Large Software Development Companies Research Articles

Global Virtual Team Working during the Covid-19 Pandemic

Abstract Virtual work introduces distinct challenges when compared to face-to-face or on-site work. Communication and collaboration are key factors in team development and in team performance. When teamwork is of a global nature, imposed because of a pandemic, then additional variables are introduced into the equation. The challenges that global virtual teams (GVTs) encounter when communicating and developing in the context of the Covid-19 pandemic impacts how work is structured and teams develop. This qualitative study was conducted just over 1 year after the start of the Covid-19 pandemic when working from home became mandatory and particular challenges for GVTs became apparent. Data are gathered through an online anonymous survey and followed by semi-structured video-mediated interviews with staff in a large multinational software development company. Findings show that GVTs encounter a number of distinct challenges than face-to-face teams. However, individuals are actively adapting to the situation in which they find themselves and are learning to deal with the challenges by being proactive. Even though the tools used previously may not be entirely suitable for virtual work, GVTs learn to change how tools are used to be more productive and collaborative. Challenges continue to exist in areas, such as knowledge gathering and knowledge sharing. Communication failures can lead to delays and confusion. The findings also indicate that even though GVTs are not communicating as much informally or socially with their colleagues because of remote working in the pandemic, being remote is not having a negative effect on the ability to get work done. Some aspects of team development can be negatively affected when working in GVTs. Impacts are identified relating to trust and relationship building, as well as being able to identify and resolve conflict. These results prompt further research opportunities as organizations and individuals continue to adapt and embrace global virtual teamwork.

Software Development Practice as Baradian Entanglement

Software development practice is a messy, complicated, and constantly shifting human endeavor. Barad’s concept of “entanglement” helps to theorize complex sociotechnical systems. We are testing the application of this theory to understand and explain software development practices, as our work appears to be the only ethnographic research using Barad in any technology industry. Our continual aim is to understand large-scale, collaborative software development more deeply in practice and to discover appropriate theories that describe our observations and insights. Both authors are experienced software engineers and researchers. Through an ongoing longitudinal ethnographic study at a large Australian software development company, we explore, support, and improve the lived experience and practice of the software developers that work there. Ethnographic insights and an appreciation of the mutual constitution of situated phenomena have expanded over several years into an elaboration of entanglement as a more insightful explanation of software development practice. This research is having a significant impact on the participant developers and organization, including changes in measurement practices, mentoring, knowledge management, and innovation.

Software Quality and Its Entanglements in Practice

Effective software quality assurance in large‐scale, complex software systems is one of the most vexed issues in software engineering, and, it is becoming ever more challenging. Software quality and its assurance is part of software development practice, a messy, complicated and constantly shifting human endeavor.What emerged from our immersive study in a large Australian software development company is that software quality in practice is inextricably entangled with the phenomena of productivity, time, infrastructure and human practice. This ethnographic insight — made visible to the organization and its developers via the rich picture and the concept of entanglements— built their trust in our work and expertise. This led to us being invited to work with the software development teams on areas for change and improvement and moving to a participatory and leading role in organizational change.

Recognizing lines of code violating company-specific coding guidelines using machine learning

Software developers in big and medium-size companies are working with millions of lines of code in their codebases. Assuring the quality of this code has shifted from simple defect management to proactive assurance of internal code quality. Although static code analysis and code reviews have been at the forefront of research and practice in this area, code reviews are still an effort-intensive and interpretation-prone activity. The aim of this research is to support code reviews by automatically recognizing company-specific code guidelines violations in large-scale, industrial source code. In our action research project, we constructed a machine-learning-based tool for code analysis where software developers and architects in big and medium-sized companies can use a few examples of source code lines violating code/design guidelines (up to 700 lines of code) to train decision-tree classifiers to find similar violations in their codebases (up to 3 million lines of code). Our action research project consisted of (i) understanding the challenges of two large software development companies, (ii) applying the machine-learning-based tool to detect violations of Sun’s and Google’s coding conventions in the code of three large open source projects implemented in Java, (iii) evaluating the tool on evolving industrial codebase, and (iv) finding the best learning strategies to reduce the cost of training the classifiers. We were able to achieve the average accuracy of over 99% and the average F-score of 0.80 for open source projects when using ca. 40K lines for training the tool. We obtained a similar average F-score of 0.78 for the industrial code but this time using only up to 700 lines of code as a training dataset. Finally, we observed the tool performed visibly better for the rules requiring to understand a single line of code or the context of a few lines (often allowing to reach the F-score of 0.90 or higher). Based on these results, we could observe that this approach can provide modern software development companies with the ability to use examples to teach an algorithm to recognize violations of code/design guidelines and thus increase the number of reviews conducted before the product release. This, in turn, leads to the increased quality of the final software.

Task assignment to distributed teams aided by a hybrid methodology of verbal decision analysis

An increasingly common practice in large software development companies is to distribute tasks among geographically dispersed teams. This practice can bring many benefits, such as gains in terms of time and cost, but many are the challenges. One of the major challenges regards the method of assigning tasks to remote teams. This method involves knowing, classifying and ordering the factors that drive the assignment of tasks in a distributed scenario. This is a typical scenario for decision-making based on multiple criteria. Verbal decision analysis (VDA) is a multi-criteria framework to decision-making. This study presents a hybrid methodology structured on methods of VDA for classification ORdinal CLASSification (ORCLASS) and ordering (ZAPROS III-i) of factors that drive task assignment to distributed teams in software development projects. Tasks were grouped according to their type, i.e. requirements, architecture, implementation, and testing.

Introduction to the Special Issue on “International Conference on Software Reuse 2015”

Conducting requirements reviews before the start of software design is one of the central goals in requirements management. Fast and accurate reviews promise to facilitate software development process and mitigate technical risks of late design modifications. In large software development companies, however, it is difficult to conduct reviews as fast as needed, because the number of regularly incoming requirements is typically several thousand. Manually reviewing thousands of requirements is a time-consuming task and disrupts the process of continuous software development. As a consequence, software engineers review requirements in parallel with designing the software, thus partially accepting the technical risks. In this paper we present a measurement-based method for automating requirements reviews in large software development companies. The method, Rendex, is developed in an action research project in a large software development organization and evaluated in four large companies. The evaluation shows that the assessment results of Rendex have 73%-80% agreement with the manual assessment results of software engineers. Succeeding the evaluation, Rendex was integrated with the requirements management environment in two of the collaborating companies and is regularly used for proactive reviews of requirements.

Industrial experiences from evolving measurement systems into self‐healing systems for improved availability

SummaryAutomated measurement programs are an efficient way of collecting, processing, and visualizing measures in large software development companies. The number of measurements in these programs is usually large, which is caused by a diversity of the needs of the stakeholders. In this paper, we present the application of the self‐healing concepts to assure the availability of measurements to the stakeholders without the need for effort‐intensive and costly manual interventions of the operators. We study the measurement infrastructure at one of the development units of a large infrastructure provider. In this paper, we present how the Monitor, Analyze, Plane, and Execute with Knowledge model was instantiated in a simplistic manner to reduce the need for manual intervention in the operation of the measurement systems. Based on the experiences from the 2 cases studied in this paper, we show how an evolution toward self‐healing measurement systems is done both with a dedicated failure taxonomy and with an effective straightforward handling of the most common errors in the execution. The mechanisms studied and presented in this paper show that self‐healing provides significant improvements to the operation of the measurement program and reduces the need for daily oversight by an operator for the measurement systems.

Rendex: A method for automated reviews of textual requirements

Abstract Conducting requirements reviews before the start of software design is one of the central goals in requirements management. Fast and accurate reviews promise to facilitate software development process and mitigate technical risks of late design modifications. In large software development companies, however, it is difficult to conduct reviews as fast as needed, because the number of regularly incoming requirements is typically several thousand. Manually reviewing thousands of requirements is a time-consuming task and disrupts the process of continuous software development. As a consequence, software engineers review requirements in parallel with designing the software, thus partially accepting the technical risks. In this paper we present a measurement-based method for automating requirements reviews in large software development companies. The method, Rendex, is developed in an action research project in a large software development organization and evaluated in four large companies. The evaluation shows that the assessment results of Rendex have 73%-80% agreement with the manual assessment results of software engineers. Succeeding the evaluation, Rendex was integrated with the requirements management environment in two of the collaborating companies and is regularly used for proactive reviews of requirements.

Program management approach for large-scale information technology development projects: a case study

This case study presents the program management approach in managing large-scale information technology projects. Using the case of ACME Solutions Ltd., a large software development company, the authors first emphasize on the need to use program management over project management when managing related multiple information technology projects. Then, they explain the program lifecycle in this company and discuss the ‘process’ and ‘people’ related challenges across the program stages. Broadly, they observe that there is a lack of coordination between the stakeholders and processes of the program. Recommendations to overcome these limitations are discussed.

The Utilization of Information Systems Development Methodologies in Practice

The objective of our research is to study people and their actions within an organizational context, namely whether and how system developers use Information Systems Development methodologies in practice. This article adds to the ongoing discussion about the practical use of ISD methodologies. Many prescriptive and normative textbooks as well as anecdotes exist, but there is little empirical documentation about the actual use of development methods. To contribute to the scientific documentation of methodology utilization, we provide here an empirically based study of the practical use of development methods in three projects within a large Danish software development company. Founded on a Grounded Theory analysis we identified five main categories of themes, which are related and have an effect on the use of ISD methodologies. These include 1) the extent to which a specific methodology is universally applicable, 2) the need for confidence of and between the parties involved, 3) the degree of the developer’s experience, 4) the developer’s wish for co-determination in the development process, and 5) the nature of the introduction process for a method. Our results confirm existing research in the field and offer new insights, especially with regard to the interplay and relationship of the different, identified themes.