Source Code Management Systems Research Articles

AUTOMATING BUILD OF EMBEDDED LINUX BINARIES IN A HIGH-PERFORMANCE COMPUTING CLUSTER

A method for automating the build process of the embedded Linux operating system binary images in a high-performance computing cluster based on continuous integration and continuous deployment technology is discussed. The method proposed can significantly reduce software design time, free up computing resources at local workstations and organize joint work on a team project. A practical example of setting up the software tools necessary to compile the boot-loader, embedded Linux kernel and root file system for BeagleBone Black device with an ARM Cortex A8 processor is provided. Basic requirements for the server and workstation software are formulated. The materials of the article can be used to organize system software design for Internet of Things devices effectively, as well as for educational purposes. Tools used to develop embedded operating systems based on Linux Yocto as well as GitLab source code management system and configuring of CI/CD feature are described. The build system environment proposed includes GitLab service installed on a high-performance virtual machine in a computing cluster and set of workstations connected to the local network. The project repository is physically located on the server and managed by GitLab service. Docker virtualization is used to isolate build process from the server operating system. Building of operating system image is started automatically using CI/CD runner script, every time changes to the source code of the project are made. Git protocol is used to modify project repository remotely. Intermediate compilation data is stored outside of the Docker sandbox to prevent data integrity between compilation events. This data includes a significant amount of third-party library source code downloaded from external Linux repositories on the Internet. Thus, rebuilding the project after making changes does not require a complete rebuild and reloading of library sources, and takes much less time. Requirements for the workplace of a development engineer are minimized because the main computing load is transferred to a remote server. The proposed method of building an image of the Linux Yocto operating system allows manage team to work on a project and significantly increases the speed of the project rebuild procedure, therefore, reduces the time spent on designing and debugging system software for embedded systems. The effectiveness of the proposed method was confirmed practically with sample project Linux Yocto for the BeagleBone Black minicomputer based on the ARM Cortex A8 processor. The article contains examples of settings taken from this project. The proposed method can be used to study design of system software for embedded systems. Handson training sessions are a good example of team-based software development in a time-constrained environment.

Natural Language Processing Application on Commit Messages: A Case Study on HEP Software

Version Control and Source Code Management Systems, such as GitHub, contain a large amount of unstructured historical information of software projects. Recent studies have introduced Natural Language Processing (NLP) to help software engineers retrieve information from a very large collection of unstructured data. In this study, we have extended our previous study by increasing our datasets and machine learning and clustering techniques. We have followed a complex methodology made up of various steps. Starting from the raw commit messages we have employed NLP techniques to build a structured database. We have extracted their main features and used them as input of different clustering algorithms. Once each entry was labelled, we applied supervised machine learning techniques to build a prediction and classification model. We have developed a machine learning-based model to automatically classify commit messages of a software project. Our model exploits a ground-truth dataset that includes commit messages obtained from various GitHub projects belonging to the High Energy Physics context. The contribution of this paper is two-fold: it proposes a ground-truth database and it provides a machine learning prediction model that automatically identifies the more change-prone areas of code. Our model has obtained a very high average accuracy (0.9590), precision (0.9448), recall (0.9382), and F1-score (0.9360).

A framework for rapid virtual prototyping: a case study with the Gunnerus research vessel

ABSTRACT Virtual prototypes (VPs) are digital models that mock-up existing or conceptual systems' behaviour. In offshore operations, VPs find usages in design, proof of concept for new equipment or method, control system testing, procedure planning, and expert crew training. Moreover, VP can be used in full mission simulators with crews of maritime and offshore engineers, in which case they integrate with control systems such as handles and dynamic positioning systems. Putting the human in the loop sets high requirements for the fidelity of the visual 3D-models and the mathematical models' validity. VPs are thus time-consuming to create and difficult to validate, even based on an existing offshore system. This paper presents an innovative framework for rapid virtual prototyping of ships for hardware and human in the loop simulations and validates the results with data gathered in a sea trial performed on a research vessel, with satisfying results for position keeping. Abbreviations: CLI, Command line interpreter; DP, Dynamic positioning system: ship equipment used to maintain position and heading; DM, Damping matrix; Force FBK, Force Feedback Thruster1; HIL, Hardware in the loop; HITL, Human in the loop; JNI, Java native interface; LC, Loading condition; RAO, Response amplitude operator; RPM, Revolutions per minute; RPM FBK, RPM Feedback Thruster2/3 (Main/Azimuth); SCM, Source code management system; SOG, Speed over ground; VP, Virtual prototyping/prototype; VST, Virtual sea trial; sea trial performed in a simulation

A software environment for effective reliability management for pulsed power design

The reliable design of magnetically insulated transmission lines (MITLs) for very high current pulsed power machines must be accomplished in the future by utilizing a variety of sophisticated modeling tools. The complexity of the models required is high and the number of sub-models and approximations large. The potential for significant analyst error using a single tool is large, with possible reliability issues associated with the plasma modeling tools themselves or the chosen approach by the analyst to solve a given problem.We report on a software infrastructure design that provides a workable framework for building self-consistent models and constraining feedback to limit analyst error. The framework and associated tools aid the development of physical intuition, the development of increasingly sophisticated models, and the comparison of performance results. The work lays the computational foundation for designing state-of-the-art pulsed-power experiments. The design and useful features of this environment are described. We discuss the utility of the Git source code management system and a GitLab interface for use in project management that extends beyond software development tasks.

Project repositories for machine learning with TensorFlow

Abstract In machine learning, models capture intelligence from data using algorithms implemented on frameworks like TensorFlow. Models learn during the training phase; an iterative process in which parameters are tuned to improve the prediction accuracy. Software repositories are used to save the artifacts of model development so that they can be modified in subsequent releases and shared between development teams. Issues in saving the state of machine learning projects is different from standard software practices. Machine learning models are equivalent to binary executable programs and ideally one should be able to recreate the model from the information preserved in project repositories. Recreation of the model becomes necessary when there is a change in the development team as part of the product transition. Retraining of models also becomes necessary when the inaccuracy in the predictions made on new data increases beyond the acceptable limit. When traditional source code management systems are used for maintaining repositories of machine learning projects, we face challenges in keeping complete information required for model development starting from saved states. This paper presents the results of the studies conducted to identify the challenges in maintaining TensorFlow machine learning projects in repositories. Some of the existing tools are compared and recommendations are made to improve the ease of recreation of machine learning models by saving complete information in project repositories maintained in normal source code control systems.

A Prologue of Git and SVN

Version Control Software or Revision Control Software are the most important things in the world of software development. In this paper, we have described two version control tools: Git and Apache Subversion. Git comes as free and open source code management and version control system which is disseminated with the GNU general public license. Apache Subversion abbreviated as SVN is one amongst a software versioning and revision control systems given as open source under Apache License. Git design, its functionality, and usage of Git and SVN are discussed in this paper. The goal of this research paper is to accentuate on GIT and SVN tools, evaluate and compare five version control tools to ascertain their usage and efficacy.

Ability Level of Git Hub Amongst Computer Science Students

Source code management is one of the most vital tools in modern software development. Moreover, the open source initiative requires a method to distribute their code effectively. GitHub is one of the most popular web-based version control systems that offers version control and source code management. Therefore, it is important to introduce GitHub as early as possible to computer science students. Our objective is to observe the use of GitHub as a source code management system. We perform a survey targeted at the students and collected 298 answers. We also perform a short interview amongst the lecturer regarding their familiarity with GitHub and source control management in general. The survey result shows that while GitHub is quite popular amongst the student, the knowledge and experience of using it is considerably low. Similar responses were received from the lecturer that argues that the role of GitHub in classroom is redundant. The details of the result are thoroughly discussed in this paper

Change profile analysis of open-source software systems to understand their evolutionary behavior

Source code management systems (such as git) record changes to code repositories of Open-Source Software (OSS) projects. The metadata about a change includes a change message to record the intention of the change. Classification of changes, based on change messages, into different change types has been explored in the past to understand the evolution of software systems from the perspective of change size and change density only. However, software evolution analysis based on change classification with a focus on change evolution patterns is still an open research problem. This study examines change messages of 106 OSS projects, as recorded in the git repository, to explore their evolutionary patterns with respect to the types of changes performed over time. An automated keyword-based classifier technique is applied to the change messages to categorize the changes into various types (corrective, adaptive, perfective, preventive, and enhancement). Cluster analysis helps to uncover distinct change patterns that each change type follows. We identify three categories of 106 projects for each change type: high activity, moderate activity, and low activity. Evolutionary behavior is different for projects of different categories. The projects with high and moderate activity receive maximum changes during 76–81 months of the project lifetime. The project attributes such as the number of committers, number of files changed, and total number of commits seem to contribute the most to the change activity of the projects. The statistical findings show that the change activity of a project is related to the number of contributors, amount of work done, and total commits of the projects irrespective of the change type. Further, we explored languages and domains of projects to correlate change types with domains and languages of the projects. The statistical analysis indicates that there is no significant and strong relation of change types with domains and languages of the 106 projects.

KAJIAN VERSION CONTROL DALAM MENDUKUNG KINERJA DEVELOPER PADA PT. JAWASOFT

Abstract - Version Control is a system that keeps track of the historical changes and usage of a resource within an integrated storage media. Version Control (also widely known as a Source Code Management System) is a crucial component for any team working on software development. Version control will keep a record of every single source code change to a file or document, such as historical data, comparisons between different versions, and even access rights to that file or document. A wise choice on which Version Control system to use will have a massive effect on the performance of the Software Developers. Hence many factors must be acknowledged in the process of making the decision of which product to use. The objective of this research is to find which features/attributes of a Version Control System are most influential in the aforementioned decision making process. The research explores the features/attributes inherent in three well known Version Control systems – Subversion, Mercurial and Git. This is done using ISO 9126 as a criteria. Influential factors in the decision making process are gauged using a descriptive analysis technique, and the instrument used in this case is the Analytical Hierarchy Process (AHP). Extensive questionnaire data was 'fed' into the AHP technique, and based on the results obtained, it was calculated that Subversion is the more favorable Version Control system compared to Mercurial and Git. It can thus be concluded that Subversion is the best Version Control system to support the productivity of software developers. Keywords: Version Control, Subversion, Mercurial, Git, Analytical Hierarchy Process.

MDSplus quality improvement project

MDSplus is a data acquisition and analysis system used worldwide predominantly in the fusion research community. Development began 29 years ago on the OpenVMS operating system. Since that time there have been many new features added and the code has been ported to many different operating systems. There have been contributions to the MDSplus development from the fusion community in the way of feature suggestions, feature implementations, documentation and porting to different operating systems. The bulk of the development and support of MDSplus, however, has been provided by a relatively small core developer group of three or four members. Given the size of the development team and the large number of users much more effort was focused on providing new features for the community than on keeping the underlying code and documentation up to date with the evolving software development standards. To ensure that MDSplus will continue to provide the needs of the community in the future, the MDSplus development team along with other members of the MDSplus user community has commenced on a major quality improvement project. The planned improvements include changes to software build scripts to better use GNU Autoconf and Automake tools, refactoring many of the source code modules using new language features available in modern compilers, using GNU MinGW-w64 to create MS Windows distributions, migrating to a more modern source code management system, improvement of source documentation as well as improvements to the www.mdsplus.org web site documentation and layout, and the addition of more comprehensive test suites to apply to MDSplus code builds prior to releasing installation kits to the community. This work should lead to a much more robust product and establish a framework to maintain stability as more enhancements and features are added. This paper will describe these efforts that are either in progress or planned for the near future.

Understanding Open Source Software Evolution Using Fuzzy Data Mining Algorithm for Time Series Data

Source code management systems (such as Concurrent Versions System (CVS), Subversion, and git) record changes to code repositories of open source software projects. This study explores a fuzzy data mining algorithm for time series data to generate the association rules for evaluating the existing trend and regularity in the evolution of open source software project. The idea to choose fuzzy data mining algorithm for time series data is due to the stochastic nature of the open source software development process. Commit activity of an open source project indicates the activeness of its development community. An active development community is a strong contributor to the success of an open source project. Therefore commit activity analysis along with the trend and regularity analysis for commit activity of open source software project acts as an important indicator to the project managers and analyst regarding the evolutionary prospects of the project in the future.

Studying the laws of software evolution in a long-lived FLOSS project.

Some free, open-source software projects have been around for quite a long time, the longest living ones dating from the early 1980s. For some of them, detailed information about their evolution is available in source code management systems tracking all their code changes for periods of more than 15 years. This paper examines in detail the evolution of one of such projects, glibc, with the main aim of understanding how it evolved and how it matched Lehman's laws of software evolution. As a result, we have developed a methodology for studying the evolution of such long-lived projects based on the information in their source code management repository, described in detail several aspects of the history of glibc, including some activity and size metrics, and found how some of the laws of software evolution may not hold in this case. © 2013 The Authors. Journal of Software: Evolution and Process published by John Wiley & Sons Ltd.

Ring: A unifying meta-model and infrastructure for Smalltalk source code analysis tools

Source code management systems record different versions of code. Tool support can then compute deltas between versions. To ease version history analysis we need adequate models to represent source code entities. Now naturally the questions of their definition, the abstractions they use, and the APIs of such models are raised, especially in the context of a reflective system which already offers a model of its own structure. We believe that this problem is due to the lack of a powerful code meta-model as well as an infrastructure. In Smalltalk, often several source code meta-models coexist: the Smalltalk reflective API coexists with the one of the Refactoring engine or distributed versioning system such as Monticello or Store. While having specific meta-models is an adequate engineered solution, it multiplies meta-models and it requires more maintenance efforts (e.g., duplication of tests, transformation between models), and more importantly hinders navigation tool reuse when meta-models do not offer polymorphic APIs. As a first step to provide an infrastructure to support history analysis, this article presents Ring, a unifying source code meta-model that can be used to support several activities and proposes a unified and layered approach to be the foundation for building an infrastructure for version and stream of change analyses. We re-implemented three tools based on Ring to show that it can be used as the underlying meta-model for remote and off-image browsing, scoping refactoring, and visualizing and analyzing changes. As a future work and based on Ring we will build a new generation of history analysis tools.

On the reproducibility of empirical software engineering studies based on data retrieved from development repositories

Among empirical software engineering studies, those based on data retrieved from development repositories (such as those of source code management, issue tracking or communication systems) are specially suitable for reproduction. However their reproducibility status can vary a lot, from easy to almost impossible to reproduce. This paper explores which elements can be considered to characterize the reproducibility of a study in this area, and how they can be analyzed to better understand the type of reproduction studies they enable or obstruct. One of the main results of this exploration is the need of a systematic approach to asses the reproducibility of a study, due to the complexity of the processes usually involved, and the many details to be taken into account. To address this need, a methodology for assessing the reproducibility of studies is also presented and discussed, as a tool to help to raise awareness about research reproducibility in this field. The application of the methodology in practice has shown how, even for papers aimed to be reproducible, a systematic analysis raises important aspects that render reproduction difficult or impossible. We also show how, by identifying elements and attributes related to reproducibility, it can be better understood which kind of reproduction can be done for a specific study, given the description of datasets, methodologies and parameters it uses.

Are Developers Fixing Their Own Bugs?

The process of fixing software bugs plays a key role in the maintenance activities of a software project. Ideally, code ownership and responsibility should be enforced among developers working on the same artifacts, so that those introducing buggy code could also contribute to its fix. However, especially in FLOSS projects, this mechanism is not clearly understood: in particular, it is not known whether those contributors fixing a bug are the same introducing and seeding it in the first place. This paper analyzes the comm-central FLOSS project, which hosts part of the Thunderbird, SeaMonkey, Lightning extensions and Sunbird projects from the Mozilla community. The analysis is focused at the level of lines of code and it uses the information stored in the source code management system. The results of this study show that in 80% of the cases, the bug-fixing activity involves source code modified by at most two developers. It also emerges that the developers fixing the bug are only responsible for 3.5% of the previous modifications to the lines affected; this implies that the other developers making changes to those lines could have made that fix. In most of the cases the bug fixing process in comm-central is not carried out by the same developers than those who seeded the buggy code.

On-line construction of parameterized suffix trees for large alphabets

We consider on-line construction of the suffix tree for a parameterized string, where we always have the suffix tree of the input string read so far. This situation often arises from source code management systems where, for example, a source code repository is gradually increasing in its size as users commit new codes into the repository day by day. We present an on-line algorithm which constructs a parameterized suffix tree in randomized O ( n ) time, where n is the length of the input string. Our algorithm is the first randomized linear time algorithm for the on-line construction problem.

Protecting the process [source code management

The author mentions that building software using a team of multiple programmers working from different time zones brings production efficiencies, but managing the source code effectively is essential. Mention source code management (SCM) to most developers, and there is the strong possibility that they will think about version control of individual source-code files. At its most basic, version control is a method of maintaining separate versions of files, rather than simply overwriting the old ones.The most up-to-date SCM systems offer developers and project managers a way of implementing an efficient and productive workflow: they go beyond simple version control they can streamline project management.

Tools for the Study of the Usual Data Sources found in Libre Software Projects

Due to the open nature of Free/Libre/Open Source software projects, researchers have gained access to a rich set of development-related information. Although this information is publicly available on the Internet, obtaining and analyzing it in a convenient way is not an easy task and many considerations have to be taken into account. In this paper we present the most important data sources that can be found in libre software projects and that are studied by the research community: source code, source code management systems, mailing lists and bug tracking systems. We will give advice for the problems that can be found when retrieving and preparing the data sources for a posterior analysis, as well as provide information about the tools that support these tasks.

Implementing CFR 21 part 11 for SAS®without tears or joins

Abstract This paper argues that the best way to construct an easy-to-program in and CFR 21 part 11 compliant environment for SAS® programming is by using a version control system, specifically the IBM Rational product ClearCase®. It concentrates on architectural issues to do with protecting data and outputs as well as programs, and stresses the importance of linking an output with its constituent parts. The main reasons for using ClearCase® are explained and illustrated with examples from a successful implementation. Enough information about ClearCase® is included to show why it is uniquely suited, among all Source Code Management Systems, for this task. Although this paper focuses on SAS®, the environment can also be used for other programs with little or no changes.

Unified software repositories for Wendelstein 7-X: Workflow elements for fusion software development

Software development for a large project like Wendelstein 7-X (W7-X) requires an appropriate development process to provide a reliable environment supporting the coordinated work of scientific and engineering stakeholders. The first step to achieve this goal was the installation of a central source code management system (SCM). Besides being a code base it provides functions allowing the specification of a release procedure by introducing levels of acceptance specified by appropriate quality criteria. The SCM system serves as a starting point for automatic generation of standard code documentation and for performing automatic testing procedures on standardized integration platforms. In order to provide a universal documentation platform for the multi programming language environment at W7-X the DocSys system has been developed which allows to employ any (language specific) document generator producing html-pages for presentation via internet. An automatic integration testing environment is still being prepared and not yet in standard use.