There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Thematic analysis is an approach that is often used for identifying, analyzing, and reporting patterns (themes) within data in primary qualitative research. 'Thematic synthesis' draws on the principles of thematic analysis and identifies the recurring themes or issues from multiple studies, interprets and explains these themes, and draws conclusions in systematic reviews. This paper conceptualizes the thematic synthesis approach in software engineering as a scientific inquiry involving five steps that parallel those of primary research. The process and outcome associated with each step are described and illustrated with examples from systematic reviews in software engineering.

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Recommended Steps for Thematic Synthesis in Software Engineering

Statistical Inference from Capture Data on Closed Animal Populations

Software engineering: theory and practice

ContextComparing and contrasting evidence from multiple studies is necessary to build knowledge and reach conclusions about the empirical support for a phenomenon. Therefore, research synthesis is at the center of the scientific enterprise in the software engineering discipline. ObjectiveThe objective of this article is to contribute to a better understanding of the challenges in synthesizing software engineering research and their implications for the progress of research and practice. MethodA tertiary study of journal articles and full proceedings papers from the inception of evidence-based software engineering was performed to assess the types and methods of research synthesis in systematic reviews in software engineering. ResultsAs many as half of the 49 reviews included in the study did not contain any synthesis. Of the studies that did contain synthesis, two thirds performed a narrative or a thematic synthesis. Only a few studies adequately demonstrated a robust, academic approach to research synthesis. ConclusionWe concluded that, despite the focus on systematic reviews, there is limited attention paid to research synthesis in software engineering. This trend needs to change and a repertoire of synthesis methods needs to be an integral part of systematic reviews to increase their significance and utility for research and practice.

/pdf/research-synthesis-in-software-engineering-40heqp30v5.pdf

Research synthesis in software engineering

Most software quality research has focused on identifying faults (i.e., information is incorrectly recorded in an artifact). Because software still exhibits incorrect behavior, a different approach is needed. This paper presents a systematic literature review to develop taxonomy of errors (i.e., the sources of faults) that may occur during the requirements phase of software lifecycle. This taxonomy is designed to aid developers during the requirement inspection process and to improve overall software quality. The review identified 149 papers from the software engineering, psychology and human cognition literature that provide information about the sources of requirements faults. A major result of this paper is a categorization of the sources of faults into a formal taxonomy that provides a starting point for future research into error-based approaches to improving software quality.

/pdf/a-systematic-literature-review-to-identify-and-classify-2jnc13hk01.pdf

A systematic literature review to identify and classify software requirement errors

Although computer science, information systems, and information technology educators often do an exemplary job of preparing their students for jobs in industry or for further education, there are still many areas where these students do not possess the necessary skills or knowledge based on the expectations of employers or academia. These gaps between the abilities of graduating students and those expected to have can prevent them from succeeding in their careers. This paper presents the results of a systematic literature review conducted to determine which areas graduating students most frequently fall short of the expectations of industry or macademia. The results of this review indicate that graduating students are lacking in many different areas, including technical abilities (design, testing, configuration management tools, etc.) personal skills (communication, teamwork, etc.) and professional qualities (e.g. ethics). By raising awareness of these areas, it is possible for educators to become aware of areas where students most frequently fail to meet expectations and to make curriculum changes or adjustments to address these problems

Gaps between industry expectations and the abilities of graduates

Graduating computer science and software engineering students do not always possess the necessary skills, abilities, or knowledge when beginning their careers in the software industry. The lack of these skills and abilities can limit the productivity of newly hired, recent graduates, or even prevent them from gaining employment. This paper presents the results of an empirical study where twenty-three managers and hiring personnel from various software companies in the United States and Europe were interviewed. Participants were asked about areas where recent graduates frequently struggled when beginning employment at their companies and which skill deficiencies might prevent a recent graduate from being hired. The results of this study indicate that recent graduates struggle with using configuration management systems (and other software tools), effectively communicating with co-workers and customers, producing unit tests for their code, and other skills or abilities. The results also indicate that a lack of project experience and problem solving abilities are the most commonly cited issues preventing students from gaining employment. This research is intended to assist educators in identifying areas where students may not measure up the expectations of industry companies and in improving the curriculum at their universities to better prepare them for their future careers.

Investigating the skill gap between graduating students and industry expectations

Background Human-centric software engineering activities, such as requirements engineering, are prone to error. These human errors manifest as faults. To improve software quality, developers need methods to prevent and detect faults and their sources. Aims Human error research from the field of cognitive psychology focuses on understanding and categorizing the fallibilities of human cognition. In this paper, we applied concepts from human error research to the problem of software quality. Method We performed a systematic literature review of the software engineering and psychology literature to identify and classify human errors that occur during requirements engineering. Results We developed the Human Error Taxonomy (HET) by adding detailed error classes to Reason's well-known human error taxonomy of Slips, Lapses, and Mistakes. Conclusion The process of identifying and classifying human error identification provides a structured way to understand and prevent the human errors (and resulting faults) that occur during human-centric software engineering activities like requirements engineering. Software engineering can benefit from closer collaboration with cognitive psychology researchers.

Development of a human error taxonomy for software requirements: A systematic literature review

Achieving high software quality is a primary concern for software development organizations. Researchers have developed many quality improvement methods that help developers detect faults early in the lifecycle. To address some of the limitations of fault-based quality improvement approaches, this paper describes an approach based on errors (i.e. the sources of the faults). This research extends Lanubile et al.'s, error abstraction process by providing a formal requirement error taxonomy to help developers identify both faults and errors. The taxonomy was derived from the software engineering and psychology literature. The error abstraction and classification process and the requirement error taxonomy are validated using a family of four empirical studies. The main conclusions derived from the four studies are: (1) the error abstraction and classification process is an effective approach for identifying faults; (2) the requirement error taxonomy is useful addition to the error abstraction process; and (3) deriving requirement errors from cognitive psychology research is useful.

Gursimran S. Walia

Papers

A systematic literature review to identify and classify software requirement errors

Gaps between industry expectations and the abilities of graduates

Investigating the skill gap between graduating students and industry expectations

Development of a human error taxonomy for software requirements: A systematic literature review

Using error abstraction and classification to improve requirement quality: conclusions from a family of four empirical studies