an empirical study aimed to analyze the quality of unit test code generated by automated test tools. We compare the tests generated by two tools (Randoop and EvoSuite) with the existing unit test suite of open-source software projects. We analyze the unit test code of twenty-one open-source Java projects and detected the presence of nineteen types of test smells. The results indicated significant differences in the unit test quality when comparing data from both automated unit test generators and existing unit test suites.

Replication Package for the paper: "How Does Modern Code Review Impact Software Design Degradation? An In-depth Empirical Study"

This is the replication package for the paper: "How Does Modern Code Review Impact Software Design Degradation? An In-depth Empirical Study", published at the 36th International Conference on Software Maintenance and Evolution (ICSME' 20).   It contains all the preliminary and final results of our empirical methodology. We highlight the manual classification of design-related and design-unrelated reviews, according to the developers’ intent of improving the structural design of the system. This might be used for further studies on the impact of design discussions on the structural quality of design.   Feel free to use any part of this replication package in your study, please cite as: Anderson Uchôa, Caio Barbosa, Willian Oizumi, Publio Blenílio, Rafael Lima, Alessandro Garcia, and Carla Bezerra. How Does Modern Code Review Impact Software Design Degradation? An In-depth Empirical Study. Proceedings of the 36th International Conference on Software Maintenance and Evolution (ICSME), Adelaide, Australia, September 2020.

Replication package with data used in the study: "The effect of code smells on the relationship between design patterns and defects. An empirical study"

This is a replication package with data used in a study by T. Alkhaeir and B. Walter "The effect of code smells on the relationship between design patterns and defects. An empirical study" This dataset contains the following folders: <ul> <li> "Analyzed systems" folder: <ul> <li> For each subject system (Ant-1.7, JEdit-4.2, Lucene-2.4, Camel-1.6, Log4j-1.2, Xalan-2.7, Poi-3.0, Ivy-2.0, Xerces-2.0, Velocity-1.6), we identify the following datasets: SDP, nSDP, SnDP, and nSnDP. Each dataset is represented by a separate csv file. </li> <li> Those csv files include raw data about every class in every release. Each file includes columns which represent: <ul> <li> System:  The analyzed system </li> <li> className: A fully qualified class name </li> <li> Pattern: if the class is part of any pattern the cell contains the name of the pattern, and “null” otherwise </li> <li> Smell: if the class is part of affected by any smell  the cell contains the name of the smell, and “null”  otherwise </li> <li> Bugs: Number of defects reported inside the class (extracted from the PROMISE dataset) </li> </ul> </li> </ul> </li> <li> A "detailed analysis" folder: <ul> <li> For each pattern, we report all the classes which participate in it in all the analyzed systems. The csv files inside this folder follow the same structure as the other csv files reported above </li> </ul> </li> </ul>

It Takes a Village to Build a Robot: An Empirical Study of The ROS Ecosystem - Replication Package

Over the past eleven years, the Robot Operating System (ROS), has grown from a small research project into the most popular framework for robotics development. Composed of packages released on the Rosdistro package manager, ROS aims to simplify development by providing reusable libraries, tools and conventions for building a robot. Still, developing a complete robot is a difficult task that involves bridging many technical disciplines. Experts who create computer vision packages, for instance, may need to rely on software designed by mechanical engineers to implement motor control. As building a robot requires domain expertise in software, mechanical, and electrical engineering, as well as artificial intelligence and robotics, ROS faces knowledge based barriers to collaboration. In this paper, we examine how the necessity of domain specific knowledge impacts the open source collaboration model. We create a comprehensive corpus of package metadata and dependencies over three years in the ROS ecosystem, analyze how collaboration is structured, and study the dependency network evolution. We find that the most widely used ROS packages belong to a small cluster of foundational working groups (FWGs), each organized around a different domain in robotics. We show that the FWGs are growing at a slower rate than the rest of the ecosystem, in terms of their membership and number of packages, yet the number of dependencies on FWGs is increasing at a faster rate. In addition, we mined all ROS packages on GitHub, and showed that 82% rely exclusively on functionality provided by FWGs. Finally, we investigate these highly influential groups and describe the unique model of collaboration they support in ROS.

An Empirical Study of Refactorings and Technical Debt in Machine Learning Systems

Machine Learning (ML), including Deep Learning (DL), systems, i.e., those with ML capabilities, are pervasive in today's data-driven society. Such systems are complex; they are comprised of ML models and many subsystems that support learning processes. As with other complex systems, ML systems are prone to classic technical debt issues, especially when such systems are long-lived, but they also exhibit debt specific to these systems. Unfortunately, there is a gap of knowledge in how ML systems actually evolve and are maintained. In this paper, we fill this gap by studying refactorings, i.e., source-to-source semantics-preserving program transformations, performed in real-world, open-source software, and the technical debt issues they alleviate. We analyzed 26 projects, consisting of 4.2 MLOC, along with 327 manually examined code patches. The results indicate that developers refactor these systems for various reasons, both specific and tangential to ML; some refactorings correspond to established technical debt categories. In contrast, others do not, and code duplication is a major cross-cutting theme that particularly involved ML configuration and model code, which was also the most refactored. We also introduce 14 and 7 new ML-specific refactorings and technical debt categories, respectively, and put forth several recommendations, best practices, and anti-patterns. The results can potentially assist practitioners, tool developers, and educators in facilitating long-term ML system usefulness.

opencc-by-4.0Oct 2020View details →

An empirical study of automatically-generated tests from the perspective of test smells

Developing software test code can be as or more expensive than developing software production code. Commonly, developers use automated unit test generators to speed up software testing. The purpose of such tools is to shorten production time without decreasing code quality. Nonetheless, unit tests usually do not have a quality check layer above testing code, which might be hard to guarantee the quality of the generated tests. A strategy to verify the tests quality is to analyze the presence of test smells in software test code. Test smells are characteristics in the test code that possibly indicate weaknesses in test design and implementation. Their presence in test code could be used as a quality indicator. In this paper, we present an empirical study to analyze the quality of unit test code generated by automated test tools. We compare the tests generated by two tools (Randoop and EvoSuite) with the existing unit test suite of twenty-one open-source Java projects. We analyze the unit test code to detect the presence of nineteen types of test smells. The results indicated significant differences in the unit test quality when comparing data from the automated unit test generators and existing unit test suites.

opencc-by-4.0May 2020View details →

Replication Package for the Paper: "Code Smells Detection via Code Review: An Empirical Study"

This repository contains the data and results from the paper "Code Smells Detection via Code Review: An Empirical Study" submitted to ESEM 2020.   1. data folder The data folder contains the retrieved 269 reviews that discuss code smells. Each review includes four parts: Code Change URL, Code Smell Term, Code Smell Discussion, and Source Code URL.   2. scripts floder The scripts folder contains the Python script that was used to search for code smell terms and the list of code smell terms. <ul> <li>smell-term/general_smell_terms.txt contains general code smell terms, such as "code smell".</li> <li>smell-term/specific_smell_terms.txt contains specific code smell terms, such as "dead code".</li> <li>smell-term/misspelling_terms_of_smell.txt contains the misspelling terms of 'smell', such as "ssell".</li> <li>get_changes.py is used for getting code changes from OpenStack.</li> <li>get_comments.py is used for getting review comments for each code change.</li> <li>smell_search.py is used for searching review comments that contain code smell terms.</li> </ul>   3. project folder The project folder contains the MAXQDA project files. The files can be opened by MAXQDA 12 or higher versions, which are available at https://www.maxqda.com/ for download. You may also use the free 14-day trial version of MAXQDA 2018, which is available at https://www.maxqda.com/trial for download. <ul> <li>Data Labeling & Encoding for RQ2.mx12 is the results of data labeling and encoding for RQ2, which were analyzed by the MAXQDA tool.</li> <li>Data Labeling & Encoding for RQ3.mx12 is the results of data labeling and encoding for RQ3, which were analyzed by the MAXQDA tool.</li> </ul>

opencc-zeroDec 2014View details →

Data from: How should genes and taxa be sampled for phylogenomic analyses with missing data? An empirical study in iguanian lizards

Targeted sequence capture is becoming a widespread tool for generating large phylogenomic data sets to address difficult phylogenetic problems. However, this methodology often generates data sets in which increasing the number of taxa and loci increases amounts of missing data. Thus, a fundamental (but still unresolved) question is whether sampling should be designed to maximize sampling of taxa or genes, or to minimize the inclusion of missing data cells. Here, we explore this question for an ancient, rapid radiation of lizards, the pleurodont iguanians. Pleurodonts include many well-known clades (e.g., anoles, basilisks, iguanas, and spiny lizards) but relationships among families have proven difficult to resolve strongly and consistently using traditional sequencing approaches. We generated up to 4921 ultraconserved elements with sampling strategies including 16, 29, and 44 taxa, from 1179 to approximately 2.4 million characters per matrix and approximately 30% to 60% total missing data. We then compared mean branch support for interfamilial relationships under these 15 different sampling strategies for both concatenated (maximum likelihood) and species tree (NJst) approaches (after showing that mean branch support appears to be related to accuracy). We found that both approaches had the highest support when including loci with up to 50% missing taxa (matrices with ∼40–55% missing data overall). Thus, our results show that simply excluding all missing data may be highly problematic as the primary guiding principle for the inclusion or exclusion of taxa and genes. The optimal strategy was somewhat different for each approach, a pattern that has not been shown previously. For concatenated analyses, branch support was maximized when including many taxa (44) but fewer characters (1.1 million). For species-tree analyses, branch support was maximized with minimal taxon sampling (16) but many loci (4789 of 4921). We also show that the choice of these sampling strategies can be critically important for phylogenomic analyses, since some strategies lead to demonstrably incorrect inferences (using the same method) that have strong statistical support. Our preferred estimate provides strong support for most interfamilial relationships in this important but phylogenetically challenging group.

opencc-zeroDec 2014View details →

Data from: Empirical and theoretical study of Atelostomate (Echinoidea, Echinodermata) plate architecture: using graph analysis to reveal structural constraints

Describing patterns of connectivity among organs is essential for identifying anatomical homologies among taxa. It is also critical for revealing morphogenetic processes and the associated constraints that control the morphological diversification of clades. This is particularly relevant for studies of organisms with skeletons made of discrete elements such as arthropods, vertebrates, and echinoderms. Nonetheless, relatively few studies devoted to morphological disparity have considered connectivity patterns as a level of morphological organization or developed comparative frameworks with proper tools. Here, we analyze connectivity patterns among apical plates in Atelostomata, the most diversified clade among irregular echinoids. The clade comprises approximately 1600 fossil and Recent species (e.g., 25% of post-Paleozoic species of echinoids) and shows high levels of morphological disparity. Plate connectivity patterns were analyzed using tools and statistics of graph theory. To describe and explore the diversity of connectivity patterns among plates, we symbolized each pattern as a graph in which plates are coded as nodes that are connected pairwise by edges. We then generated a comparative framework as a morphospace of connections, in which the disparity of plate patterns observed in nature was mapped and analyzed. Main results show that apical plate patterns are both highly disparate between and within atelostomate groups and limited in number; overall, they also constitute small, compact, and simple structures compared to possible random patterns. Main traits of the evolution of apical plate patterns reveal the existence of strong morphogenetic constraints that are phylogenetically determined. In contrast, evolutionary radiations within atelostomates were accompanied by a clear increase in disparity, suggesting a release of some constraints at the origin of clades.

openother-openJun 2021View details →

Replication Package for "On the Practice of Semantic Versioning for Ansible Galaxy Roles: An Empirical Study and a Change Classification Model"

Replication package for our analysis of Semantic Versioning in Ansible Galaxy role repositories. This replication package consists of three parts: <ul> <li> Classification Model: Contains Jupyter notebooks used to train and evaluate a Random Forest classification model based on structural features. Training and evaluation data is included. </li> <li> Quantitative Notebooks: Contains Jupyter notebooks used to perform quantitative analyses of versions and changes. </li> <li> data: CSV files of the data used in the Quantitative Notebooks, and the source data for the classification model. Should be downloaded separately fromthe classification model. Should be downloaded separately from <a href="https://doi.org/10.5281/zenodo.4991955">https://doi.org/10.5281/zenodo.4991955</a>. </li> </ul> The data is under the Creative Commons Attribution Share-Alike 4.0 license. The source code is under the GNU General Public License.

opencc-zeroDec 2016View details →

Data from: Detecting environment-dependent diversification from phylogenies: a simulation study and some empirical illustrations

Understanding the relative influence of various abiotic and biotic variables on diversification dynamics is a major goal of macroevolutionary studies. Recently, phylogenetic approaches have been developed that make it possible to estimate the role of various environmental variables on diversification using time-calibrated species trees, paleoenvironmental data, and maximum-likelihood techniques. These approaches have been effectively employed to estimate how speciation and extinction rates vary with key abiotic variables, such as temperature and sea level, and we can anticipate that they will be increasingly used in the future. Here we compile a series of biotic and abiotic paleodatasets that can be used as explanatory variables in these models and use simulations to assess the statistical properties of the approach when applied to these paleodatasets. We demonstrate that environment-dependent models perform well in recovering environment-dependent speciation and extinction parameters, as well as in correctly identifying the simulated environmental model when speciation is environment-dependent. We explore how the strength of the environment-dependency, tree size, missing taxa, and characteristics of the paleoenvironmental curves influence the performance of the models. Finally, using these models, we infer environment-dependent diversification in two empirical phylogenies: temperature-dependence in Cetacea and δ 13C-dependence in Ruminantia. We illustrate how to evaluate the relative importance of abiotic and biotic variables in these two clades and interpret these results in light of macroevolutionary hypotheses. Given the important role paleoenvironments are presumed to have played in species evolution, our statistical assessment of how environment-dependent models behave is crucial for their utility in macroevolutionary analysis.

opencc-zeroDec 2015View details →

Data from: Understanding human queuing behaviour at exits: an empirical study

The choice of the exit to egress from a facility plays a fundamental role in pedestrian modelling and simulation. Yet, empirical evidence for backing up simulation is scarce. In this contribution, we present three new groups of experiments that we conducted in different geometries. We varied parameters such as the width of the doors, the initial location and number of pedestrians which in turn affected their perception of the environment. We extracted and analysed relevant indicators such as distance to the exits and density levels. The results put in evidence the fact that pedestrians use time-dependent information to optimize their exit choice, and that, in congested states, a load balancing over the exits occurs. We propose a minimal modelling approach that covers those situations, especially the cases where the geometry does not show a symmetrical configuration. Most of the models try to achieve the load balancing by simulating the system and solving optimization problems. We show statistically and by simulation that a linear model based on the distance to the exits and the density levels around the exit can be an efficient dynamical alternative.

opencc-zeroDec 2015View details →

Data from: Species diversity can be overestimated by a fixed empirical threshold: insights from DNA barcoding of the genus Cletus (Hemiptera: Coreidae) and the meta-analysis of COI data from previous phylogeographical studies

The use of genetic distances to identify species within the framework of DNA barcoding has to some extent improved the development of biodiversity studies. However, using a fixed empirical threshold to delimit species may lead to overestimating species diversity. In this study, we use a new data set of COI sequences for 366 specimens within the genus of Cletus as well as conduct an analysis on the same genetic data for collected morphologically defined species from previous phylogeographical studies, to test whether high intraspecific genetic divergences are common with the premises of comprehensive sampling. The results indicate C. graminis Hsiao & Cheng 1964, is the same species with C. punctiger (Dallas, 1852) and should be synonymized and that the distributional record of C. pugnator (Fabricius, 1787) in China is correct. High intraspecific genetic differentiations (0%–4.35%) were found in C. punctiger. Furthermore, as to the mined data, the maximum intraspecific K2P distances of 186 species (48.44% of 384) exceed 3%, and 101 species (26.30%) can be divided into two or more clusters with a threshold of 3% in cluster analysis. If genetic distance is used to delimit species boundaries, the minimum interspecific K2P distance of the congeneric species should be considered rather than only using the fixed empirical value; otherwise, the species richness may be overestimated in some cases.

openDec 2023View details →

The Pollution from Obsolete Issue Reports: An Empirical Study

<h1>The Pollution from Obsolete Issue Report: An Empirical Study</h1> <h2>Project summary</h2> In software development, programmers use issue trackers to manage their maintenance issues and record valuable maintenance details in issue reports. Based on these issue reports, programmers have enhanced code comprehension and researchers have mined knowledge from issue reports to assist various programming tasks. Although issue reports are useful, some of them can be obsolete, in that their corresponding commits are overwritten or rolled back, with the evolution of software. The obsolete issue reports can invalidate their references and descriptions, and can have far-reaching impacts on the approaches built on them. To deepen the understanding of obsolete issue reports, we conducted the first empirical study to analyze obsolete issue reports. We consider that an issue report is obsolete if its revisions are partially or totally removed in later commits. To measure how an issue report becomes obsolete, we define an obsolete ratio of an issue report as its deleted lines over all its modified lines. In this paper, we build a tool, ICLinker, to inspect the obsolete issue reports and calculate the obsolete ratios. With ICLinker, we analyze 116,106 commits and 72,136 issue reports that are collected from 9 Apache projects. Taking them as our inputs, we explore four research questions, which concern the distributions, the references, the explanations and the impact of obsolete issue reports. Our findings on these research questions enrich the knowledge of obsolete issue reports, and some are even counterintuitive. For example, we find that obsolete issue reports are mixed with other issue reports. As another example, we find that only a small portion of issue reports are mentioned in code comments, but about half of them are obsolete. We confirm that 48.18% of issue reported recommended by a recent approach are obsolete. As many approaches take issue reports as inputs, obsolete issue reports can affect more research topics than recommending issue reports.

opencc-by-4.0Mar 2024View details →

Replication Package: An Empirical Study on the Characteristics of Reusable Code Clones

This is the updated code and datasets with comments to the code.

opencc-by-4.0Apr 2024View details →

Usefulness and Ease of Use of TikTok as an Academic Support Tool: An Empirical Study of University Students

Open the record for dataset details and reuse information.

openother-openNov 2021View details →

Replication kit for: Problems with SZZ and Features: An empirical study of the state of practice of defect prediction data collection

This is the replication package for our article "Problems with SZZ and Features: An empirical study of the state of practice of defect prediction data collection".  All relevant information is available in the replication-notebook, which is available as executable Jupyter Notebook and as HTML page. The archive release-level-data.tar.gz contains the defect prediction data labeled with IND-JLMIV+R for the 398 releases and is shared for re-use by other researcher for defect prediction experiments.  The archive DO_NOT_USE_release-leve-data.tar.gz contains the contains the defect prediction data labeled with 6M-SZZ and should not be re-used.  The raw data with the MongoDB required to run the Jupyter Notebook is contained in the SmartSHARK Database release 1.0 (https://smartshark.github.io/dbreleases/ / https://doi.org/10.5281/zenodo.4071448). All materials are licensed under the Apache 2.0 License (see LICENSE file).

openapgl-v3Jun 2022View details →

An empirical study of data constraint implementations in Java

Replication package for eponymous EMSE article.