Convergence of AI programming and software engineering

Context: Capture-recapture method has long been adopted in software engineering as a relatively objective way for defect estimation. While many relevant studies have been carried out to evaluate various capture-recapture models and estimators, there still lacks common understanding on the adoption status of the method in software engineering. It is necessary to systematically collect empirical evidence of Capture-recapture adoption hence form necessary understanding on the method.Objective: This study aims to synthesize relevant primary studies on the adoption of capture-recapture method in software engineering, and try to identify possible gaps between the state-of-practice and the state-of-art so as to provide clues for future research.Method: By following the guidelines of Kitchenham, we conducted a Systematic Literature Review(SLR) on studies of the adoption of capture-recapture method in software engineering.Results: From 5 common digital libraries, we retrieved 506 published articles, among them 44 were identified as relevant primary studies. We identified 18 capture-recapture estimators under 4 basic models. Types of the currently existing studies as well as the relevant influencing factors to adoption of the capture-recapture method are also discussed.Conclusion: Results show that there are no conclusive decisions on the best capture-recapture models and estimators. Besides, the number of inspectors and their capability to detect defects as well as the difficulty to detect defects are most critical influencing factors. In addition, lacking of industrial application may be the major issue of current adoption status of capture-recapture method in software engineering.

Learning Software Engineering principles, processes, methods and tools is a prerequisite to becoming a Software Engineer. The technological advancements and revolution in this new century are probing the boundaries of education and training in software engineering. This work tries to locate the shortcomings in existing approaches to Education in Software Engineering (ESE) in respect to today's technological advancements. We hereby proposed a new model for Education in Software Engineering to bridge the industry-academia gap.

This paper describes work that explores how tools can help change agents in software organizations incorporate new software engineering tools and methods more effectively. A prototype expert system was built to assist change agents in gathering information and planning tasks in a software engineering adoption and implementation effort. The knowledge engineering process for this system helped to integrate and translate research and practice from software engineering technology adoption and implementation within the field of technology transfer and diffusion of innovation for software change agents.KeywordsSoftware engineeringadoptionimplementationtechnology transferknowledge-based toolexpert systemknowledge elicitation

As a basis subject of computer, Computer software engineering has been increasingly used in various fields, Games management system has been pre-designed on the basis of application of software engineering theory and method. The actual games management system software has been developed from using software engineering methods, in the actual design and development, it has been proved that a practical system has been perfect created with efficiency design, fully functional form, rational and affordable design.

This paper considers the current state of software engineering for parallel systems. A review of existing approaches and techniques identifies inadequacies. Recent work on design, verification and automated support is outlined. The next generation of embedded and distributed technologies will compound the problems through increased demand and diversity. This paper discusses the implications for the progression of current techniques into new methods for future software engineering of parallel systems.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

The discipline of Software Engineering is continuously adapting to new challenges while gaining more and more insights. The age of globalisation has brought about a new movement of internationalisation and localisation. While practitioners fully embrace the efforts, educators only marginally consider the implications for the teaching and learning of Software Engineering. While the relevance of the software deployment context has been widely recognised, the intrinsic values of the development context are less evident. Besides western cultural indicators being omnipresent in software applications, they are deeply rooted in Software Engineering concepts and methods. Standards and models have been established in the absence of possible deviations from other -- e.g. African -- contexts. Educators and authors of common and internationally used textbooks present Software Engineering concepts and methods as universally valid. Thus software engineering graduates all over the world continue to be ill-equipped for specific software development contexts. Moreover the necessity to localise Software Engineering education is illustrated by our vast amount of challenges, experiences and best-practices of teaching Software Engineering in a Sub-Saharan country. In this paper, we introduce a generic framework leading towards a Contextualised Software Engineering education (CSE2).

A comprehensive engineering framework for guaranteeing component compatibility

Computer science and art have been in contact since the 1960s. Our hypothesis is that software engineering can benefit from multidisciplinary research at the intersection with art for the purpose of increasing innovation and creativity. To do so, we have designed and planned a literature review in order to identify the existing knowledge base in this interdisciplinary field. A preliminary analysis of both results of our review and observations of software development projects with artist participation, reveals four main issues. These are software development issues, which include requirement management, tools, development and business models; educational issues, with focus on multidisciplinary education; aesthetics of both code and user interface, and social and cultural implications of software and art. The identified issues and associated literature should help researchers design research projects at the intersection of software engineering and art. Moreover, they should help artists to increase awareness about software engineering methods and tools when conceiving and implementing their software-based artworks.

Traditional, informal techniques in software engineering reach their limits when complex systems are to be developed efficiently. The Institute for Formal Methods in Computer Science of the Universitat Stuttgart states: Tools like IDEs, automatic code generation from graphical descriptions, visualization techniques like UML diagrams, and others are certainly necessary. However, they often lack the ability to support detailed and provably sound reasoning about complex systems. Formal methods in software engineering provide approaches to close that gap.

Empirical research is playing a significant role in software engineering (SE), and it has been applied to evaluate software artifacts and technologies. There have been a great number of empirical research articles published recently. There is also a large research community in empirical software engineering (ESE). In this paper, we identify both the overall landscape and detailed implementations of ESE, and investigate frequently applied empirical methods, targeted research purposes, used data sources, and applied data processing approaches and tools in ESE. The aim is to identify new trends and obtain interesting observations of empirical software engineering across different sub-fields of software engineering. We conduct a mapping study on 538 selected articles from January 2013 to November 2017, with four research questions. We observe that the trend of applying empirical methods in software engineering is continuously increasing and the most commonly applied methods are experiment, case study and survey. Moreover, open source projects are the most frequently used data sources. We also observe that most of researchers have paid attention to the validity and the possibility to replicate their studies. These observations are carefully analyzed and presented as carefully designed diagrams. We also reveal shortcomings and demanded knowledge/strategies in ESE and propose recommendations for researchers.

Specialized tools, such as IDEs, issue trackers, and code review tools, are an indispensable part of the modern software engineering process. These tools are constantly evolving. Besides enabling tools to support a wider range of technologies and frameworks, we are learning to provide additional features in completely new ways. One prominent stream of innovation in software engineering tools is dedicated to utilizing historical data to enable data-driven features, such as defect prediction engines and recommender systems, which leverage records of prior activity to assist with decision making. Many data-driven features in software engineering tools initially get born out of the context of real-world tools as techniques devised and evaluated in synthetic settings by researchers. While convenient, synthetic evaluation of approaches that are ultimately aimed at bringing improvement to real world problems involves a number of simplifications and assumptions. In this dissertation, we highlight several aspects that, while vital for bringing innovative methods to software engineering tools, are often discarded in existing research. We closely explore several topics specific to artificial evaluation environments, such as simplifications in mining file modification histories, use of synthetic datasets for source code authorship attribution, and a gap between accuracy of reviewer recommendation models and their perception by users. Moreover, we make a case for sharing technical artifacts by converting data mining pipelines into reusable tools, and propose a novel approach to modeling expertise transfer from code modification by capturing individual contribution style of developers. Key contributions of this dissertation include a high-level model of the lifecycle of a data-driven software engineering technique, a discussion of dangerous assumptions and simplifications that are made on every step in this lifecycle, a demonstration of importance of a careful approach to mining software repositories, and a demonstration of serious misalignment between artificial evaluation and realistic environments for the problems of code reviewer recommendation and code authorship attribution. We conclude the dissertation by discussing underlying reasons for misalignment between research environments and real-world tools, and propose potential steps to narrow it down and ultimately accelerate innovation in software engineering tooling.

Paradigms for experimentation and empirical studies in software engineering

: Software engineering tools are computer programs that assist people in doing the work of software engineering. As understanding of the software engineering process has broadened and the need to solve problems has intensified, there has been increasing interest in using software engineering tools. Understanding what a tool does and comparing it to similar tools are difficult tasks given the diversity of functionality that exists. This report describes a tool classification technique that helps those investigating tools decide where a tool fits in the software engineering process and identify what a tool does or doesn't do. It also provides guidance to the tool evaluation process and lists specific criteria that should be considered when evaluating tools.

Software engineering is a design discipline. As such, its engineering methods are based on cognitive instead of physical laws, and their effectiveness depends highly on context. Empirical methods can be used to observe the effects of software engineering methods in vivo and in vitro, to identify improvement potentials, and to validate new research results. This paper summarizes both the current body of knowledge and further challenges wrt. empirical methods in software engineering as well as empirically derived evidence regarding software typical engineering methods. Finally, future challenges wrt. education, research, and technology transfer will be outlined.

ISEF is an environment for programming-in-the-large that integrates disparate software engineering principles, methods and tools into an industrial-strength, automated software development framework. Projects using ISEF have reported increased software quality, improved software manageability and decreased software production costs. This paper presents the basic principles and mechanisms that enable ISEF to achieve environment/process integration as well as integration within the environment itself, describes the ISEF approach to software development, provides comparisons with related work, and reports on experience in using ISEF.