Version Control Software Research Articles

The tale of HORTON: Lessons learned in a decade of scientific software development.

HORTON is a free and open-source electronic-structure package written primarily in Python 3 with some underlying C++ components. While HORTON's development has been mainly directed by the research interests of its leading contributing groups, it is designed to be easily modified, extended, and used by other developers of quantum chemistry methods or post-processing techniques. Most importantly, HORTON adheres to modern principles of software development, including modularity, readability, flexibility, comprehensive documentation, automatic testing, version control, and quality-assurance protocols. This article explains how the principles and structure of HORTON have evolved since we started developing it more than a decade ago. We review the features and functionality of the latest HORTON release (version 2.3) and discuss how HORTON is evolving to support electronic structure theory research for the next decade.

Exploring knowledge management from a software engineering perspective

Context: The knowledge domain of software engineering (SE) gradually expands due to fast emerging technologies and complex organisational processes. The software industry represents a special focus of interest from a Knowledge Management (KM) perspective, as it is characterized by high employee turnover, a high level of outsourced projects, and an accelerated pace of technology innovations. Knowledge management can substantially influence SE knowledge's life cycle, contributing to better structuring of organisational processes of knowledge creation, knowledge transfer, and knowledge sharing. Reflecting on the trends for SE automation with artificial intelligence tools, KM approaches can enable companies and professionals to reconsider the future of SE work. Purpose: The present research aims to identify and investigate how implementing knowledge management principles and processes within the software engineering domain can facilitate the future transformation of software-related jobs. Based on a conceptual model, built upon the literature review, the paper analyses the quantitative data, collected from 91 software experts. Evaluating the impact of both organizational and domain types of SE knowledge, the discussion evaluates the unique value-adding SE processes along with models of how to explore AI applications to automate the SE domain. Results: The outcomes of the analysis identify the models of structuring knowledge management processes in SE both within the technological domain and organisational layers. The discussion section establishes suitable KM methods and approaches for supporting SE job transformation. It identifies the main knowledge management integration practices, demonstrating how combining KM with AI-based innovations may change the SE knowledge flow, improving substantially SE activities like onboarding new team members, monitoring software documentation, version control, and error tracking.

An Automated Framework for Detecting Change in the Source Code and Test Case Change Recommendation

Improvements and acceleration in software development have contributed towards high-quality services in all domains and all fields of industry, causing increasing demands for high-quality software developments. The industry is adopting human resources with high skills, advanced methodologies, and technologies to match the high-quality software development demands to accelerate the development life cycle. In the software development life cycle, one of the biggest challenges is the change management between the version of the source codes. Various reasons, such as changing the requirements or adapting available updates or technological upgrades, can cause the source code's version. The change management affects the correctness of the software service's release and the number of test cases. It is often observed that the development life cycle is delayed due to a lack of proper version control and due to repetitive testing iterations. Hence the demand for better version control-driven test case reduction methods cannot be ignored. The parallel research attempts propose several version control mechanisms. Nevertheless, most version controls are criticized for not contributing toward the test case generation of reduction. Henceforth, this work proposes a novel probabilistic rule-based test case reduction method to simplify the software development's testing and version control mechanism. Software developers highly adopt the refactoring process for making efficient changes such as code structure and functionality or applying changes in the requirements. This work demonstrates very high accuracy for change detection and management. This results in higher accuracy for test case reductions. The outcome of this work is to reduce the development time for the software to make the software development industry a better and more efficient world.

Prioritizing tasks in software development: A systematic literature review.

Task prioritization is one of the most researched areas in software development. Given the huge number of papers written on the topic, it might be challenging for IT practitioners-software developers, and IT project managers-to find the most appropriate tools or methods developed to date to deal with this important issue. The main goal of this work is therefore to review the current state of research and practice on task prioritization in the Software Engineering domain and to individuate the most effective ranking tools and techniques used in the industry. For this purpose, we conducted a systematic literature review guided and inspired by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses, otherwise known as the PRISMA statement. Based on our analysis, we can make a number of important observations for the field. Firstly, we found that most of the task prioritization approaches developed to date involve a specific type of prioritization strategy-bug prioritization. Secondly, the most recent works we review investigate task prioritization in terms of "pull request prioritization" and "issue prioritization," (and we speculate that the number of such works will significantly increase due to the explosion of version control and issue management software systems). Thirdly, we remark that the most frequently used metrics for measuring the quality of a prioritization model are f-score, precision, recall, and accuracy.

Blockchain-Based Decentralized Architecture for Software Version Control

Version control is an important component of configuration management, and most enterprise-level software uses different tools and technologies to manage the software version control such as CVS, Subversion, or Perforce. Following the success of bitcoin, the first practical application of blockchain, it is being implemented in other fields such as healthcare, supply chains, financial management, real estate, electoral systems, and so on. Blockchain’s core features include decentralization, immutability, and interminability. Most version control repositories are centralized and can be modified by external sources, implying that they are in danger of being corrupted or controlled. In this study, we present the BDA-SCV architecture for implementing a version control system in blockchain technology. Our proposed approach would replace the necessity for a centralized system, with a decentralized approach implemented in the blockchain using distributed file storage, for which we will use the InterPlanetary File System (IPFS), which is a distributed file system. The proof of authority (PoA) consensus algorithm will be used to approve the developer communicating modifications to the private blockchain network; the authority will only provide permission and will not be able to add, edit, or delete code files. For each change, a ledger block will be created with a reference to the file stored in the distributed repository. A block cannot be manipulated once it has been created. Smart contracts will be used to register developers, create blocks, and manage the repository. The suggested model is implemented using the Hyperledger Fabric network, and the developer and authorizer ends are built into the dotnet web application.

Generative Logics and Conceptual Clicks: A Case Study of the Method for Design Materialization

Abstract Game design research is caught between epistemologies and disciplines, leading to a lack of grounded methodologies. Without such methodological approaches, we cannot support evidence-based claims about game design. The Method for Design Materialization (MDM) is a methodological approach to capturing game design via software version control. By embracing a time-sliced representation of a game throughout its development and pairing it with explicit materializations of design thinking through reflective writing, we believe significant progress can be made in understanding and extrapolating from the design process.

Git going with LEGO

Git, an open source version control software, is difficult to both teach and learn because it conceals its work in a hidden directory and is often deployed using a command line interface. Yet, version control is an essential tool of reproducible research. Two librarians formed a playful partnership to experiment with teaching Git using LEGO, an approach inspired by our Carpentries Instructor certifications and one’s LEGO Serious Play certification. Our method combines novice-centric Carpentries pedagogy with theories of play, constructionism, constructivism, conceptual metaphor, and the hand-mind connection that are foundational to LEGO Serious Play. We share details of developing, testing, and assessing this Git-LEGO combination. Our preliminary study indicates that our LEGO activity may increase learners' short-term retention of Git commands. We discuss future directions for our research and our experiences as academic librarians in a playful partnership.

Towards Creative Version Control

Version control systems are powerful tools for managing history information and shaping personal and collaborative processes. While many complex tools exist for software engineering, and basic functionality for capturing versions is often found in collaborative applications such as text editors and design layout tools, these systems are not attuned to the needs and behaviors of creative practitioners within those domains, and fail to support creative practitioners in many others. Through 18 semi-structured interviews across diverse domains of creativity, we investigate how creative practitioners use version histories in their process. With the familiar paradigms and features of software version control as an organizing structure, we discuss how these creative practitioners embrace, challenge, and complicate uses of version histories in four ways: using versions as a palette of materials, providing confidence and freedom to explore, leveraging low-fidelity version capture, and reflecting on and reusing versions across long time scales. We discuss how the themes present across this wide range of mediums and domains can provide insight into future designs and uses of version control systems to support creative process.

TTDFT: A GPU accelerated Tucker tensor DFT code for large-scale Kohn-Sham DFT calculations

We present the Tucker tensor DFT (TTDFT) code which uses a tensor-structured algorithm with graphic processing unit (GPU) acceleration for conducting ground-state DFT calculations on large-scale systems. The Tucker tensor DFT algorithm uses a localized Tucker tensor basis computed from an additive separable approximation to the Kohn-Sham Hamiltonian. The discrete Kohn-Sham problem is solved using Chebyshev filtered subspace iteration method that relies on matrix-matrix multiplications of a sparse symmetric Hamiltonian matrix and a dense wavefunction matrix, expressed in the localized Tucker tensor basis. These matrix-matrix multiplication operations, which constitute the most computationally intensive step of the solution procedure, are GPU accelerated providing ∼8-fold GPU-CPU speedup for these operations on the largest systems studied. The computational performance of the TTDFT code is presented using benchmark studies on aluminum nano-particles and silicon quantum dots with system sizes ranging up to ∼7,000 atoms. Program summaryProgram Title: TTDFT: Tucker tensor density functional theory codeCPC Library link to program files:https://doi.org/10.17632/8dgmcs8ys2.1Licensing provisions: LGPLProgramming language: C/C++External routines/libraries: TuckerMPI (https://gitlab.com/tensors/TuckerMPI), cuBLAS (https://docs.nvidia.com/cuda/cublas/index.html), cuSparse (https://docs.nvidia.com/cuda/cusparse/index.html), ALGLIB (http://www.alglib.net/), Boost (https://www.boost.org/), BLAS (http://www.netlib.org/blas/), LAPACK (http://www.netlib.org/lapack/), PETSc (https://www.mcs.anl.gov/petsc), SLEPc (http://slepc.upv.es)Nature of problem: Real-space Kohn-Sham density functional theory calculations using localized Tucker tensor basis.Solution method: We present a real-space Kohn-Sham density functional theory code based on tensor-structured techniques with GPU acceleration. Tensor-structured techniques are adopted for computing a Tucker tensor basis, representing the eigenfunctions of an additive separable approximation to the Kohn-Sham Hamiltonian. The Tucker tensor basis is further localized using L1 regularization to improve the sparsity of the Kohn-Sham Hamiltonian matrix, and improve the computational efficiency and parallel scalability of the proposed algorithm. The solution to the Kohn-Sham problem in the localized Tucker tensor basis is computed using the Chebyshev filtered subspace iteration (ChFSI) method.Additional comments including restrictions and unusual features: The code works with Troullier-Martin (TM) pseudopotentials in Kleinman-Bylander form. The current release supports only non-periodic DFT calculations with the local density approximation (LDA) for exchange-correlation functional.This TTDFT project uses GitHub via Git, a free distributed version control software. The archived version at the time of submission of this work can be found on the CPC program library through program files DOI provided above. The GitHub repository of this project can be found on https://github.com/ttdftdev/ttdft_public.

Curation of BIDS (CuBIDS): A workflow and software package for streamlining reproducible curation of large BIDS datasets

The Brain Imaging Data Structure (BIDS) is a specification accompanied by a software ecosystem that was designed to create reproducible and automated workflows for processing neuroimaging data. BIDS Apps flexibly build workflows based on the metadata detected in a dataset. However, even BIDS valid metadata can include incorrect values or omissions that result in inconsistent processing across sessions. Additionally, in large-scale, heterogeneous neuroimaging datasets, hidden variability in metadata is difficult to detect and classify. To address these challenges, we created a Python-based software package titled “Curation of BIDS” (CuBIDS), which provides an intuitive workflow that helps users validate and manage the curation of their neuroimaging datasets. CuBIDS includes a robust implementation of BIDS validation that scales to large samples and incorporates DataLad––a version control software package for data––as an optional dependency to ensure reproducibility and provenance tracking throughout the entire curation process. CuBIDS provides tools to help users perform quality control on their images’ metadata and identify unique combinations of imaging parameters. Users can then execute BIDS Apps on a subset of participants that represent the full range of acquisition parameters that are present, accelerating pipeline testing on large datasets.

A Survey of Estonian Video Game Industry Needs

Designing a video game design and development curriculum in higher education is a challenging task. Information about the needs of the respective industry certainly helps. In this paper, we have surveyed Estonian video game development companies to determine their current needs when it comes to knowledge areas, software tools, languages, abilities, and contextual fluencies. The survey is based on a similar survey conducted a decade ago and this paper compares the current results with those found earlier.
 
 Compared to the prior survey, we have found significant differences in the rated importance of knowledge in optimization, version control technologies, the C, C++, and C# programming languages, and the time management ability for video game development companies looking to hire university graduates. We have also extended the previous survey to include a contemporary selection of game design and development tools. Based on that, we have determined a strong need for graduates with skills specifically in Unity and Unreal Engine game engines, Photoshop raster image editing software, and Git version control software.
 
 While most of our results are largely consistent with the previous research, our added survey items like visual languages and game engines bring the results to the modern context. This allows curriculum designers and managers to see the differences regarding the landscape of industry needs for their graduates and thus make more informed decisions in their work.

Golden Mutator Recommendation Based on Mutation Pattern Mining

Mutation testing is widely used in the research of evaluation and optimization of test set quality, and has been paid attention to the study of bug localization and fixing. But one inherent problem of mutation testing is huge computation cost. Selective mutation is an important method to reduce mutation testing cost. However, the existing selective mutation researches indicate that there is no universal selection strategy. This paper proposes a method which integrates with historical software data mining to recommend suitable mutator for program under test. The basic idea of the method is in the software version control system, any pair of nonfixed and post-fixed programs can be original program and mutant of each other. The edit performed during bug fixing contains mutators, and such mutator can guide buggy program to correct program, hence it is called Golden Mutator. The basic method is to compare the buggy files and the corresponding fixed files in the version control system, obtain historical faulty statements and their fix editing operations, thereby accumulating the bug-fix instance base, and then mining mutation patterns from it. Before mutating the target statement, we first find out faulty instances similar to the target statement, and use their fixing edits to match with the mutation pattern, so as to get the golden mutator applicable to the target statement. This paper uses Defects4j dataset in the test, verifies the accuracy of the proposed recommendation method, and further uses the method in bug localization. Compared to fixedly selected mutators, when applying the golden mutator recommended by using the proposed method, the average accuracy of bug localization is higher.

On the Application of Agile Project Management Techniques, V-Model and Recent Software Tools in Postgraduate Theses Supervision

Due to the nature of most postgraduate theses in control engineering and their similarities to industrial and software engineering projects, invoking novel project control techniques could be effective. In recent decades, agile techniques have attracted popularity thanks to their attributes in delivering successful projects. Hence exploiting those methods in education and thesis supervision of engineering topics can facilitate the process. On the other hand, because of the limitations imposed by the CoVid19 pandemic, the integration of well-established online tools in collaborative education is noteworthy. This paper proposes an application of the agile project management method for the supervision of postgraduate students’ theses in the general field of engineering. The study extends a Scrum technique combined with approved systems engineering and team working tools such as Jira Software, Microsoft Teams, and Git version control (Github website). A custom designed V-model to nail an outstanding thesis is presented. The overall blended method is beneficial to provide feedback and self-assessment aid for the students and the supervisors. Employing this technique has shown promising progress in easing the supervision of students whilst helping them to manage their projects.

Model Architecture for Subversion Software Repositories System

In the development cycle of any software, software evolution plays an important role. Software Evolution is essential and challenges characteristics in the field of software engineering. Many research studies have concluded that 60-80% of efforts are spent on the evolution and maintenance of the software. Software repositories, for example, version control and bug tracking systems, are vital fragments of numerous software maintenance activities. The version control system is an incremental version tracking system, introduced to avoid unnecessary overwriting of files such as programming code, web pages, and records. It also helps to decrease the confusion affected by duplicate or outdated data. In this proposed research, the SVN repository was maintained and analyzed for msitone.wikispaces.com to minimize the efforts as well as resources for future users. Two semesters' data was taken as the observations for the analysis. The obtained archives were implemented and deployed for postulating the local archives to the online server via the Visual SVN server, allowing remote users to access a repository.The tortoise SVN tool is used as an SVN client to access the repository of Wiki spaces. Analyses were observed with and without implementing the SVN repository. The result shows that implementing the SVN repositories is helpful for the maintenance of the Wiki spaces. It also reduces the cost, time and efforts for their evolution. Whereas without implementing the SVN repositories, Wikis paces were just supposed to be building the house byputting each brick from the start.

A Beginner's Guide to Conducting Reproducible Research

A Beginner's Guide to Conducting Reproducible Research

AtChem (version 1), an open-source box model for the Master Chemical Mechanism

Abstract. AtChem is an open-source zero-dimensional box model for atmospheric chemistry. Any general set of chemical reactions can be used with AtChem, but the model was designed specifically for use with the Master Chemical Mechanism (MCM, http://mcm.york.ac.uk/, last access: 16 January 2020). AtChem was initially developed within the EUROCHAMP project as a web application (AtChem-online, https://atchem.leeds.ac.uk/webapp/, last access: 16 January 2020) for modelling environmental chamber experiments; it was recently upgraded and further developed into a stand-alone offline version (AtChem2), which allows the user to run complex and long simulations, such as those needed for modelling of intensive field campaigns, as well as to perform batch model runs for sensitivity studies. AtChem is installed, set up and configured using semi-automated scripts and simple text configuration files, making it easy to use even for inexperienced users. A key feature of AtChem is that it can easily be constrained to observational data which may have different timescales, thus retaining all the information contained in the observations. Implementation of a continuous integration workflow, coupled with a comprehensive suite of tests and version control software, makes the AtChem code base robust, reliable and traceable. The AtChem2 code and documentation are available at https://github.com/AtChem/ (last access: 16 January 2020) under the open-source MIT License.

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.

Reproducibility and Transparency by Design

The reproducibility of bioinformatics analyses can be elevated to equal status with biological discovery. To achieve this, reproducibility must become part of the process, not an afterthought. Graphical Abstract Highlights • Repositories are enabling sharing of data. • Sharing analyses remains a major stumbling block for reproducibility. • Three simple steps can enable sharing analyses, with nominal effort.

A method for software trusted update on network security equipment

Network security equipment plays an important role in preventing network security attacks. However, with the change of network environment and the upgrade of network attack means, the protection ability of the security software on the existing network security equipment will gradually decrease with time. For some large organizations or enterprises, their information security operations centers lack attention to software version control and software update processes for network security equipment, resulting in some security crises in the software update process. In this paper, we propose a method for software trusted update on network security equipment. This method can provide trusted identify authentication, secure data transmission and effective software version control. It enables the network security operations centers to more safely manage software update process on network security equipment. This method uses the functions of Trusted Cryptography Module to provide trusted execution environment. In this paper, we had introduced the process design, the prototype design and theoretical analysis to explain the feasibility and safety of this method.

Software Consistency Checking Method for Distribution Terminal based on Chaotic Map

Distribution terminal system software is the core carrier of its function realization and performance stability. In the process of development and operation and maintenance of distribution terminals, software versions are confusing and inconsistent with the archived versions due to technical upgrades, version management, and regulatory deficiencies. It makes some functions unable to operate normally, performance indicators can not be met, equipment on-line rate decreased, and seriously affecting the operation and maintenance and practicality of distribution automation system. In order to strengthen the software version control of distribution automation terminal equipment, the feature information of software version was extracted by analysing the executable files of terminal software, and then the priority was divided according to the feature information. The MD5 algorithm and CRC32 checking algorithm were used to calculate the comparison factor, which then was encrypted by using pseudo random code generated by Logistic chaotic map. The model and method of software version consistency detection for distribution terminal were established.