Engaging the net generation with evidence-based software engineering through a community-driven web database

Software engineering faculty face the challenge of educating future researchers and industry practitioners regarding the generation of empirical software engineering studies and their use in evidence-based software engineering. In order to engage the Net generation with this topic, we propose development and population of a community-driven Web database containing summaries of empirical software engineering studies. We also present our experience with integrating these activities into a graduate software engineering course. These efforts resulted in the creation of “SEEDS: Software Engineering Evidence Database System”. Graduate students initially populated SEEDS with 216 summaries of empirical software engineering studies. The summaries were randomly sampled and reviewed by industry professionals who found the student-written summaries to be at least as useful as professional-written summaries. In fact, 30% more of the respondents found the student-written summaries to be “very useful”. Motivations, student and instructor-developed prototypes, and assessments of the resulting artifacts will be discussed.     

A NEW PARADIGM FOR IS

An Is paradigm shift will create problems of adjustment and new opportunities for IS professionals. To function effectively in this new world, current and future IS professionals must acquire new knowledge and skills. This will not be easy to accomplish and will require the joint effort of both industry and academia. However, the payoffs from such human investments will be enormous. The existence of a cadre of capable IS professionals who can intelligently and effectively apply emerging information technologies not only affects the success of individual organizations but improves the competitiveness of our nation.     

Split ends: labor shortage and the CS-IS divide

Will we still suffer a major drought of software professionals after our Y2K problems are solved? The author considers how a shortage of highly skilled software people will persist and will hinder the growth of the entire industry. He lays blame for this shortage on academics and the persistent division between CS and IS departments. Is academia alone to blame, or does industry also contribute to the shortage?     

TAP-D: A model for developing specialization tracks in a graduate software engineering curriculum

Software is pervasive: it exists in many different types of applications and involves a variety of computer technologies. Representative applications that exemplify this diversity include aircraft control, video conferencing, Internet commerce, and computer-based tutors. There is a corresponding increase in demand for technical professionals with advanced software engineering skills and with expertise in developing specific applications or in applying specific technologies. A graduate curriculum that enables the student to acquire application-specific or technology-specific knowledge and skills while studying software engineering can help to supply this demand. Some graduate programs include electives that the student can use to specialize in technology-specific areas. Few programs offer students a systematic way to integrate their software engineering education with their development of application-specific knowledge and skills. This article discusses the TAP-D model for incorporating specialization tracks into a software engineering curriculum. The author discusses how this model was applied to the development of the Real-Time Specialization Track in the Master of Software Engineering Program at Carnegie Mellon University.     

Forging a discipline: An outline history of software engineering education

Software engineering education has a 30-year history. It is a story of academics struggling to fulfill industry needs with almost no support from computer science curriculum designers. It is a story of industry finally winning over some of academia to teach software engineering rather than vanilla computer science. It is a story of a discipline still incomplete, but having made great strides in the last decade. This paper discusses the succeeding eras of software engineering education, from lone teachers to master's curricula to undergraduate degree programs. Even though the maturity of the discipline is as yet unattained, it will achieve adult status through practice, not by waiting for academia to glacially catch up.     

Need for well-balanced education in software engineering measurement

This paper deals with a perceived need for a well-balanced education (or in some cases re-education) in the subject of software engineering measurement, more commonly although less accurately known as software metrics. This need was confirmed by a major survey of both industry and academia conducted in 1989.Software metrics have received a lot of bad press in the past, mainly due to some much criticized early work in so-called complexity metrics. A result of this has been scepticism or lack of interest in other areas of the wider subject of software engineering measurement, which covers not only models and measures applicable to software products, but also those applicable to the processes and resources involved in software production.The ideas and work described in this paper have arisen out of the ESPRIT project METKIT, which has produced educational material about software engineering measurement for use in both industry and academia. This paper also describes the material designed for academia, most of which has now been tested in 12 European academic institutions. The material concentrates on principles and examples rather than prescribing the use of particular models and measures.This material has been widely publicized; the response to it has been encouraging so far and it appears that the material will have a significant impact towards getting the subject taught much more widely, and in a more balanced way.     

Industry–academia collaborations in software testing: experience and success stories from Canada and Turkey

Collaboration between industry and academia supports improvement and innovation in industry and helps to ensure industrial relevance in academic research. However, many researchers and practitioners believe that the level of joint industry–academia collaborations (IAC) in software engineering (SE) is still relatively very low, compared to the amount of activity in each of the two communities. The goal of the empirical study reported in this paper is to characterize a set of collaborative industry–academia R&D projects in the area of software testing conducted by the authors (based in Canada and Turkey) with respect to a set of challenges, patterns and anti-patterns identified by a recent Systematic Literature Review study, with the aim of contributing to the body of evidence in the area of IAC, for the benefit of SE researchers and practitioners in conducting successful IAC projects in software testing and in software engineering in general. To address the above goal, a pool of ten IAC projects (six completed, two failed and two ongoing) all in the area of software testing, which the authors have led or have had active roles in, were selected as objects of study and were analyzed (both quantitatively and qualitatively) with respect to the set of selected challenges, patterns and anti-patterns. As outputs, the study presents a set of empirical findings and evidence-based recommendations, e.g.: it has been observed that even if an IAC project may seem perfect from many aspects, one single major challenge (e.g., disagreement in confidentiality agreements) can lead to its failure. Thus, we recommend that both parties (academics and practitioners) consider all the challenges early on and proactively work together to eliminate the risk of challenges in IAC projects. We furthermore report correlation and interrelationship of challenges, patterns and anti-patterns with project success measures. This study hopes to encourage and benefit other SE researchers and practitioners in conducting successful IAC projects in software testing and in software engineering in general in the future.     

SERP-test: a taxonomy for supporting industry–academia communication

This paper presents the construction and evaluation of SERP-test, a taxonomy aimed to improve communication between researchers and practitioners in the area of software testing. SERP-test can be utilized for direct communication in industry academia collaborations. It may also facilitate indirect communication between practitioners adopting software engineering research and researchers who are striving for industry relevance. SERP-test was constructed through a systematic and goal-oriented approach which included literature reviews and interviews with practitioners and researchers. SERP-test was evaluated through an online survey and by utilizing it in an industry–academia collaboration project. SERP-test comprises four facets along which both research contributions and practical challenges may be classified: Intervention, Scope, Effect target and Context constraints. This paper explains the available categories for each of these facets (i.e., their definitions and rationales) and presents examples of categorized entities. Several tasks may benefit from SERP-test, such as formulating research goals from a problem perspective, describing practical challenges in a researchable fashion, analyzing primary studies in a literature review, or identifying relevant points of comparison and generalization of research.     

Onboarding inexperienced developers: struggles and perceptions regarding automated testing

Previous research found that inexperienced software engineers may tend to view automatic testing as a waste of time and as an activity completely separate from programming. This could have a negative impact on their later careers and could be a sign that improvements in software engineering education are needed when it comes to testing. At the same time, this stance could negatively influence the perception that practitioners have of recent university graduates. To explore this issue, we conducted a qualitative study and surveyed 170 and interviewed 22 practitioners about their experiences with recent graduates, focusing on software testing skills. We find that practitioners do recognize a skill gap between university graduates and industry expectations and that this perception could be engrained deeply enough already to influence hiring practices. Practitioners use different and at times costly strategies to alleviate this skill gap, such as training and mentoring efforts. We validated core findings in a survey with 698 professional software developers. Our qualitative insights can help industry, research, and educational institutions guide in-depth studies that explore the severity of the effects we have found. The coping strategies we have found can provide valuable starting points that can inform changes in how we educate the software engineers of the future.     

The synergistic integration of mathematics, software engineering, and user-centred design: exploring new trends in education

There is an increasing recognition in the society that interdisciplinary challenges must be part of new educational practices. In this paper, we describe the key curriculum activities at the University of Southern Denmark that combine mathematical modelling, software engineering, and user-centred design courses. These three disciplines represent a core of our graduate program, aiming at educating the professionals that will be capable of not only using but also further developing new technologies, and therefore, will be capable of fostering further the progress in computational science and engineering. Finally, we show how the learning environment, with emphases on broadening the student experience by industrial links, affects the student career aspiration.     

Software engineering technology innovation - Turning research results into industrial success

This paper deals with the innovation of software engineering technologies. These technologies are methods and tools for conducting software development and maintenance. We consider innovation as a process consisting of two phases, being technology creation and technology transfer. In this paper, we focus mainly on the transfer phase.Technology transfer is of mutual interest to both academia and industry. Transfer is important for academia, because it shows the industrial relevance of their research results to, for example, their sponsoring authorities. Showing the industrial applicability of research results is sometimes referred to as valorization of research. Nowadays, valorization is often required by research funding bodies. The transfer is important for industries, because innovating their development processes and their products is supportive in gaining a competitive edge or remaining competitive in their business. We describe the technology transfer phase by means of three activities: technology evaluation, technology engineering, and technology embedding. The technology evaluation activity is perceived as the main gate between the technology creation phase and the technology transfer phase. With two case studies, originating from the Dutch high-tech systems industry, we will illustrate the activities in the transfer phase.In addition to the process we will also define the main roles in a software engineering technology innovation, namely: the technology provider (academic research, industrial research and technology vendor) and the technology receiver (industrial development). With those roles we also address the issues concerning the ownership of technologies.     

Knowledge processing for concurrent engineering: An evolving challenge in CIM research

As technological tasks in CIM environments become more complicated, the level of intelligence required to automate and integrate these tasks also evolves with increasing complexity. This paper classifies CIM tasks and their required intelligence into facility, data and decision levels, and discusses the automation and integration of those knowledge-intensive CIM tasks at their decision level. Since decision-level tasks are often more abstract than those at the facility and data levels, a systematic approach is necessary to build research programs for the automation of these tasks. This paper will use the decision-level task of concurrent engineering as an example to explain the five-step approach that we have adapted to form our research programs in this evolving area of CIM research. These five steps are: (1) perform analysis of the task and its needed decision-level supports, (2) conceptualize these analysis results into a concise framework, (3) propose a software paradigm for the conceptual framework, (4) identify functional requirements from this paradigm to guide software implementations, and (5) correlate implementation results to identify a fundamental technology. More specifically, the analysis of concurrent engineering tasks in CIM can be found in Section 2. Section 3 explains the conceptualization process which views decision making activities as mappings and loops between a control and performance space. In Section 4, concurrent engineering is modeled as a team problem-solving process participated in by multiple cooperating knowledge sources (MCKS) with overlapping expertise to perform those loops. Several functional requirements are identified from this MCKS model of concurrent engineering and example research activities to address these challenges are described in Section 5. The correlations in Section 6 indicate that the knowledge processing technology, evolved from applied artificial intelligence research, is a fundamental technology for building intelligent systems to support various knowledge-intensive CIM tasks at their decision level.     

Naked into the World: IT experiences on a final primary school teaching practice—a second survey

Abstract This study reports a survey of 103 student teachers who were asked about their experiences of IT on their final teaching practice. Data are related to those from an earlier survey of the same group of students on their first teaching practice. The use of IT was higher than before, but still unacceptably low. A large majority of students will graduate with no classroom experience of databases and other applications software; a significant number will graduate without any classroom experiences using IT whatsoever. The patterns of IT use in class were most disappointing. A predominant use was for pupils to work on tasks unrelated to lesson plans, often practising basic skills.
Those students who had taken a course in computer studies were more confident in their use of IT, made more use of IT in class, and experienced fewer technical problems than students who had not taken this course. However, students who had taken this course were no more likely to use a computer in class than those who had not. Students who do use IT in class reported increased confidence and a desire to make greater use of IT in the future. It is concluded that compulsory courses on the educational uses of IT, and use of IT early in teaching practice will help improve the current unacceptable situation, so long as they address the problem of ensuring appropriate classroom use of IT by students.     

Master's Degrees in Software Engineering: An Analysis of 28 University Programs

The Software Engineering Institute published the last reference curriculum for a master's in software engineering in 1991. In 2007, a coalition from academia, industry, and government began creating a new reference curriculum. An early step was to establish a baseline of graduate education by surveying 28 master's programs in software engineering. The survey was largely limited to US schools. Key findings showed that the universities viewed software engineering largely as a specialization of computer science, that faculty size is generally small with few dedicated professors, and that new master's programs continue to start despite the decrease in computer science majors over the past few years. We used the IEEE Computer Society's Software Engineering Body of Knowledge (SWEBOK) to structure our analysis of the 28 curricula, focusing primarily on courses and topics required or semirequired of all students. (A course is semirequired if there is at least a 50 percent chance a student must take it.) Major findings show wide variation in the depth and breadth of SWEBOK coverage in required and semirequired courses, less than 40 percent of all programs requiring an introductory course on software engineering, and many universities having required and semirequired courses that are peripheral to SWEBOK.     

Software engineering grows up

The author discusses licensing in the software engineering profession. If software professionals do not participate in defining licensing and other regulation mechanisms, they could find themselves at the mercy of laws designed to protect segments of industry or to increase the reach of professional organizations that do not represent them     

Training practicing software engineers at Texas instruments

Much has been written about software engineering programs from the viewpoint of the academician, but do these programs really reflect the need of industry? This paper provides some insight into the needs of practicing software engineers at Texas Instruments who are developing software according to military specifications and requirements for embedded real-time systems. The needs of our environment are compared to the entering skills of a typical newhire, with the differences noted. These differences can be satisfied by internal training that covers all aspects of software engineering, from communicating with co-workers to understanding the system life cycle.     

GPU Acceleration for FEM-Based Structural Analysis

Graphic Processing Units (GPUs) have greatly exceeded their initial role of graphics accelerators and have taken a new role of co-processors for computation—heavy tasks. Both hardware and software ecosystems have now matured, with fully IEEE compliant double precision and memory correction being supported and a rich set of software tools and libraries being available. This in turn has lead to their increased adoption in a growing number of fields, both in academia and, more recently, in industry. In this review we investigate the adoption of GPUs as accelerators in the field of Finite Element Structural Analysis, a design tool that is now essential in many branches of engineering. We survey the work that has been done in accelerating the most time consuming steps of the analysis, indicate the speedup that has been achieved and, where available, highlight software libraries and packages that will enable the reader to take advantage of such acceleration. Overall, we try to draw a high level picture of where the state of the art is currently at.     

以服务为导向的软件工程研究生培养模式

在以服务理念为导向的软件产业发展趋势下,高等院校的软件工程研究生培养模式应该有所调整。通过增强咨询和管理知识的学习,在项目实践和交流中提升软件工程研究生的综合能力和重新规划专业方向这三个步骤建立新型的软件工程研究生培养模式,为高速发展的信息产业和我国各行业的信息化建设提供优秀的人才。     

以服务为导向的软件工程研究生培养模式

在以服务理念为导向的软件产业发展趋势下,高等院校的软件工程研究生培养模式应该有所调整。通过增强咨询和管理知识的学习,在项目实践和交流中提升软件工程研究生的综合能力和重新规划专业方向这三个步骤建立新型的软件工程研究生培养模式,为高速发展的信息产业和我国各行业的信息化建设提供优秀的人才。     

Procurement Fraud Vulnerability: A Case Study

Abstract

In today’s digital dependent world, organizations struggle to mitigate a stealthy, well-resourced, and tenacious advanced persistent threat (APT) attacks by nefarious actors, organizations, and even nation-states with intent on gaining a foothold into an organization’s IT infrastructure. This onslaught of advanced attacks requires far more than baseline security practices. While most security professionals are APT-aware, many lack the experience, requisite skills, and the ability to integrate technology to counter APT attacks. The problem is exacerbated by a widening cybersecurity skills gap. Recent research by ISACA, the world’s largest information security professional association, reported more than 60% of applicants for entry level cybersecurity positions lack the skill and ability to perform the tasks associated with their potential new roles. Success against the APT is predicated on insight into APT attack stages and the integration of technology to enable organizational resilience; however, this is not possible in organizations do not have the workforce with the requisite knowledge, skills, and abilities to perform the technical tasks related to their functional roles. This article addresses a customized response strategy executed by a skilled workforce that mitigates and even counters attacks. The strategy recommends that a coordinated response based on organization risk management policies be implemented. In addition, it requires organizational insight into their information assets, control of administrator privileges, implementation of sound network segregation architecture, and a commitment to a balanced vulnerability management program. It is critical that a further discussion occur to outline skills acquisition based on skills-based training and performance-based assessments.