Software development is still based on manufactory production, and most of the programming code is still hand-crafted. Software development is very far away from the ultimate goal of industrialization in software production, something which has been achieved long time ago in the other industries. The lack of software industrialization creates an inability to cope with fast and frequent changes in user requirements, and causes cost and time inefficiencies during their implementation. Analogous to what other industries had done long time ago, industrialization of software development has been proposed using the concept of software factories. We have accepted this vision about software factories, and developed our own software factory which produces three-layered ASP.NET web applications. In this paper we report about our experience with using this approach in the process of software development, and present comparative results on performances and deliverables in both traditional development and development using software factories.
Software technology has high impact on the global economy as in many sectors of contemporary society. As a product enabling the most varied daily activities, the software product has to be produced reflecting high quality. Software quality is dependent on its development that is based in a large set of software development processes. However, the implementation and continuous improvement of software process aimed at software product should be carefully institutionalized by software development organizations such as software factories, testing factories, V&V organizations, among others. The ins…
The process of contracting software factories within the scope of the Federal Public Administration (APF, in Portuguese) in Brazil has undergone some changes due to legislative alterations and a model has been proposed to improve the rendering of services regarding delivering results. Software factory contracts based on predictive processes and on the metrics of Function Points are the target of criticisms and have issues in achieving results, as verified in previous research. The initial objective of the study now proposed will be to define a process model for formulating metrics that can be …
We conducted a set of Rapid Reviews to characterize Internet of Things facets. We formatted a generic meta-protocol that was instantiated for each of the six facets presented (Connectivity, Things, Behavior, Smartness, Interactivity, and Environment)and considering the issue of Security, one of the most important and frequent challenges in the context of IoT. The meta-protocol is detailed and the results of each review are presented.
Context: Context-aware contemporary software systems (CACSS) are mainstream. Furthermore, they present challenges for current engineering practices. These challenges are distinctively present when testing CACSS, as the variation of context deepens the limitations of available software testing practices and technologies. Objective: To understand how the industry deals with the variation of context when testing CACSS. Method: A Rapid Review was commissioned to uncover the necessary evidence to achieve the objectives. Results: Our results show that current research initiatives aim to generate or …
Introduction of DevOps into the software development life cycle represents a cultural shift in the IT culture, amalgamating development and operations to improve delivery speed in a rapid and maintainable manner. At the same time, security threats and breaches are expected to grow as more enterprises move to new agile frameworks for rapid product delivery. Meanwhile, DevSecOps is a mindset change that revolutionizes software development by embedding security at each step of the software cycle, leading to resilient software. This paper discusses a framework organization can use to embed DevSecO…
Artificial Intelligence (AI) is making a significant impact in multiple areas like medical, military, industrial, domestic, law, arts as AI is capable to perform several roles such as managing smart factories, driving autonomous vehicles, creating accurate weather forecasts, detecting cancer and personal assistants, etc. Software testing is the process of putting the software to test for some abnormal behaviour of the software. Software testing is a tedious, laborious and most time-consuming process. Automation tools have been developed that help to automate some activities of the testing proc…
The practice of continuous deployment has enabled companies to reduce time-to-market by increasing the rate at which software can be deployed. However, deploying more frequently bears the risk that occasionally defective changes are released. For Internet companies, this has the potential to degrade the user experience and increase user abandonment. Therefore, quality control gates are an important component of the software delivery process. These are used to build confidence in the reliability of a release or change. Towards this end, a common approach is to perform a canary test to evaluate …
Modern platform software delivery cost increases rapidly as it usually needs to align with many hardware and silicon's TTMs, feature evolvement and involves hundreds of engineers. In this paper, citing one ultra-large-scale software - Intel Media Driver as an example, we analyze the hotspots leading to delivery cost increase in continuous software development, the challenges on our software design and our experiences on software delivery cost shrink against the targeted design enhancements. We expect the identified hotspots can help more researchers to form the corresponding research agendas a…
Context: DevOps and microservices are acknowledged to be important new paradigms to tackle contemporary software demands and provide capabilities for rapid and reliable software development. Industrial reports show that they are quickly adopted together in massive software companies. However, because of the technical and organizational requirements, many difficulties against efficient implementation of the both emerge in real software teams. Objectives: This study aims to discover the organization, benefits and issues of software teams using DevOps & microservices from an immersive perspective…
Modern software development is based on a series of rapid incremental changes collaboratively made to large source code repositories by developers with varying experience and expertise levels. The ZeroIn project is aimed at analyzing the metadata of these dynamic phenomena, including the data on repositories, commits, and developers, to rapidly and accurately mark the quality of commits as they arrive at the repositories. In this context, the present article presents a characterization of the software development metadata in terms of distributions of data that best captures the trends in the d…
Background: Quality requirements (QRs) describe desired system qualities, playing an important role in the success of software projects. In the context of agile software development (ASD), where the main objective is the fast delivery of functionalities, QRs are often ill-defined and not well addressed during the development process. Software analytics tools help to control quality though the measurement of quality-related software aspects to support decision-makers in the process of QR management. Aim: The goal of this research is to explore the benefits of integrating a concrete software ana…
Low-code software development (LCSD) is an emerging approach to democratize application development for software practitioners from diverse backgrounds. LCSD platforms promote rapid application development with a drag-and-drop interface and minimal programming by hand. As it is a relatively new paradigm, it is vital to study developers' difficulties when adopting LCSD platforms. Software engineers frequently use the online developer forum Stack Overflow (SO) to seek assistance with technical issues. We observe a growing body of LCSD-related posts in SO. This paper presents an empirical study o…
The Matthew Effect of AI Programming Assistants: A Hidden Bias in Software Evolution
City University of Hong Kong (Dongguan)（香港城市大学（东莞））；The Hong Kong Polytechnic University（香港理工大学）；The University of Hong Kong（香港大学）；The Hong Kong University of Science and Technology（香港科技大学）
Agile development is conventional these days and with the passage of time software developers are rapidly moving from Waterfall to Agile development. Agile methods focus on delivering executable code quickly by increasing the responsiveness of software companies while decreasing development overhead and consider people as the strongest pillar of software development. As agile development overshadows Waterfall methodologies for software development, it comes up with some distinct challenges related to testing of such software. Our study is going to discuss the challenges this approach has stirr…
Crowdsourcing is becoming an accepted method of software development for different phases in the production lifecycle. Ideally, mass parallel production through Crowdsourcing could be an option for rapid acquisition in software engineering by leveraging infinite worker resource on the internet. It is important to understand the patterns and strategies of decomposing and uploading parallel tasks to maintain a stable worker supply as well as a satisfactory task completion rate. This research report is an empirical analysis of the available tasks' lifecycle patterns in crowdsourcing. Following th…
Scientific software projects evolve rapidly in their initial development phase, yet at the end of a funding period, the completion of a research project, thesis, or publication, further engagement in the project may slow down or cease completely. To retain the invested effort for the sciences, this software needs to be preserved or handed over to a succeeding developer or team, such as the next generation of (PhD) students. Comparable guides provide top-down recommendations for project leads. This paper intends to be a bottom-up approach for sustainable hand-over processes from a developer's p…
In the past decades, the revolutionary advances of Machine Learning (ML) have shown a rapid adoption of ML models into software systems of diverse types. Such Machine Learning Software Applications (MLSAs) are gaining importance in our daily lives. As such, the Quality Assurance (QA) of MLSAs is of paramount importance. Several research efforts are dedicated to determining the specific challenges we can face while adopting ML models into software systems. However, we are aware of no research that offered a holistic view of the distribution of those ML quality assurance challenges across the va…
