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The Information Systems (IS) and Software Engineering (SE) fields share a remarkable number of similarities in their historical evolution to date. These similarities are briefly outlined below. An analysis of 10 years (2001-2010) of…
A well-rounded software engineer is often defined by technical prowess and the ability to deliver on complex projects. However, the narrative around the ideal Software Engineering (SE) candidate is evolving, suggesting that there is more to…
Students of software engineering struggle to develop a systems perspective because most of the software engineering methodologies focus on developing a particular aspect of a system. Lack of unified coverage to the topic of systems…
Software Engineering as an industry is highly diverse in terms of development methods and practices. Practitioners employ a myriad of methods and tend to further tailor them by e.g. omitting some practices or rules. This diversity in…
The primary theory of software engineering is that an organization's Policies and Processes influence the quality of its Products. We call this the PPP Theory. Although empirical software engineering research has grown common, it is unclear…
Recent years have seen the successful application of deep learning to software engineering (SE). In particular, the development and use of pre-trained models of source code has enabled state-of-the-art results to be achieved on a wide…
Context: Advancements in machine learning (ML) lead to a shift from the traditional view of software development, where algorithms are hard-coded by humans, to ML systems materialized through learning from data. Therefore, we need to…
In software engineering, the concept of a ``feature'' is widely used but inconsistently defined across disciplines such as requirements engineering (RE) and software product lines (SPL). This lack of consistency often results in…
This article attempts to describe specific mental techniques that are related to resolving very complex tasks in software engineering. This subject may be familiar to some software specialists to different extents; however, there is…
The main problems of Software Engineering appear as a result of incompatibilities. For example, the quality of organization of the production process depends on correspondence with existent resources and on a common understanding of project…
Machine-learning (ML) techniques have become popular in the recent years. ML techniques rely on mathematics and on software engineering. Researchers and practitioners studying best practices for designing ML application systems and software…
Requirements Engineering (RE) has established itself as a software engineering discipline during the past decades. While researchers have been investigating the RE discipline with a plethora of empirical studies, attempts to systematically…
Large Language Models (LLMs) are rapidly becoming ubiquitous both as stand-alone tools and as components of current and future software systems. To enable usage of LLMs in the high-stake or safety-critical systems of 2030, they need to…
The SEMAT kernel is a thoroughly thought generic framework for Software Engineering system development in practice. But one should be able to test its characteristics by means of a no less generic theory matching the SEMAT kernel. This…
While mastered by some, good scientific writing practices within Empirical Software Engineering (ESE) research appear to be seldom discussed and documented. Despite this, these practices are implicit or even explicit evaluation criteria of…
Background: The state of the art in software engineering consists of a myriad of contributions and the gaps between them; it is difficult to characterize. Questions: In order to help understanding the state of the art, can we identify gaps…
Empirical Software Engineering has received much attention in recent years and became a de-facto standard for scientific practice in Software Engineering. However, while extensive guidelines are nowadays available for designing, conducting,…
Motivations and challenges jointly shape how individuals enter, persist, and evolve within software engineering (SE), yet their interplay remains underexplored across the transition from education to professional practice. We conducted 15…
Linear Software Models is a systematic effort to formulate a theory of software systems neatly based upon standard mathematics, viz. linear algebra. It has appeared in a series of papers dealing with various aspects of the theory. But one…
Models are fundamentally crucial to many scientific fields, including software engineering, systems engineering, enterprise modeling, and business modeling. This paper focuses on diagrammatic conceptual modeling, as opposed to mathematical…