jehanweerasuriya/uni-ai-dataset huggingface dataset:
Contextual Injection of Quality Measures into Software Engineering Processes
Authors: Gregor Grambow, Roy Oberhauser, Manfred Reichert
Published in: OPUS (Aalen University) (2011-01-01)

Despite improvements in software engineering processes and tools, concrete preventative and analytical software quality assurance activities are still typically manually triggered and determined, resulting in missed or untimely quality opportunities and increased project overhead.Quality goals, when defined, lack holistic environmental support for automated performance measurement and governance that is tightly integrated in the low-level operational software engineering processes.This results in higher quality risks and cost risks.Based on adaptive process management, an approach is presented that injects situationally-determined quality measure proposals into the concrete workflows of software engineers, using contextual semantic knowledge and multi-agent quality goal tracking and decision-making.Our evaluation shows the feasibility of the approach for automatically providing timely quality measure guidance to software engineers without disrupting their current activities.This supports process governance while reducing quality risks and costs during software development projects.
Metode SLR untuk Mengidentifikasi Isu-Isu dalam Software Engineering
Authors: Lusiana Lusiana, Melva Suryani
Published in: SATIN - Sains dan Teknologi Informasi (2018-07-31)

Software Engineering (SE) merupakan disiplin ilmu yang berkaitan dengan semua aspek produksi software yang dimulai dari tahap awal spesifikasi sampai pada pemeliharaan sistem yang digunakan [1], oleh sebab itu SE memiliki peran penting terhadap perkembangan dunia teknologi informasi. Penelitian ini mengkaji isu dan pedekatan yang digunakan dalam SE empat tahun terakhir (2010-2013) yang belum teridentifikasi dengan baik, dengan menggunakan metode SLR. SLR merupakan cara untuk mengidentifikasi, mengevaluasi dan menafsirkan semua penelitian yang tersedia dengan pertanyaan penelitian tertentu, bidang topik, atau fenomena yang menarik [2] (Kitchenham 2007). Dengan metode SLR isu-isu yang berhubungan dalam software engineering akan diidentifikasi dengan menggunakan kata kunci â€œwhat the problemâ€ (apa masalah) dan â€œhow to solve the problemâ€ (bagaimana memecahkan masalah tersebut). Hasil penelitian dapat dijadikan panduan oleh mahasiswa dan pembaca lainnya untuk melakukan penelitian yang berhubungan dengan SE selain itu, penelitian ini juga dapat membantu pembaca untuk mencari topik yang dominan penelitian dalam bidang SE
Experimental design and analysis in software engineering
Authors: Shari Lawrence Pfleeger
Published in: ACM SIGSOFT Software Engineering Notes (1995-01-01)

article Free Access Share on Experimental design and analysis in software engineering: Part 2: how to set up and experiment Author: Shari Lawrence Pfleeger Centre for Software Reliability, City University, Northampton Square, London ECIV 0HB England Centre for Software Reliability, City University, Northampton Square, London ECIV 0HB EnglandView Profile Authors Info & Claims ACM SIGSOFT Software Engineering NotesVolume 20Issue 1Jan. 1995 pp 22–26https://doi.org/10.1145/225907.225910Published:01 January 1995Publication History 21citation955DownloadsMetricsTotal Citations21Total Downloads955Last 12 Months37Last 6 weeks2 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my Alerts New Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF
Analysis of Software Engineering Skills Gap in the Industry
Authors: Deniz Akdur
Published in: ACM Transactions on Computing Education (2022-10-12)

Many practitioners might struggle with becoming productive in different software engineering (SE) roles due to misalignment of the skills learnt during the university time with what is expected in the industry. Companies spend significant resources to train the personnel, whose academic backgrounds are not only based on “computing disciplines”. Hiring properly trained practitioners allows employers to spend less time while incorporating them more efficiently into the workforce; for employees, knowing the most important skillset is helpful to increase their chance of employability. On the other hand, for academia, understanding the necessary skillset is critical to make curriculum updates. To achieve these objectives, we conducted a survey, which was responded to by 628 software practitioners, who completed their undergraduate degree in Turkey, working in 13 countries. This paper sheds light on the most important (hard and soft) skills in the industry by presenting various cross-factor analyses as well as their coverage in the academic curriculum (mostly in Turkish universities). The results showed that the most important skills are related to various factors such as profiles of the practitioners (e.g., SE role(s), work experience) and the characteristics of the product developed by the practitioner. The findings revealed that both academia and industry should invest in skills improvement: academia can make necessary educational updates according to industrial needs; whereas industry can provide practical experiences to students. By creating the awareness of the expected skillset, both practitioners and academics will benefit from the results, which help close the gaps that can and should be achieved through more Industry Academia Collaborations (IACs) .
Machine Learning for Software Engineering: A Tertiary Study
Authors: Zoe Kotti, Rafaila Galanopoulou, Diomidis Spinellis
Published in: ACM Computing Surveys (2022-11-30)

Machine learning (ML) techniques increase the effectiveness of software engineering (SE) lifecycle activities. We systematically collected, quality-assessed, summarized, and categorized 83 reviews in ML for SE published between 2009 and 2022, covering 6,117 primary studies. The SE areas most tackled with ML are software quality and testing, while human-centered areas appear more challenging for ML. We propose a number of ML for SE research challenges and actions, including conducting further empirical validation and industrial studies on ML, reconsidering deficient SE methods, documenting and automating data collection and pipeline processes, reexamining how industrial practitioners distribute their proprietary data, and implementing incremental ML approaches.
Generative Artificial Intelligence for Software Engineering—A Research Agenda
Authors: Anh Nguyen‐Duc, Beatriz Cabrero‐Daniel, Adam Przybyłek, Chetan Arora, Dron Khanna, Tomas Herda, Usman Rafiq, Jorge Melegati, Eduardo Guerra, Kai‐Kristian Kemell, Mika Saari, Zheying Zhang, Huy Quoc Le, Tho Quan, Pekka Abrahamsson
Published in: Software Practice and Experience (2025-07-29)

ABSTRACT Context Generative artificial intelligence (GenAI) tools have become increasingly prevalent in software development, offering assistance to various managerial and technical project activities. Notable examples of these tools include OpenAI's ChatGPT, GitHub Copilot, and Amazon CodeWhisperer. Objective Although many recent publications have explored and evaluated the application of GenAI, a comprehensive understanding of the current development, applications, limitations, and open challenges remains unclear to many. Particularly, we do not have an overall picture of the current state of GenAI technology in practical software engineering usage scenarios. Method We conducted a literature review and focus groups for a duration of five months to develop a research agenda on GenAI for software engineering. Results We identified 78 open research questions (RQs) in 11 areas of software engineering. Our results show that it is possible to explore the adoption of GenAI in partial automation and support decision‐making in all software development activities. While the current literature is skewed toward software implementation, quality assurance and software maintenance, other areas, such as requirements engineering, software design, and software engineering education, would need further research attention. Common considerations when implementing GenAI include industry‐level assessment, dependability and accuracy, data accessibility, transparency, and sustainability aspects associated with the technology. Conclusions GenAI is bringing significant changes to the field of software engineering. Nevertheless, the state of research on the topic still remains immature. We believe that this research agenda holds significance and practical value for informing both researchers and practitioners about current applications and guiding future research.
Characterizing industry-academia collaborations in software engineering: evidence from 101 projects
Authors: Vahid Garousi, Dietmar Pfahl, João M. Fernandes, Michael Felderer, Mika Mäntylä, David Shepherd, Andrea Arcuri, Ahmet Coşkunçay, Bedir Teki̇nerdoğan
Published in: Empirical Software Engineering (2019-04-23)

Research collaboration between industry and academia supports improvement and innovation in industry and helps ensure the industrial relevance of academic research. However, many researchers and practitioners in the community believe that the level of joint industry-academia collaboration (IAC) projects in Software Engineering (SE) research is relatively low, creating a barrier between research and practice. The goal of the empirical study reported in this paper is to explore and characterize the state of IAC with respect to industrial needs, developed solutions, impacts of the projects and also a set of challenges, patterns and anti-patterns identified by a recent Systematic Literature Review (SLR) study. To address the above goal, we conducted an opinion survey among researchers and practitioners with respect to their experience in IAC. Our dataset includes 101 data points from IAC projects conducted in 21 different countries. Our findings include: (1) the most popular topics of the IAC projects, in the dataset, are: software testing, quality, process, and project managements; (2) over 90% of IAC projects result in at least one publication; (3) almost 50% of IACs are initiated by industry, busting the myth that industry tends to avoid IACs; and (4) 61% of the IAC projects report having a positive impact on their industrial context, while 31% report no noticeable impacts or were “not sure”. To improve this situation, we present evidence-based recommendations to increase the success of IAC projects, such as the importance of testing pilot solutions before using them in industry. This study aims to contribute to the body of evidence in the area of IAC, and benefit researchers and practitioners. Using the data and evidence presented in this paper, they can conduct more successful IAC projects in SE by being aware of the challenges and how to overcome them, by applying best practices (patterns), and by preventing anti-patterns.
Object-oriented software engineering
Authors: Debora Weber-Wulff
Published in: ACM SIGSOFT Software Engineering Notes (2000-05-01)

No abstract available.
Resilience Engineering: Concepts and Precepts
Authors: R L Wears
Published in: BMJ Quality & Safety (2006-12-01)

For Resilience Engineering, 'failure' is the result of the adaptations necessary to cope with the complexity of the real world, rather than a breakdown or malfunction. The performance of individuals and organizations must continually adjust to current conditions and, because resources and time are finite, such adjustments are always approximate. This definitive new book explores this groundbreaking new development in safety and risk management, where 'success' is based on the ability of organizations, groups and individuals to anticipate the changing shape of risk before failures and harm occur. Featuring contributions from many of the worlds leading figures in the fields of human factors and safety, Resilience Engineering: Concepts and Precepts provides thought-provoking insights into system safety as an aggregate of its various components, subsystems, software, organizations, human behaviours, and the way in which they interact. The book provides an introduction to Resilience Engineering of systems, covering both the theoretical and practical aspects. It is written for those responsible for system safety on managerial or operational levels alike, including safety managers and engineers (line and maintenance), security experts, risk and safety consultants, human factors professionals and accident investigators.
The profession of ITIs software engineering engineering?
Authors: Peter J. Denning, Richard Riehle
Published in: Communications of the ACM (2009-02-25)

Software engineering continues to be dogged by claims it is not engineering. Adopting more of a computer-systems view may help.
Extracting Knowledge From On-Line Sources for Software Engineering Labor Market: A Mapping Study
Authors: Μαρία Παπουτσόγλου, Apostolos Ampatzoglou, Nikolaos Mittas, Lefteris Angelis
Published in: IEEE Access (2019-01-01)

Software engineering is a continuously evolving sector and the demands of the related labor market result in a wide variety of job openings, ranging from developers to customer service positions. Thus, there is a need to continuously monitor labor market trends using data and analytics. Both employers and employees can benefit by capturing emerging trends which can facilitate continuous learning and training in new technologies, support of better matching between a job offer and the ideal candidate and expertise detection. To fulfill these needs, the results of labor market analytics need to reach the stakeholders timely and accurately. However, often delays occur, which stem from time-consuming approaches based on collecting data from traditional sources, such as questionnaires or interviews. Recently, researchers started leveraging content from digital sources, which are easily accessed and contain a wealth of information. This paper presents the results of a Systematic Mapping Study on digital sources that can be used to address the data analytics needs of the labor market. It provides a multifaceted categorization of the issues involved in the analysis of digital sources of the software engineering labor market. It aims to identify digital labor market sources for data retrieval which are appropriate for employers and employees analytics. Additionally, it aims to connect different skill types, needs and goals of labor market with the utilization of digital sources and data analysis methods. In total 86 primary studies were selected and each one was evaluated and classified aiming to identify the: (a) digital sources that are used for labor market analytics; (b) type of skills they examine; (c) methods which are used to utilize the raw digital content; (d) goals for which every primary study is conducted; (e) beneficiaries (stakeholder) of the results; and (f) time trends for all the above.
Sustainability competencies and skills in software engineering: An industry perspective
Authors: Rogardt Heldal, Ngoc Thanh Nguyên, Ana Moreira, Patricia Lago, Letícia Duboc, Stefanie Betz, Vlad C. Coroamă, Birgit Penzenstadler, Jari Porras, Rafael Capilla, Ian Brooks, Shola Oyedeji, Colin C. Venters
Published in: Journal of Systems and Software (2024-02-02)

Achieving the UN Sustainable Development Goals (SDGs) demands a shift by industry, governments, society, and individuals to reach adequate levels of awareness and actions to address sustainability challenges. Software systems will play an important role in moving towards these targets. Sustainability skills are necessary to support the development of software systems and to provide sustainable IT-supported services for citizens. While there is a growing number of academic bodies including sustainability education in engineering and computer science curricula, there is not yet comprehensive research on the competencies and skills required by IT professionals to develop such systems. This study aims to identify the industrial sustainability needs for education and training from software engineers’ perspective. For this, we answer the following questions: (1) what are the interests of organisations with an IT division with respect to sustainability? (2) what do organisations want to achieve with respect to sustainability, and how? and (3) what are the sustainability-related competencies and skills that organisations need to achieve their sustainability goals? We conducted a qualitative study with interviews and focus groups with experts from twenty-eight organisations with an IT division from nine countries to understand their interests, goals, and achievements related to sustainability, and the skills and competencies needed to achieve their goals. Our findings show that organisations are interested in sustainability, both idealistically and increasingly for core business reasons. They seek to improve the sustainability of software processes and products but encounter difficulties, like the trade-off between short-term financial profitability and long-term sustainability goals or an unclear understanding of sustainability concepts from a software engineering perspective. To fill these gaps, they have promoted in-house training courses, collaborated with universities, and sent employees to external training. The acquired competencies should support translating environmental and social benefits into economic ones and make sustainability an integral part of software development.
Software engineering ontology : a development methodology
Authors: Olavo Mendes, Alain Abran
Published in:  (2004-01-01)

According to Gruber’s definition an ontology [1] is “a formal specification of a conceptualization”. A conceptualisation being a simplified, abstract way of perceiving a segment of the world (a piece of reality), for which we agree to recognize the existence of a set of objects and their interrelations, as well as the terms we use to refer to them and their agreed meanings and properties.
The management of software engineering, Part I: Principles of software engineering
Authors: Harlan D. Mills
Published in: IBM Systems Journal (1999-01-01)

In the past 20 years, the Federal Systems Division of the IBM Corporation has been involved with some of the nation's most complex and demanding software developments. These include the ground support software for the NASA Manned Space Series of the Mercury, Gemini, Apollo, and Skylab Programs (reaching the moon with Apollo), and both the ground and space software for the NASA Space Shuttle Program. FSD has also developed software for the Safeguard Anti-Ballistic Missile System, for the Enroute Traffic Control System for the FAA, and many other major civil and defense systems.
Opportunistic Problem Solving in Software Engineering
Authors: P.N. Robillard
Published in: IEEE Software (2005-11-01)

Software development is a complex, mainly cognitive endeavor. Studying these cognitions can improve software processes, but this is an ambitious task. The topic is broad, and the software engineering domain is still maturing. Positioning software engineering activities within a holistic view of the software process helps us compare it with other engineering disciplines. In this way, we can better define what is specific to software engineering and how to quantitatively and qualitatively measure these activities.
Software Engineering for Science
Authors: Jeffrey C. Carver
Published in: Computing in Science & Engineering (2016-03-01)

AEIC Jeffrey C. Carver describes ways to improve software engineering for science, introduces the Software Engineering Track for CiSE magazine, and provides a link to a survey that can inform future progress.
The Enriched UTAUT Model for the Acceptance of Software Engineering Tools in Academic Education
Authors: Stanisław Wrycza, Bartosz Marcinkowski, Damian Gajda
Published in: Information Systems Management (2016-10-31)

This article provides an enriched technology acceptance model explaining the impact of both classic and additional variables on software engineering tools acceptance within Information Systems Development courses. Two novel, domain-specific variables were identified (i.e., Professional Training Diffusion and Model Interchange). Statistical verification of the proposed model and study regarding the influence of the variables on students’ intention to use specific tools were conducted—providing users with enhanced means of selecting optimal software for real-life projects.
A Handbook of Software and Systems Engineering: Empirical Observations, Laws and Theories
Authors: Albert Endres, H. Dieter Rombach
Published in:  (2003-05-12)

This book guides students toward the best practice to use when implementing software engineering techniques. It identifies and discusses the rules and laws of developing software. Largely independent of technologies, these rules and laws form the basis for principles underlying software and systems engineering. The book is structured around the software development life cycle, which begins with requirements definition and continues by covering maintenance and withdrawal. This is the first book in the Fraunhofer IESE series in Software Engineering.
Prototyping a project master database for software engineering environments
Authors: Maria H. Penedo
Published in: ACM SIGPLAN Notices (1987-01-01)

Software Engineering Environments (SEE) have been determined as good means of increasing software productivity by shifting projects from the paper world into the automated world. An environment database has been identified as the core of any automated Software Engineering Environment. It should provide the means for accessing, storing and relating all the project's products, the means for automating the process by which these components are entered in this library, modified, controlled and disseminated, and the means for supporting “active databases 1 ”. The inherent complexity of building such a database is widely recognized. We have been studying issues associated with such an environment database, which we denote Project Master Data Base (PMDB), with the overall objective of defining, designing and developing a PMDB as an integrated part of a SEE. Due to the lack of explicit requirements for its design, a prototype of the PMDB was developed in order to gain information and experience on both the specifications of the PMDB itself and also on different implementation approaches. This paper discusses our prototyping exercise; it describes the prototype, how the problem reporting, evaluation, and tracking process was modeled, and some of the lessons learned as a result of this effort.
Scaling up: a research agenda for software engineering
Authors: CORPORATE Computer Science and Technology Board
Published in: Communications of the ACM (1990-03-01)

The following excerpts have been gleaned from a report by the Computer Science and Technology Board that summarizes the deliberations of a group of software engineers participating in a CSTB workshop that focused on setting research priorities.
Splitting the difference: the historical necessity of synthesis in software engineering
Authors: Stuart S. Shapiro
Published in: IEEE Annals of the History of Computing (1997-01-01)

For the last quarter of a century, software technologists have worked to address the "software crisis" identified in the 1960s. Their efforts have focused on a number of different areas, but have often been marked by the search for singular "best" solutions. However, the fundamental nature of software-involving basic and poorly understood problem solving processes combined with unprecedented and multifaceted complexity-weighs heavily against the utility of singular approaches. Examination of the discourse of software technologists in a number of key professional and trade journals over the last 25 years illuminates various disputes central to the development of software engineering and highlights the necessity of a more pluralistic mind set revolving around synthesis and trade-offs.