相关论文: Experience vs Data: A Case for More Data-informed …
There is a diversity of models explaining organizational culture and how these complex aspects can be addressed in connection to organizational change efforts. This workshop paper claims that models already exist for dealing with the…
Considering the market's competitiveness and the complexity of organizations and projects, analyzing data is crucial to decision support on software development and project management processes. These practices are essential to increase…
The Covid-19 pandemic established hybrid work as the new norm in software development companies. In large-scale agile, meetings of different types are pivotal for collaboration, and decisions need to be taken on how they are organized and…
Architecture decision making is considered one of the most challenging cognitive tasks in software development. The objective of this study is to explore the state of the practice of architecture decision making in software teams, including…
The dramatic increase of observational data across industries provides unparalleled opportunities for data-driven decision making and management, including the manufacturing industry. In the context of production, data-driven approaches can…
Decision support tools enable improved decision-making for challenging decision problems by empowering stakeholders to process, analyze, visualize, and otherwise make sense of a variety of key factors. Their intentional design is a critical…
Software development of modern, data-driven applications still relies on tools that use interaction paradigms that have remained mostly unchanged for decades. While rich forms of interactions exist as an alternative to textual command…
Software design is gradually becoming open, distributed, pervasive, and connected. It is a sad statistical fact that software projects are scientifically fragile and tend to fail more than other engineering fields. Agile development is a…
This paper presents an empirical study on how self- organized software teams could attain high performance using agile and lean practices. In particular, the paper qualitatively examines characteristics of high performance and self-…
Release management is one of the most important software processes and is a set of processes that includes the compilation, configuration, and management of software versions in different environments. In recent years, changes in processes,…
The number of machine learning, artificial intelligence or data science related software engineering projects using Agile methodology is increasing. However, there are very few studies on how such projects work in practice. In this paper,…
Randomized Controlled Trials (RCTs) represent the gold standard for causal inference yet remain a scarce resource. While large-scale observational data is often available, it is utilized only for retrospective fusion, and remains discarded…
Evaluation of potential AGI systems and methods is difficult due to the breadth of the engineering goal. We have no methods for perfect evaluation of the end state, and instead measure performance on small tests designed to provide…
Event data provide the main source of information for analyzing and improving processes in organizations. Process mining techniques capture the state of running processes w.r.t. various aspects, such as activity-flow and performance…
There has been some evidence that agility is connected to the group maturity of software development teams. This study aims at conducting group development psychology training with student teams, participating in a project course at…
Expert judgment for software effort estimation is oriented toward direct evidences that refer to actual effort of similar projects or activities through experts' experiences. However, the availability of direct evidences implies the…
Software development effort estimation is one of the most critical aspect in software development process, as the success or failure of the entire project depends on the accuracy of estimations. Researchers are still conducting studies on…
The ability to make decisions based on data, with its inherent uncertainties and variability, is a complex and vital skill in the modern world. The need for such quantitative critical thinking occurs in many different contexts, and while it…
The rapid growth in terms of the availability of transportation data provides great potential for the introduction of emerging data-driven methodologies into transportation-related research and development efforts. However, advanced…
Agile methods have gotten a good reputation for managing projects in many different sectors. A challenge among practitioners in the ERP (Enterprise Resource Planning) domain, is to decide if an agile method is suitable or not for new…