Defining a Requirements Process Improvement Model

Both software organisations and the academic community are aware that the requirements phase of software development is in need of further support. We address this problem by creating a specialised Requirements Capability Maturity Model (R-CMM¹). The model focuses on the requirements engineering process as defined within the established Software Engineering Institute’s (SEI’s) software process improvement framework. Our empirical work with software practitioners is a primary motivation for creating this requirements engineering process improvement model. Although all organisations in our study were involved in software process improvement (SPI), they all showed a lack of control over many requirement engineering activities.This paper describes how the requirements engineering (RE) process is decomposed and prioritised in accordance with maturity goals set by the SEI’s Software Capability Maturity Model (SW CMM). Our R-CMM builds on the SEI’s framework by identifying and defining recommended RE sub-processes that meet maturity goals. This new focus will help practitioners to define their RE process with a view to setting realistic goals for improvement.Sarah Beecham is a research fellow in the Department of Maths and Computing in The Open University in the UK. She is currently working on the EPSRC funded CRESTES project () looking into modelling resource estimation for long-lived software. She has recently completed her PhD for a program of work entitled “A Requirements-based Software Process Maturity Model”. Current research interests are in estimation for software evolution and maintenance and in the general areas of software process improvement. Her particular research interests are in empirical methods in software engineering and requirements engineering.Tracy Hall leads the Systems & Software Research Group in the Department of Computer Science at the University of Hertfordshire. She specialises in the empirical investigation of technical and non-technical issues within software engineering. During the past ten years Tracy has successfully collaborated with many companies on a variety of research projects. She is very active in the Empirical Software Engineering community and is regularly invited to talk about empirical methods both in the UK and abroad. Tracy is an accomplished researcher having published over twenty high quality journal papers.Austen Rainer Austen Rainer is a senior lecturer at the University of Hertfordshire. He studied for his PhD at Bournemouth University, in conjunction with IBM Hursley Park. His current research interests include open source software development, longitudinal case study research, and the credibility of empirical evidence for researchers and software practitioners.     

软件可靠性工程学综述

软件可靠性工程学定量评价软件系统的可靠性,是开发并维护软件系统的一种工程学技术.回顾了软件可靠性工程学的历史、目前的趋势以及现存的问题和困难.提出了软件可靠性工程学中未来可能的方向和有前景的研究课题.     

一种基于Markov模型的自适应软件可用性监测模型

软件可用性工程是当前软件开发的重要研究领域,研究者试图通过对软件可用性特征的分析提高使用者使用效率,改善软件质量。本文针对软件使用过程中的用户操作特征,采用Markov模型对用户软件操作过程进行聚类和建模。并在此基础上根据用户模型的概率描述指标,提出了相应的在线模型更新算法和帮助系统设计方法。在实际软件设计过程中设计实现了以此为理论基础的试验系统,取得了较好的应用效果。     

Teaching PSP: challenges and lessons learned

Software engineering educators need to provide environments where students learn about the size and complexity of modern software systems and the techniques available for managing these difficulties. Five universities used the personal software process to teach software engineering concepts in a variety of contexts.     

软件开发方法发展回顾与展望

软件是信息化社会的基础设施,而构造并运用软件的能力成为一种核心竞争力.软件开发方法凝结了系统化的软件构造过程和技术.简要回顾了50年来软件开发方法发展历程中具有重要影响的里程碑,包括基于结构化程序设计和模块化开发的基本方法、面向对象方法、软件复用与构件化方法、面向方面的方法、模型驱动的方法,以及服务化的方法.而后针对Internet的发展普及以及人机物融合应用对软件开发方法提出的挑战,介绍了网构软件的研究和探索,并展望未来人机物融合的软件方法和技术.     

Reusing software: issues and research directions

Software productivity has been steadily increasing over the past 30 years, but not enough to close the gap between the demands placed on the software industry and what the state of the practice can deliver; nothing short of an order of magnitude increase in productivity will extricate the software industry from its perennial crisis. Several decades of intensive research in software engineering and artificial intelligence left few alternatives but software reuse as the (only) realistic approach to bring about the gains of productivity and quality that the software industry needs. In this paper, we discuss the implications of reuse on the production, with an emphasis on the technical challenges. Software reuse involves building software that is reusable by design and building with reusable software. Software reuse includes reusing both the products of previous software projects and the processes deployed to produce them, leading to a wide spectrum of reuse approaches, from the building blocks (reusing products) approach, on one hand, to the generative or reusable processor (reusing processes), on the other. We discuss the implication of such approaches on the organization, control, and method of software development and discuss proposed models for their economic analysis. Software reuse benefits from methodologies and tools to: (1) build more readily reusable software and (2) locate, evaluate, and tailor reusable software, the last being critical for the building blocks approach. Both sets of issues are discussed in this paper, with a focus on application generators and OO development for the first and a thorough discussion of retrieval techniques for software components, component composition (or bottom-up design), and transformational systems for the second. We conclude by highlighting areas that, in our opinion, are worthy of further investigation     

An Empirical Study of Lehman's Law on Software Quality Evolution

Software systems must change to adapt to new functional requirements and nonfunctional requirements. According to Lehman''s laws of software evolution, on the one side, the size and the complexity of a software system will continually increase in its life time; on the other side, the quality of a software system will decrease unless it is rigorously maintained and adapted. Lehman''s laws of software evolution, especially of those on software size and complexity, have been widely validated. However, there are few empirical studies of Lehman''s law on software quality evolution, despite the fact that quality is one of the most important measurements of a software product. This paper defines a metric---accumulated defect density---to measure the quality of evolving software systems. We mine the bug reports and measure the size and complexity growth of four evolution lines of Apache Tomcat and Apache Ant projects. Based on these studies, Lehman''s law on software quality evolution is examined and evaluated.     

A systematic mapping study of search-based software engineering for software product lines

ContextSearch-Based Software Engineering (SBSE) is an emerging discipline that focuses on the application of search-based optimization techniques to software engineering problems. Software Product Lines (SPLs) are families of related software systems whose members are distinguished by the set of features each one provides. SPL development practices have proven benefits such as improved software reuse, better customization, and faster time to market. A typical SPL usually involves a large number of systems and features, a fact that makes them attractive for the application of SBSE techniques which are able to tackle problems that involve large search spaces.ObjectiveThe main objective of our work is to identify the quantity and the type of research on the application of SBSE techniques to SPL problems. More concretely, the SBSE techniques that have been used and at what stage of the SPL life cycle, the type of case studies employed and their empirical analysis, and the fora where the research has been published.MethodA systematic mapping study was conducted with five research questions and assessed 77 publications from 2001, when the term SBSE was coined, until 2014.ResultsThe most common application of SBSE techniques found was testing followed by product configuration, with genetic algorithms and multi-objective evolutionary algorithms being the two most commonly used techniques. Our study identified the need to improve the robustness of the empirical evaluation of existing research, a lack of extensive and robust tool support, and multiple avenues worthy of further investigation.ConclusionsOur study attested the great synergy existing between both fields, corroborated the increasing and ongoing interest in research on the subject, and revealed challenging open research questions.     

Evolutionary Sampling and Software Quality Modeling of High-Assurance Systems

Software quality modeling for high-assurance systems, such as safety-critical systems, is adversely affected by the skewed distribution of fault-prone program modules. This sparsity of defect occurrence within the software system impedes training and performance of software quality estimation models. Data sampling approaches presented in data mining and machine learning literature can be used to address the imbalance problem. We present a novel genetic algorithm-based data sampling method, named Evolutionary Sampling, as a solution to improving software quality modeling for high-assurance systems. The proposed solution is compared with multiple existing data sampling techniques, including random undersampling, one-sided selection, Wilson's editing, random oversampling, cluster-based oversampling, Synthetic Minority Oversampling Technique (SMOTE), and Borderline-SMOTE. This paper involves case studies of two real-world software systems and builds C4.5- and RIPPER-based software quality models both before and after applying a given data sampling technique. It is empirically shown that Evolutionary Sampling improves performance of software quality models for high-assurance systems and is significantly better than most existing data sampling techniques.      

A Basis for Analyzing Software Architecture Analysis Methods

A software architecture is a key asset for any organization that builds complex software-intensive systems. Because of an architecture's central role as a project blueprint, organizations should analyze the architecture before committing resources to it. An analysis helps to ensure that sound architectural decisions are made. Over the past decade a large number of architecture analysis methods have been created, and at least two surveys of these methods have been published. This paper examines the criteria for analyzing architecture analysis methods, and suggests a new set of criteria that focus on the essence of what it means to be an architecture analysis method. These criteria could be used to compare methods, to help understand the suitability of a method, or to improve a method. We then examine two methods—the Architecture Tradeoff Analysis Method and Architecture-level Modifiability Analysis—in light of these criteria, and provide some insight into how these methods can be improved. Rick Kazman is a Senior Member of the Technical Staff at the Software Engineering Institute of Carnegie Mellon University and Professor at the University of Hawaii. His primary research interests are software architecture, design and analysis tools, software visualization, and software engineering economics. He also has interests in human-computer interaction and information retrieval. Kazman has created several highly influential methods and tools for architecture analysis, including the SAAM and the ATAM. He is the author of over 80 papers, and co-author of several books, including “Software Architecture in Practice”, and “Evaluating Software Architectures: Methods and Case Studies”. Len Bass is a Senior Member of the Technical Staff at the Software Engineering Institute (SEI). He has written two award winning books in software architecture as well as several other books and numerous papers in a wide variety of areas of computer science and software engineering. He is currently working on techniques for the methodical design of software architectures and to understand how to support usability through software architecture. He has been involved in the development of numerous different production or research software systems ranging from operating systems to database management systems to automotive systems. Mark Klein is Senior Member of the Technical Staff of the Software Engineering Institute. He has over 20 years of experience in research on various facets of software engineering, dependable real-time systems and numerical methods. Klein's most recent work focuses on the analysis of software architectures, architecture tradeoff analysis, attribute-driven architectural design and scheduling theory. Klein's work in real-time systems involved the development of rate monotonic analysis (RMA), the extension of the theoretical basis for RMA, and its application to realistic systems. Klein's earliest work involved research in high-order finite element methods for solving fluid flow equations arising in oil reservoir simulation. He is the co-author two books: “A Practitioner's Handbook for Real-Time Analysis: Guide to Rate Monotonic Analysis for Real-Time Systems” and “Evaluating Software Architecture: Methods and Case Studies”. Anthony J. Lattanze is an Associate Teaching Professor at the Institute for Software Research International (ISRI) at Carnegie Mellon University (CMU) and a senior member of the technical staff at the Software Engineering Institute (SEI). Anthony teaches courses in CMUs Masters of Software Engineering Program in Software Architecture, Real-Time/Embedded Systems, and Software Development Studio. His primary research interest is in the area software architectural design for embedded, software intensive systems. Anthony consults and teaches throughout industry in the areas of software architecture design and architecture evaluation. Prior to Carnegie Mellon, Mr. Lattanze was the Chief of Software Engineering for the Technology Development Group at the United States Flight Test Center at Edwards Air Force Base, CA. During his tenure at the Flight Test Center, he was involved with a number of software and systems engineering projects as a software and systems architect, project manager, and developer. During this time as he was involved with the development, test, and evaluation of avionics systems for the B-2 Stealth Bomber, F-117 Stealth Fighter, and F-22 Advanced Tactical Fighter among other systems. Linda Northrop is the director of the Product Line Systems Program at the Software Engineering Institute (SEI) where she leads the SEI work in software architecture, software product lines and predictable component engineering. Under her leadership the SEI has developed software architecture and product line methods that are used worldwide, a series of five highly-acclaimed books, and Software Architecture and Software Product Line Curricula. She is co-author of the book, “Software Product Lines: Practices and Patterns,” and a primary author of the SEI Framework for Software Product Line Practice.     

Modeling the growth of complex software function dependency networks

Software engineering efforts can potentially benefit much from a good understanding of the structures of existing software systems and the processes governing their development. Towards that end, we study software systems by means of the complex network analysis framework. We model a software package as a network, with nodes representing the functions in the package and edges representing the dependencies among the functions. Our empirical analysis of five widely-adopted open-source software packages reveals a set of interesting features of such networks, which cannot be adequately reproduced by existing complex network models. We then set out to develop a new network growth model, explicitly imitating generally-advocated software development principals, such as divide-and-conquer, modularization, high intra-module cohesion, and low inter-module coupling. Results of our analytical derivations and numeric studies show that our model can more closely reproduce the particular features exhibited by real-world software packages, thus hopefully better explaining the phenomena of concern.     

Software evolution visualization: A systematic mapping study

BackgroundSoftware evolution is an important topic in software engineering. It generally deals with large amounts of data, as one must look at whole project histories as opposed to their current snapshot. Software visualization is the field of software engineering that aims to help people to understand software through the use of visual resources. It can be effectively used to analyze and understand the large amount of data produced during software evolution.ObjectiveThis study investigates Software Evolution Visualization (SEV) approaches, collecting evidence about how SEV research is structured, synthesizing current evidence on the goals of the proposed approaches and identifying key challenges for its use in practice.MethodsA mapping study was conducted to analyze how the SEV area is structured. Selected primary studies were classified and analyzed with respect to nine research questions.ResultsSEV has been used for many different purposes, especially for change comprehension, change prediction and contribution analysis. The analysis identified gaps in the studies with respect to their goals, strategies and approaches. It also pointed out to a widespread lack of empirical studies in the area.ConclusionResearchers have proposed many SEV approaches during the past years, but some have failed to clearly state their goals, tie them back to concrete problems, or formally validate their usefulness. The identified gaps indicate that there still are many opportunities to be explored in the area.     

The applicability of software engineering in information systems development

The development of computer-based information systems involves more than the building of a complicated software system because each information system is embedded in a social and organizational environment. Software Engineering, which relies mainly on engineering approaches and places emphasis on formal methods, is inadequate to steer information systems development projects. Particular advances in Software Engineering will be best utilized within a broad framework which is capable of dealing with both technical and social/organizational issues.     

Fundamental Laws and Assumptions of Software Maintenance

Researchers must pay far more attention to discovering and validating the principles that underlie software maintenance and evolution. This was one of the major conclusions reached during the International Workshop on Empirical Studies of Software Maintenance. This workshop, held in November 1996 in Monterey, California, brought together an international group of researchers to discuss the successes, challenges and open issues in software maintenance and evolution. This article documents the discussion of the subgroup on fundamental laws and assumptions of software maintenance. The participants of this group included researchers in software engineering, the behavioral sciences, information systems and statistics. Their main conclusion was that insufficient effort has been paid to synthesizing research conjectures into validated theories and that this problem has slowed progress in software maintenance. To help support this vision they identified the following supporting conclusions. (1) need to develop a genuine scientific approach—more than just using empirical methods, (2) other disciplines can help, (3) need to explore a wider range of approaches to empirical studies, (4) need to study both evolution and maintenance. This revised version was published online in July 2006 with corrections to the Cover Date.     

A systematic literature review on the usage of eye-tracking in software engineering

ContextEye-tracking is a mean to collect evidence regarding some participants’ cognitive processes. Eye-trackers monitor participants’ visual attention by collecting eye-movement data. These data are useful to get insights into participants’ cognitive processes during reasoning tasks.ObjectiveThe Evidence-based Software Engineering (EBSE) paradigm has been proposed in 2004 and, since then, has been used to provide detailed insights regarding different topics in software engineering research and practice. Systematic Literature Reviews (SLR) are also useful in the context of EBSE by bringing together all existing evidence of research and results about a particular topic. This SLR evaluates the current state of the art of using eye-trackers in software engineering and provides evidence on the uses and contributions of eye-trackers to empirical studies in software engineering.MethodWe perform a SLR covering eye-tracking studies in software engineering published from 1990 up to the end of 2014. To search all recognised resources, instead of applying manual search, we perform an extensive automated search using Engineering Village. We identify 36 relevant publications, including nine journal papers, two workshop papers, and 25 conference papers.ResultsThe software engineering community started using eye-trackers in the 1990s and they have become increasingly recognised as useful tools to conduct empirical studies from 2006. We observe that researchers use eye-trackers to study model comprehension, code comprehension, debugging, collaborative interaction, and traceability. Moreover, we find that studies use different metrics based on eye-movement data to obtain quantitative measures. We also report the limitations of current eye-tracking technology, which threaten the validity of previous studies, along with suggestions to mitigate these limitations.ConclusionHowever, not withstanding these limitations and threats, we conclude that the advent of new eye-trackers makes the use of these tools easier and less obtrusive and that the software engineering community could benefit more from this technology.     

Process-Based Software Engineering: Building the Infrastructures

A recent trend in software engineering is the shift from a focus on laboratory-oriented software engineering to a more industry-oriented view of software engineering processes. This complements preceding ideas about software engineering in terms of organization and process-orientation. From the domain coverage point of view, many of the existing software engineering approaches have mainly concentrated on the technical aspects of software development. Important areas of software engineering, such as the technical and organizational infrastructures, have been left untouched. As software systems increase in scales, issues of complexity and professional practices become involved. Software development as an academic or laboratory activity, has to engage with software development as a key industrialized process.This expanded domain of software engineering exposes the limitations of existing methodologies that often address only individual subdomains. There is, therefore, a demand for an overarching approach that provide a basis for theoretical and practical infrastructures capable of accommodating the whole range of modern software engineering practices and requirements. One approach is provided by Process-Based Software Engineering (PBSE); part of the more general trend towards a focus on process.This paper provides a review of process techniques for software engineering and a high-level perspective on PBSE. Typical approaches and techniques for the establishment, assessment, improvement and benchmarking of software engineering process systems are introduced in this paper, and many are developed further in other contributions to this volume.     

Applying empirical software engineering to software architecture: challenges and lessons learned

In the last 15 years, software architecture has emerged as an important software engineering field for managing the development and maintenance of large, software-intensive systems. Software architecture community has developed numerous methods, techniques, and tools to support the architecture process (analysis, design, and review). Historically, most advances in software architecture have been driven by talented people and industrial experience, but there is now a growing need to systematically gather empirical evidence about the advantages or otherwise of tools and methods rather than just rely on promotional anecdotes or rhetoric. The aim of this paper is to promote and facilitate the application of the empirical paradigm to software architecture. To this end, we describe the challenges and lessons learned when assessing software architecture research that used controlled experiments, replications, expert opinion, systematic literature reviews, observational studies, and surveys. Our research will support the emergence of a body of knowledge consisting of the more widely-accepted and well-formed software architecture theories.     

PEM: The small company-dedicated software process quality evaluation method combining CMMISM and ISO/IEC 14598

Many small software organizations have recognized the need to improve their software product. Evaluating the software product alone seems insufficient since it is known that its quality is largely dependant on the process that is used to create it. Thus, small organizations are asking for evaluation of their software processes and products. The ISO/IEC 14598-5 standard is already used as a methodology basis for evaluating software products. This article explores how it can be combined with the CMMI to produce a methodology that can be tailored for process evaluation in order to improve their software processes. ^SM: CMMI is a service mark of Carnegie-Mellon University. Sylvie Trudel has over 20 years of experience in software. She worked for more than 10 years in development and implementation of management information systems and embedded real-time systems. Since 1996, she works as a process improvement specialist, implementing best practices into organizations processes from CMM and CMMI models. She performed several CMM and CMMI assessments and participated in many other CMM assessments such as CBA IPI, SCE, and other proprietary methods. She obtained a bachelors degree in computer science in 1986 from Laval University in Québec City and a Masters degree in Software Engineering at école de Technologie Supérieure (éTS) in Montréal. Sylvie is currently working as a software engineering advisor at the Centre de Recherche Informatique de Montréal (CRIM). Jean-Marc Lavoie has been working in software development for over 10 years. He performed and published a comparative study between the guide to the SWEBOK and the CMMI in 2003. Jean-Marc obtained a bachelor degree in Electrical Engineering. He is pursuing a Masters degree in Software Engineering at école de Technologie Supérieure (éTS) in Montréal while working as a software architect at Trisotech. Marie-Claude Pare has been working in software development for 7 years. Marie-Claude obtained a bachelor degree in Software Engineering from école Polytechnique in Montréal. She is pursuing a Masters degree in Software Engineering at école de Technologie Supérieure (éTS) in Montréal while working as a software engineer at Motorola GSG Canada. Dr Witold Suryn is a Professor at the école de technologie supérieure, Montreal, Canada (engineering school of the Université du Québec network of institutions) where he teaches graduate and undergraduate software engineering courses and conducts research in the domain of software quality engineering, software engineering body of knowledge and software engineering fundamental principles. Dr Suryn is also the principal researcher and the director of GELOG : IQUAL, the Software Quality Engineering Research Group at école de technologie supérieure. From October 2003 Dr. Suryn holds the position of the International Secretary of ISO/IEC SC7 – System and Software Engineering.     

A new approach in development of distributed framework for automated software testing using agents

Software testing is the technical kernel of software quality engineering, and to develop critical and complex software systems not only requires a complete, consistent and unambiguous design, and implementation methods, but also a suitable testing environment that meets certain requirements, particularly, to face the complexity issues. Traditional methods, such as analyzing each requirement and developing test cases to verify correct implementation, are not effective in understanding the software’s overall complex behavior. In that respect, existing approaches to software testing are viewed as time-consuming and insufficient for the dynamism of the modern business environment. This dynamics requires new tools and techniques, which can be employed in tandem with innovative approaches to using and combining existing software engineering methods. This work advocates the use of a recently proposed software engineering paradigm, which is particularly suited to the construction of complex and distributed software-testing systems, which is known as Agent-Oriented Software Engineering. This methodology is a new one, which gives the basic approach to agent-based frameworks for testing.