Procedural coordination and offshored software tasks: Lessons from two case studies

This paper presents two case studies of offshored software tasks. The success of such tasks is critically dependent on managing an inherent interdependence between onshore and offshore teams. In one case study, both teams belong to the vendor organization, while in the other they are affiliated respectively with client and vendor. It is shown that that interdependence is best addressed through procedural coordination, which entails two complementary strategies. The first consists of carefully specifying and partitioning tasks, and the second of implementing integration mechanisms to bridge communication gaps. Despite contextual differences, the two case studies offer common lessons.     

The methodological soundness of requirements engineering papers: a conceptual framework and two case studies

This paper was triggered by concerns about the methodological soundness of many RE papers. We present a conceptual framework that distinguishes design papers from research papers, and show that in this framework, what is called a research paper in RE is often a design paper. We then present and motivate two lists of evaluation criteria, one for research papers and one for design papers. We apply both of these lists to two samples drawn from the set of all submissions to the RE’03 conference. Analysis of these two samples shows that most submissions of the RE’03 conference are design papers, not research papers, and that most design papers present a solution to a problem but neither validate this solution nor investigate the problems that can be solved by this solution. We conclude with a discussion of the soundness of our results and of the possible impact on RE research and practice.     

Using aspects for testing of embedded software: experiences from two industrial case studies

Aspect-oriented software testing is emerging as an important alternative to conventional procedural and object-oriented testing techniques. This paper reports experiences from two case studies where aspects were used for the testing of embedded software in the context of an industrial application. In the first study, we used code-level aspects for testing non-functional properties. The methodology we used for deriving test aspect code was based on translating high-level requirements into test objectives, which were then implemented using test aspects in AspectC++. In the second study, we used high-level visual scenario-based models for the test specification, test generation, and aspect-based test execution. To specify scenario-based tests, we used a UML2-compliant variant of live sequence charts. To automatically generate test code from the models, a modified version of the S2A Compiler, outputting AspectC++ code, was used. Finally, to examine the results of the tests, we used the Tracer, a prototype tool for model-based trace visualization and exploration. The results of the two case studies show that aspects offer benefits over conventional techniques in the context of testing embedded software; these benefits are discussed in detail. Finally, towards the end of the paper, we also discuss the lessons learned, including the technological and other barriers to the future successful use of aspects in the testing of embedded software in industry.     

Towards an understanding of the consumer acceptance of mobile wallet

This study seeks to validate a comprehensive model of consumer acceptance in the context of mobile payment. It uses the unified theory of acceptance and use of technology (UTAUT) model with constructs of security, trust, social influence, and self-efficacy. Structural equation modeling is used to construct a predictive model of attitudes toward the mobile wallet. Individuals’ responses to questions about attitude and intention to adopt/use a mobile wallet were collected and analyzed with various factors modified from UTAUT. While the model confirms the classical role of technology acceptance factors (i.e., perceived usefulness and ease of use are key antecedents to users’ attitude), the results also show that users’ attitudes and intentions are influenced by perceived security and trust. In the extended model, the moderating effects of demographics on the relations among the variables were found to be significant. The proposed model brings together extant research on mobile payment and provides an important cluster of antecedents to eventual technology acceptance via constructs of behavioral intention to use and actual system usage.     

Towards an understanding of assimilation in virtual worlds: the 3C approach

Virtual worlds are increasing in importance as more multi-national firms are investing heavily in these emerging communities. Although much excitement has surrounded the idea of virtual worlds, a gap exists between those who register and those who engage in virtual worlds. Our analysis of the gap between those who merely register to join a virtual world and those who ultimately engage the community on a regular basis derives from a lack of assimilation. We present the 3C approach, a high-level theoretical framework delineating the relationship between three classes of factors (namely the technology class of factors; the community class of factors; and the user class of factors) that we posit explain virtual world assimilation and employ theories to represent these classes of factors and the interaction between them. After discussing and integrating these three classes of factors, we test our model through a study of 223 new users of Second Life. The results provide empirical support for the 3C framework; specifically, our analysis indicates that the technology and community classes of factors in exert a direct influence upon a user's attitude towards the virtual world, and this relationship is moderated by the user class of factors.     

Understanding the effects of requirements volatility in software engineering by using analytical modeling and software process simulation

This paper introduces an executable system dynamics simulation model developed to help project managers comprehend the complex impacts related to requirements volatility on a software development project. The simulator extends previous research and adds research results from an empirical survey, including over 50 new parameters derived from the associated survey data, to a base model. The paper discusses detailed results from two cases that show significant cost, schedule, and quality impacts as a result of requirements volatility. The simulator can be used as an effective tool to demonstrate the complex set of factor relationships and effects related to requirements volatility.     

The influencing causes of software unavailability: A case study from industry

Software unavailability can lead to disastrous consequences ranging from delays and cancellation to a loss of millions of dollars of technology. However, research on the causes that can make systems unavailable is still little. The aim of this paper is to investigate such causes in an industrial context using 2 qualitative approaches ((a) interview and (b) retrospective analysis) using archival data and records from a student information system. As a result, connectivity, human, hardware, storage, and software were found to be the important categories of causes for the unavailability. Besides, the critical lessons to be learned that relate to activities of software management and software business are also discussed. This includes vendor support, systems documentation, health check process, licensing, and software updating or upgrading. To strengthen the claim that our findings are promising, we compare our main findings with those of a previous study. This study can generally assist software engineering people including engineers, developers, project managers, vendors. Additionally, this paper dis cusses the threats to the study's validity and suggests open problems for future research.     

基于QFD和DSM的软件需求变更影响分析方法与应用

软件需求变更是导致软件项目失败的主要因素。之前学者们在分析软件体系结构的变更风险时,体系结构间依赖值的获取主要是依靠经验预估,而不是基于模块的进一步划分和相关耦合参数的关联推导。针对这一问题,提出利用DSM和QFD模型对组件进一步细划分成粒度更小的关键设计参数(类或对象),分析参数间的依赖程度,推导出模块间的关联度,接着对模块开发顺序进行重组,从而在一定程度上控制需求变更风险。最后,通过将某公司集装箱管理系统进行模块切分和重组对所提方法的可行性和正确性进行了验证。     

Towards understanding the effects of individual gamification elements on intrinsic motivation and performance

Research on the effectiveness of gamification has proliferated over the last few years, but the underlying motivational mechanisms have only recently become object of empirical research. It has been suggested that when perceived as informational, gamification elements, such as points, levels and leaderboards, may afford feelings of competence and hence enhance intrinsic motivation and promote performance gains. We conducted a 2 × 4 online experiment that systematically examined how points, leaderboards and levels, as well as participants' goal causality orientation influence intrinsic motivation, competence and performance (tag quantity and quality) in an image annotation task. Compared to a control condition, game elements did not significantly affect competence or intrinsic motivation, irrespective of participants' causality orientation. However, participants' performance did not mirror their intrinsic motivation, as points, and especially levels and leaderboard led to a significantly higher amount of tags generated compared to the control group. These findings suggest that in this particular study context, points, levels and leaderboards functioned as extrinsic incentives, effective only for promoting performance quantity.     

Towards understanding the underlying structure of motivational factors for software engineers to guide the definition of motivational programs

Aim

In this article, factors influencing the motivation of software engineers is studied with the goal of guiding the definition of motivational programs.

Method

Using a set of 20 motivational factors compiled in a systematic literature review and a general theory of motivation, a survey questionnaire was created to evaluate the influence of these factors on individual motivation. Then, the questionnaire was applied on a semi-random sample of 176 software engineers from 20 software companies located in Recife-PE, Brazil.

Results

The survey results show the actual level of motivation for each motivator in the target population. Using principal component analysis on the values of all motivators, a five factor structure was identified and used to propose a guideline for the creation of motivational programs for software engineers.

Conclusions

The five factor structure provides an intuitive categorization for the set of variables and can be used to explain other motivational models presented in the literature. This contributes to a better understanding of motivation in software engineering.     

Towards an atomistic understanding of solid friction by computer simulations

Friction between two solid bodies in sliding motion takes place on a large spectrum of length and time scales: From the nanometer/second scale in an atomic force microscope up to the extremely macroscopic scales of tectonic motion. Despite our familiarity with friction, fundamental questions about its atomistic origins remain unanswered. Phenomenological laws that describe the friction in many systems were published more than 300 years ago by Amontons: The frictional force is proportional to the applied load and independent of the apparent area of contact. The atomistic origins of this simple law is still controversial. Many explanations, which seemed to be well-established until recently, have been called into question by new experimental results. Computer simulations have also revealed flaws in previous theoretical approaches and led to new insights into the atomistic processes responsible for friction. In this paper, selected computer simulation studies of friction will be discussed. Special attention will be given to how it is possible to gain insight into tribological processes that take place on macroscopic time scales with the help of atomistic computer simulations which are typically constrained to the nanometer and nanosecond regime.     

Developing the requirements discipline: software vs. systems

The software engineering and systems engineering communities are establishing methods for capturing, specifying, and managing requirements. The cultural differences exist between the two. Requirements work is too important to be pioneered by a mainstream software-centric or -ignorant viewpoint. Each community must continue to learn from the other for our understanding of the requirements engineering discipline to continue to grow.     

Examination of the software architecture change characterization scheme using three empirical studies

Software maintenance is one of the most crucial aspects of software development. Software engineering researchers must develop practical solutions to handle the challenges presented in maintaining mature software systems. Research that addresses practical means of mitigating the risks involved when changing software, reducing the complexity of mature software systems, and eliminating the introduction of preventable bugs is paramount to today’s software engineering discipline. The Software Architecture Change Characterization Scheme (SACCS) provides software maintainers with a systematic approach to analyzing and characterizing the impact of a change prior to its implementation. SACCS was designed to help novice developers understand change requests, facilitate discussion among developers, and provide a higher-quality change compared with an ad hoc approach. In addition, this paper describes three controlled experiments designed to assess the viability of using SACCS and its ability to fulfill its goals. The successive studies build upon each other to enable progressive insights into the viability of the scheme. The results indicate that SACCS: 1) provides insight into the difficulty of a change request by assisting novice developers to consider various aspects of the request’s potential to impact the system, 2) helps to facilitate discussion among developers by providing a common tool for change assessment, and 3) is a useful tool for supporting change implementation. The three experiments provide insight into the usefulness of SACCS, motivate additional research questions, and serve as a baseline for moving forward with research and further development of the approach.     

Understanding cost drivers of software evolution: a quantitative and qualitative investigation of change effort in two evolving software systems

Making changes to software systems can prove costly and it remains a challenge to understand the factors that affect the costs of software evolution. This study sought to identify such factors by investigating the effort expended by developers to perform 336 change tasks in two different software organizations. We quantitatively analyzed data from version control systems and change trackers to identify factors that correlated with change effort. In-depth interviews with the developers about a subset of the change tasks further refined the analysis. Two central quantitative results found that dispersion of changed code and volatility of the requirements for the change task correlated with change effort. The analysis of the qualitative interviews pointed to two important, underlying cost drivers: Difficulties in comprehending dispersed code and difficulties in anticipating side effects of changes. This study demonstrates a novel method for combining qualitative and quantitative analysis to assess cost drivers of software evolution. Given our findings, we propose improvements to practices and development tools to manage and reduce the costs.     

Deriving thresholds of software metrics to predict faults on open source software: Replicated case studies

Object-oriented metrics aim to exhibit the quality of source code and give insight to it quantitatively. Each metric assesses the code from a different aspect. There is a relationship between the quality level and the risk level of source code. The objective of this paper is to empirically examine whether or not there are effective threshold values for source code metrics. It is targeted to derive generalized thresholds that can be used in different software systems. The relationship between metric thresholds and fault-proneness was investigated empirically in this study by using ten open-source software systems. Three types of fault-proneness were defined for the software modules: non-fault-prone, more-than-one-fault-prone, and more-than-three-fault-prone. Two independent case studies were carried out to derive two different threshold values. A single set was created by merging ten datasets and was used as training data by the model. The learner model was created using logistic regression and the Bender method. Results revealed that some metrics have threshold effects. Seven metrics gave satisfactory results in the first case study. In the second case study, eleven metrics gave satisfactory results. This study makes contributions primarily for use by software developers and testers. Software developers can see classes or modules that require revising; this, consequently, contributes to an increment in quality for these modules and a decrement in their risk level. Testers can identify modules that need more testing effort and can prioritize modules according to their risk levels.     

Towards an ensemble based system for predicting the number of software faults

Software fault prediction using different techniques has been done by various researchers previously. It is observed that the performance of these techniques varied from dataset to dataset, which make them inconsistent for fault prediction in the unknown software project. On the other hand, use of ensemble method for software fault prediction can be very effective, as it takes the advantage of different techniques for the given dataset to come up with better prediction results compared to individual technique. Many works are available on binary class software fault prediction (faulty or non-faulty prediction) using ensemble methods, but the use of ensemble methods for the prediction of number of faults has not been explored so far. The objective of this work is to present a system using the ensemble of various learning techniques for predicting the number of faults in given software modules. We present a heterogeneous ensemble method for the prediction of number of faults and use a linear combination rule and a non-linear combination rule based approaches for the ensemble. The study is designed and conducted for different software fault datasets accumulated from the publicly available data repositories. The results indicate that the presented system predicted number of faults with higher accuracy. The results are consistent across all the datasets. We also use prediction at level l (Pred(l)), and measure of completeness to evaluate the results. Pred(l) shows the number of modules in a dataset for which average relative error value is less than or equal to a threshold value l. The results of prediction at level l analysis and measure of completeness analysis have also confirmed the effectiveness of the presented system for the prediction of number of faults. Compared to the single fault prediction technique, ensemble methods produced improved performance for the prediction of number of software faults. Main impact of this work is to allow better utilization of testing resources helping in early and quick identification of most of the faults in the software system.