Forecasting technical debt evolution in software systems: an empirical study

Technical debt is considered detrimental to the long-term success of software development, but despite the numerous studies in the literature, there are still many aspects that need to be investigated for a better understanding of it. In particular, the main problems that hinder its complete understanding are the absence of a clear definition and a model for its identification, management, and forecasting. Focusing on forecasting technical debt, there is a growing notion that preventing technical debt build-up allows you to identify and address the riskiest debt items for the project before they can permanently compromise it. However, despite this high relevance, the forecast of technical debt is still little explored. To this end, this study aims to evaluate whether the quality metrics of a software system can be useful for the correct prediction of the technical debt. Therefore, the data related to the quality metrics of 8 different open-source software systems were analyzed and supplied as input to multiple machine learning algorithms to perform the prediction of the technical debt. In addition, several partitions of the initial dataset were evaluated to assess whether prediction performance could be improved by performing a data selection. The results obtained show good forecasting performance and the proposed document provides a useful approach to understanding the overall phenomenon of technical debt for practical purposes.     

Important characteristics of software development team members: an empirical investigation using Repertory Grid

An information system is typically developed by a team of information systems (IS) professionals. Research shows that teams staffed with the right people are more likely to be effective and efficient. There is a paucity of study that examines the important traits of IS professionals in team contexts. The objective of this research is to identify and understand the important characteristics of good team members in software development projects. We applied an established psychological technique (Repertory Grid) to guide our interviews with 21 experienced IS professionals, who have had extensive experience in software development teams. The comprehensive list of important characteristics was analysed qualitatively using open coding method of grounded theory. Fifty‐nine unique characteristics were identified and classified into eight categories. Among them, attitude/motivation, knowledge, interpersonal/communication skills, and working/cognitive ability were perceived by research participants to be the most important categories. Our study provides a context‐specific (i.e. software development team) evaluation of important characteristics of IS professionals. The results have significant implications for IS recruiting, IS training, IS staffing, and IS human resource management. Our study also supplements the research on management of IS development teams.     

Usage and evaluation of Supply Chain Management Software – results of an empirical study in the European automotive industry

Abstract. This paper presents an evaluation of Supply Chain Management Software. For this purpose, we conducted an empirical study in the European automotive industry among car manufacturers, suppliers, distributors, and logistic service providers from 25 countries. In particular, we analysed the objectives these companies are trying to achieve by using Supply Chain Management Software and evaluated to what extent these objectives have been accomplished. Our results show that the companies have been able to reduce both their costs and lead times and to improve their service levels. The survey also reveals, however, that until now, the cooperative potential of Supply Chain Management Software has not been utilized effectively.     

The lean gap: A review of lean approaches to large-scale software systems development

Lean approaches to product development (LPD) have had a strong influence on many industries and in recent years there have been many proponents for lean in software development as it can support the increasing industry need of scaling agile software development. With it's roots in industrial manufacturing and, later, industrial product development, it would seem natural that LPD would adapt well to large-scale development projects of increasingly software-intensive products, such as in the automotive industry. However, it is not clear what kind of experience and results have been reported on the actual use of lean principles and practices in software development for such large-scale industrial contexts. This was the motivation for this study as the context was an ongoing industry process improvement project at Volvo Car Corporation and Volvo Truck Corporation.     

Determinants of software quality in offshore development - An empirical study of an Indian vendor

Context

Cost advantage has been one of the primary drivers of successful offshoring engagements of Indian software and services companies. However, the emphasis has shifted to the ability of the vendors to provide high quality over cost advantage in delivering software products and services. Meeting high quality requirements of the clients is a challenge due to the very nature of development and delivery of software through offshoring.

Objective

The objective of this research paper is to identify and evaluate the key determinants of quality in the case of software projects delivered through offshoring model.

Method

A detailed survey was conducted among project managers/project leaders (leads) of a leading midsize Indian IT services company to evaluate the relationship of the determinants on the attributes of quality.

Results

Out of six determinants, our research reveals requirements uncertainty has significant association with all the attributes of quality. While process maturity and trained personnel have moderate association, communication and control, knowledge transfer and integration and technical infrastructure have relatively low association on software quality attributes in the case of offshoring.

Conclusion

It is concluded that the complexities in offshoring necessitates proper capturing of requirements. In addition high level of process maturity and availability of trained personnel to the project will help vendors to achieve software quality. The paper provides a set of implications for practice and directions for further research.     

An empirical study on the implementation and evaluation of a goal-driven software development risk management model

ContextBuilding a quality software product in the shortest possible time to satisfy the global market demand gives an enterprise a competitive advantage. However, uncertainties and risks exist at every stage of a software development project. These can have an extremely high influence on the success of the final software product. Early risk management practice is effective to manage such risks and contributes effectively towards the project success.ObjectiveDespite risk management approaches, a detailed guideline that explains where to integrate risk management activities into the project is still missing. Little effort has been directed towards the evaluation of the overall impact of a risk management method. We present a Goal-driven Software Development Risk Management Model (GSRM) and its explicit integration into the requirements engineering phase and an empirical investigation result of applying GSRM into a project.MethodWe combine the case study method with action research so that the results from the case study directly contribute to manage the studied project risks and to identify ways to improve the proposed methodology. The data is collected from multiple sources and analysed both in a qualitative and quantitative way.ResultsWhen risk factors are beyond the control of the project manager and project environment, it is difficult to control these risks. The project scope affects all the dimensions of risk. GSRM is a reasonable risk management method that can be employed in an industrial context. The study results have been compared against other study results in order to generalise findings and identify contextual factors.ConclusionA formal early stage risk management practice provides early warning related to the problems that exists in a project, and it contributes to the overall project success. It is not necessary to always consider budget and schedule constraints as top priority. There exist issues such as requirements, change management, and user satisfaction which can influence these constraints.     

软件分布式开发中协同工作支持框架的设计与实现

为了有效地支持软件分布式开发,提高软件协同开发环境的易用性和有效性,从协同理论和应用工具两方面入手,在集成了多种协同应用软件的同时,融入了对参与者的形式描述,提高了开发环境的智能性和可定制性,进而提高了协同开发的质量和效率。     

Software quality practices — an empirical study

Concern about the quality of software is widespread. Reliable data about current practice are hard to get as no one likes to admit that they are producing poor software. In a recent survey, Wilson has taken an approach to obtaining data about the practice of software quality assurance among companies in Australia. The same technique has been used here to investigate practice among companies in Europe and America. The survey ams to investigate quality systems used by the organizations, and the application of these systems by software fevelopers. In this paper they are compared with the Australian experience and the results of the survey shown. The company's demographic data and overall response pattern from this survey are compared with Wilson's. Patterns in software quality assurance programs of organizations are suggested by comparing the management's perspective with that of the developers. The most popular software development techniques identified by the developers are prioritized in the order of their popularity by using a weighting scheme and their implications are discussed.     

Effort, co-operation and co-ordination in an open source software project: GNOME

Abstract This paper presents results from research into open source projects from a software engineering perspective. The research methodology employed relies on public data retrieved from the CVS repository of the GNOME project and relevant discussion groups. This methodology is described, and results concerning the special characteristics of open source software development are given. These data are used for a first approach to estimating the total effort to be expended.     

An empirical analysis of the impact of software development problem factors on software maintainability

Many problem factors in the software development phase affect the maintainability of the delivered software systems. Therefore, understanding software development problem factors can help in not only reducing the incidence of project failure but can also ensure software maintainability. This study focuses on those software development problem factors which may possibly affect software maintainability. Twenty-five problem factors were classified into five dimensions; a questionnaire was designed and 137 software projects were surveyed. A K-means cluster analysis was performed to classify the projects into three groups of low, medium and high maintainability projects. For projects which had a higher level of severity of problem factors, the influence on software maintainability becomes more obvious. The influence of software process improvement (SPI) on project problems and the associated software maintainability was also examined in this study. Results suggest that SPI can help reduce the level of severity of the documentation quality and process management problems, and is only likely to enhance software maintainability to a medium level. Finally, the top 10 list of higher-severity software development problem factors was identified, and implications were discussed.     

Handling class imbalance problem in software maintainability prediction: an empirical investigation

As the complexity of software systems is increasing; software maintenance is becoming a challenge for software practitioners. The prediction of classes that require high maintainability effort is of utmost necessity to develop cost-effective and high-quality software. In research of software engineering predictive modeling, various software maintainability prediction (SMP) models are evolved to forecast maintainability. To develop a maintainability prediction model, software practitioners may come across situations in which classes or modules requiring high maintainability effort are far less than those requiring low maintainability effort. This condition gives rise to a class imbalance problem (CIP). In this situation, the minority classes’ prediction, i.e., the classes demanding high maintainability effort, is a challenge. Therefore, in this direction, this study investigates three techniques for handling the CIP on ten open-source software to predict software maintainability. This empirical investigation supports the use of resampling with replacement technique (RR) for treating CIP and develop useful models for SMP.     

Evaluating the usage of fault localization in automated program repair: an empirical study

Fault localization techniques are originally proposed to assist in manual debugging by generally producing a rank list of suspicious locations.With the increasing popularity of automated program repair,the fault localization techniques have been introduced to effectively reduce the search space of automated program repair.Unlike developers who mainly focus on the rank information,current automated program repair has two strategies to use the fault localization information:suspiciousness-first algorithm(SFA)based on the suspiciousness accuracy and rank-first algorithm(RFA)relying on the rank accuracy.However,despite the fact that the two different usages are widely adopted by current automated program repair and may result in different repair results,little is known about the impacts of the two strategies on automated program repair.In this paper we empirically compare the performance of SFA and RFA in the context of automated program repair.Specifically,we implement the two strategies and six well-studied fault localization techniques into four state-of-the-art automated program repair tools,and then use these tools to perform repair experiments on 60 real-world bugs from Defects4J.Our study presents a number of interesting findings:RFA outperforms SFA in 70.02%of cases when measured by the number of candidate patches generated before a valid patch is found(NCP),while SFA performs better in parallel repair and patch diversity;the performance of SFA can be improved by increasing the suspiciousness accuracy of fault localization techniques;finally,we use SimFix that deploys SFA to successfully repair four extra Defects4J bugs which cannot be repaired by SimFix originally using RFA.These observations provide a new perspective for future research on the usage and improvement of fault localization in automated program repair.     

Determining factors that affect long-term evolution in scientific application software

One of the characteristics of scientific application software is its long lifetime of active maintenance. There has been little software engineering research into the development characteristics of scientific software and into the factors that support its successful long evolution. The research described in this paper introduces a novel model to examine the nature of change that influenced an example of industrial scientific software over its lifetime. The research uses the model to provide an objective analysis of factors that contributed to long-term evolution of the software system. Conclusions suggest that the architectural design of the software and the characteristics of the software development group played a major role in the successful evolution of the software. The novel model of change and the research method developed for this study are independent of the type of software under study.     

Trace anomalies as precursors of field failures: an empirical study

Reproducing and learning from failures in deployed software is costly and difficult. Those activities can be facilitated, however, if the circumstances leading to a failure can be recognized and properly captured. To anticipate failures we propose to monitor system field behavior for simple trace instances that deviate from a baseline behavior experienced in-house. In this work, we empirically investigate the effectiveness of various simple anomaly detection schemes to identify the conditions that precede failures in deployed software. The results of our experiment provide a preliminary assessment of these schemes, and expose the tradeoffs between different anomaly detection algorithms applied to several types of observable attributes under varying levels of in-house testing.

Traditional, iterative, and component-based development: A social analysis of software development paradigms

Information systems have always been developed through social processes, wherein actors playing a variety of specialized roles interact to produce new business applications of information technology. As systems development practices continue to evolve, an ongoing assessment of their social implications is required. This paper develops a framework for understanding the potential social implications of an emerging, component-based development paradigm. Like two alternative paradigms for systems development, the traditional life-cycle and the iterative-incremental paradigms, the new component-based paradigm requires that certain generic roles be performed to build a desired application. For each paradigm, we identify the actors who play different roles, specify the nature of their interdependence, and indicate the requirements for managing conflicts constructively. The framework may guide research into the social dynamics of system development and serve as a tentative guide to the management of information systems development.     

基于经验模态分解的混合软件可靠性预测模型

基于经验模态分解结合支持向量回归算法与灰色系统理论提出一种混合软件可靠性预测模型,通过对原始软件失效数据使用经验模态分解方法进行预处理,将失效数据分解得到不同频段的本征模态分量和剩余分量,用支持向量回归算法对本征模态分量进行预测,用灰色系统模型GM（1,1）对剩余分量进行预测,然后将预测结果进行重构,得到最终软件可靠性预测值。为了验证所提混合预测模型的有效性,利用两组真实软件失效数据,与SVR可靠性预测模型和GM（1,1）可靠性预测模型进行实验对比分析,实验结果表明,所提混合预测模型较这两种可靠性预测模型具有更精确的预测精度。     

Applying Gaia and AUML for the development of multiagent‐based control software for flexible manufacturing systems: addressing methodological and implementation issues

In this article, we present the development of a simple multiagent‐based system for the control of a flexible manufacturing system. We followed the stages of a methodology specially conceived for the development of agent‐based system, which is an integration of the classical methodology for agent‐oriented analysis and design Gaia, and AUML (Agent‐Unified Modeling Language). We adopted as study case the CIMUBB Laboratory at the University of Bio‐Bio, which has a flexible manufacturing system including three flexible manufacturing cells interconnected by a conveyor belt. In the analysis stage, we identified roles involved, and we design models representing roles and protocols. In the design stage, we applied Gaia agent, services, and acquaintance models from Gaia, and we complemented with AUML as the adopted methodology suggests. With the developed models, we constructed a fully functional system where each agent was built as an independent process tree. Agents communicate by passing messages through the Ethernet network with socket interfaces. Various tests executed in our laboratory scale manufacturing system show the effectiveness of our implementation. Copyright © 2015 John Wiley & Sons, Ltd.     

Agile requirements engineering practices and challenges: an empirical study

This paper describes empirical research into agile requirements engineering (RE) practices. Based on an analysis of data collected in 16 US software development organizations, we identify six agile practices. We also identify seven challenges that are created by the use of these practices. We further analyse how this collection of practices helps mitigate some, while exacerbating other risks in RE. We provide a framework for evaluating the impact and appropriateness of agile RE practices by relating them to RE risks. Two risks that are intractable by agile RE practices emerge from the analysis. First, problems with customer inability and a lack of concurrence among customers significantly impact agile development. Second, risks associated with the neglecting non‐functional requirements such as security and scalability are a serious concern. Developers should carefully evaluate the risk factors in their project environment to understand whether the benefits of agile RE practices outweigh the costs imposed by the challenges.     

Achieving offshore software development success: An empirical analysis of risk mitigation through relational norms

Behavioral risks such as shirking and misappropriation of information assets are more prominent in offshore software development context and could adversely affect offshore outsourcing success. This paper studies the moderating effects of different relational norms on the link between behavioral risks and offshore software development success. We focused on three major modes of relational norms: norm of flexibility, norm of solidarity and norm of information exchange. Using PLS path modeling to test a sample of 40 US corporations engaged in offshore software development, we found that the norms of solidarity and flexibility reduced the negative effects shirking risk on offshore software development success. Our results suggest that client firms shall benefit by forming the right mode of relational norms to achieve offshore success.