Exploring a Bayesian and linear approach to requirements traceability

Context

For large software projects it is important to have some traceability between artefacts from different phases (e.g.requirements, designs, code), and between artefacts and the involved developers. However, if the capturing of traceability information during the project is felt as laborious to developers, they will often be sloppy in registering the relevant traceability links so that the information is incomplete. This makes automated tool-based collection of traceability links a tempting alternative, but this has the opposite challenge of generating too many potential trace relationships, not all of which are equally relevant.

Objective

This paper evaluates how to rank such auto-generated trace relationships.

Method

We present two approaches for such a ranking: a Bayesian technique and a linear inference technique. Both techniques depend on the interaction event trails left behind by collaborating developers while working within a development tool.

Results

The outcome of a preliminary study suggest the advantage of the linear approach, we also explore the challenges and potentials of the two techniques.

Conclusion

The advantage of the two techniques is that they can be used to provide traceability insights that are contextual and would have been much more difficult to capture manually. We also present some key lessons learnt during this research.     

A methodology to assess the impact of design patterns on software quality

Context

Software quality is considered to be one of the most important concerns of software production teams. Additionally, design patterns are documented solutions to common design problems that are expected to enhance software quality. Until now, the results on the effect of design patterns on software quality are controversial.

Aims

This study aims to propose a methodology for comparing design patterns to alternative designs with an analytical method. Additionally, the study illustrates the methodology by comparing three design patterns with two alternative solutions, with respect to several quality attributes.

Method

The paper introduces a theoretical/analytical methodology to compare sets of “canonical” solutions to design problems. The study is theoretical in the sense that the solutions are disconnected from real systems, even though they stem from concrete problems. The study is analytical in the sense that the solutions are compared based on their possible numbers of classes and on equations representing the values of the various structural quality attributes in function of these numbers of classes. The exploratory designs have been produced by studying the literature, by investigating open-source projects and by using design patterns. In addition to that, we have created a tool that helps practitioners in choosing the optimal design solution, according to their special needs.

Results

The results of our research suggest that the decision of applying a design pattern is usually a trade-off, because patterns are not universally good or bad. Patterns typically improve certain aspects of software quality, while they might weaken some other.

Conclusions

Concluding the proposed methodology is applicable for comparing patterns and alternative designs, and highlights existing threshold that when surpassed the design pattern is getting more or less beneficial than the alternative design. More specifically, the identification of such thresholds can become very useful for decision making during system design and refactoring.     

Is software “green”? Application development environments and energy efficiency in open source applications

Context

The energy efficiency of IT systems, also referred to as Green IT, is attracting more and more attention. While several researchers have focused on the energy efficiency of hardware and embedded systems, the role of application software in IT energy consumption still needs investigation.

Objective

This paper aims to define a methodology for measuring software energy efficiency and to understand the consequences of abstraction layers and application development environments for the energy efficiency of software applications.

Method

We first develop a measure of energy efficiency that is appropriate for software applications. We then examine how the use of application development environments relates to this measure of energy efficiency for a sample of 63 open source software applications.

Results

Our findings indicate that a greater use of application development environments - specifically, frameworks and external libraries - is more detrimental in terms of energy efficiency for larger applications than for smaller applications. We also find that different functional application types have distinctly different levels of energy efficiency, with text and image editing and gaming applications being the most energy inefficient due to their intense use of the processor.

Conclusion

We conclude that different designs can have a significant impact on the energy efficiency of software applications. We have related the use of software application development environments to software energy efficiency suggesting that there may be a trade-off between development efficiency and energy efficiency. We propose new research to further investigate this topic.     

Reliability analysis and optimal version-updating for open source software

Context

Although reliability is a major concern of most open source projects, research on this problem has attracted attention only recently. In addition, the optimal version-dating for open source software considering its special properties is not yet discussed.

Objective

In this paper, the reliability analysis and optimal version-updating for open source software are studied.

Method

A modified non-homogeneous Poisson process model is developed for open source software reliability modeling and analysis. Based on this model, optimal version-updating for open source software is investigated as well. In the decision process, the rapid release strategy and the level of reliability are the two most important factors. However, they are essentially contradicting with each other. In order to consider these two conflicting factors simultaneously, a new decision model based on multi-attribute utility theory is proposed.

Results

Our models are tested on the real world data sets from two famous open source projects: Apache and GNOME. It is found that traditional software reliability models provide overestimations of the reliability of open source software. In addition, the proposed decision model can help management to make a rational decision on the optimal version-updating for open source software.

Conclusion

Empirical results reveal that the proposed model for open source software reliability can describe the failure process more accurately. Furthermore, it can be seen that the proposed decision model can assist management to appropriately determine the optimal version-update time for open source software.     

Reconciling software development models: A quasi-systematic review

Purpose

The purpose of this paper is to characterize reconciliation among the plan-driven, agile, and free/open source software models of software development.

Design/methodology/approach

An automated quasi-systematic review identified 42 papers, which were then analyzed.

Findings

The main findings are: there exist distinct - organization, group and process - levels of reconciliation; few studies deal with reconciliation among the three models of development; a significant amount of work addresses reconciliation between plan-driven and agile development; several large organizations (such as Microsoft, Motorola, and Philips) are interested in trying to combine these models; and reconciliation among software development models is still an open issue, since it is an emerging area and research on most proposals is at an early stage.

Research limitations

Automated searches may not capture relevant papers in publications that are not indexed. Other data sources not amenable to execution of the protocol were not used. Data extraction was performed by only one researcher, which may increase the risk of threats to internal validity.

Implications

This characterization is important for practitioners wanting to be current with the state of research. This review will also assist the scientific community working with software development processes to build a common understanding of the challenges that must be faced, and to identify areas where research is lacking. Finally, the results will be useful to software industry that is calling for solutions in this area.

Originality/value

There is no other systematic review on this subject, and reconciliation among software development models is an emerging area. This study helps to identify and consolidate the work done so far and to guide future research. The conclusions are an important step towards expanding the body of knowledge in the field.     

Assessing PSP effect in training disciplined software development: A Plan-Track-Review model

Context

In training disciplined software development, the PSP is said to result in such effect as increased estimation accuracy, better software quality, earlier defect detection, and improved productivity. But a systematic mechanism that can be easily adopted to assess and interpret PSP effect is scarce within the existing literature.

Objective

The purpose of this study is to explore the possibility of devising a feasible assessment model that ties up critical software engineering values with the pertinent PSP metrics.

Method

A systematic review of the literature was conducted to establish such an assessment model (we called a Plan-Track-Review model). Both mean and median approaches along with a set of simplified procedures were used to assess the commonly accepted PSP training effects. A set of statistical analyses further followed to increase understanding of the relationships among the PSP metrics and to help interpret the application results.

Results

Based on the results of this study, PSP training effect on the controllability, manageability, and reliability of a software engineer is quite positive and largely consistent with the literature. However, its effect on one’s predictability on project in general (and on project size in particular) is not implied as said in the literature. As for one’s overall project efficiency, our results show a moderate improvement. Our initial finding also suggests that a prior stage PSP effect could have an impact on later stage training outcomes.

Conclusion

It is concluded that this Plan-Track-Review model with the associated framework can be used to assess PSP effect regarding a disciplined software development. The generated summary report serves to provide useful feedback for both PSP instructors and students based on internal as well as external standards.     

Pattern-based framework for modularized software development and evolution robustness

Context

Software development is now facing much more challenges than ever before due to the intrinsic high complexity and the increasing demands of the quick-service-ready paradigm.

Objective

As the developers are now called for more quality software systems from the industries, there is insufficient guidance from the methodologies and standards of software engineering that can provide assistance to the rapid development of qualified business software.

Method

In this work, we discuss the advantages of the pattern-based software development. We verify the benefits using a pattern-based software framework called OS2F, and a corresponding system design architecture that is intended for the rapid development of web applications.

Results

The objective of the framework/architecture is that, through software patterns, developers should be able to separate the work of system development from the business rules so as to reduce the problems caused by a developer’s lack of business experiences.

Conclusion

Through a suitable pattern-based software framework, the quality of the product can thus be enhanced, software development time and cost decreased, and software evolution robustness improved.     

Code churn estimation using organisational and code metrics: An experimental comparison

Context

Source code revision control systems contain vast amounts of data that can be exploited for various purposes. For example, the data can be used as a base for estimating future code maintenance effort in order to plan software maintenance activities. Previous work has extensively studied the use of metrics extracted from object-oriented source code to estimate future coding effort. In comparison, the use of other types of metrics for this purpose has received significantly less attention.

Objective

This paper applies machine learning techniques to unveil predictors of yearly cumulative code churn of software projects on the basis of metrics extracted from revision control systems.

Method

The study is based on a collection of object-oriented code metrics, XML code metrics, and organisational metrics. Several models are constructed with different subsets of these metrics. The predictive power of these models is analysed based on a dataset extracted from eight open-source projects.

Results

The study shows that a code churn estimation model built purely with organisational metrics is superior to one built purely with code metrics. However, a combined model provides the highest predictive power.

Conclusion

The results suggest that code metrics in general, and XML metrics in particular, are complementary to organisational metrics for the purpose of estimating code churn.     

Conceptual scheduling model and optimized release scheduling for agile environments

Context

Release scheduling deals with the selection and assignment of deliverable features to a sequence of consecutive product deliveries while several constraints are fulfilled. Although agile software development represents a major approach to software engineering, there is no well-established conceptual definition and sound methodological support of agile release scheduling.

Objective

To propose a solution, we present, (1) a conceptual model for agile scheduling, and (2) a novel multiple knapsack-based optimization model with (3) a branch-and-bound optimization algorithm for agile release scheduling.

Method

To evaluate our model simulations were carried out seven real life and several generated data sets.

Results

The developed algorithm strives to prevent resource overload and resource underload, and mitigates risks of delivery slippage.

Conclusion

The results of the experiment suggest that this approach can provide optimized semi-automatic release schedule generations and more informed and established decisions utilizing what-if-analysis on the fly to tailor the best schedule for the specific project context.     

Design guidelines for software processes knowledge repository development

Context

Staff turnover in organizations is an important issue that should be taken into account mainly for two reasons:

1.

Employees carry an organization’s knowledge in their heads and take it with them wherever they go

2.

Knowledge accessibility is limited to the amount of knowledge employees want to share

Objective

The aim of this work is to provide a set of guidelines to develop knowledge-based Process Asset Libraries (PAL) to store software engineering best practices, implemented as a wiki.

Method

Fieldwork was carried out in a 2-year training course in agile development. This was validated in two phases (with and without PAL), which were subdivided into two stages: Training and Project.

Results

The study demonstrates that, on the one hand, the learning process can be facilitated using PAL to transfer software process knowledge, and on the other hand, products were developed by junior software engineers with a greater degree of independence.

Conclusion

PAL, as a knowledge repository, helps software engineers to learn about development processes and improves the use of agile processes.     

Migration of information systems in the Italian industry: A state of the practice survey

Context

Software migration—and in particular migration towards the Web and towards distributed architectures—is a challenging and complex activity, and has been particularly relevant in recent years, due to the large number of migration projects the industry had to face off because of the increasing pervasiveness of the Web and of mobile devices.

Objective

This paper reports a survey aimed at identifying the state-of-the-practice of the Italian industry for what concerns the previous experiences in software migration projects—specifically concerning information systems—the adopted tools and the emerging needs and problems.

Method

The study has been carried out among 59 Italian Information Technology companies, and for each company a representative person had to answer an on-line questionnaire concerning migration experiences, pieces of technology involved in migration projects, adopted tools, and problems occurred during the project.

Results

Indicate that migration—especially towards the Web—is highly relevant for Italian IT companies, and that companies tend to increasingly adopt free and open source solutions rather than commercial ones. Results also indicate that the adoption of specific tools for migration is still very limited, either because of the lack of skills and knowledge, or due to the lack of mature and adequate options.

Conclusions

Findings from this survey suggest the need for further technology transfer between academia and industry for the purpose of favoring the adoption of software migration techniques and tools.     

Evaluating software engineering techniques for developing complex systems with multiagent approaches

Context

Multiagent systems (MAS) allow complex systems to be developed in which autonomous and heterogeneous entities interact. Currently, there are a great number of methods and frameworks for developing MAS. The selection of one or another development environment is a crucial part of the development process. Therefore, the evaluation and comparison of MAS software engineering techniques is necessary in order to make the selection of the development environment easier.

Objective

The main goal of this paper is to define an evaluation framework that will help in facilitating, standardizing, and simplifying the evaluation, analysis, and comparison of MAS development environments. Moreover, the final objective of the proposed tool is to provide a repository of the most commonly used MAS software engineering methods and tools.

Method

The proposed framework analyzes methods and tools through a set of criteria that are related to both system engineering dimensions and MAS features. Also, the support for developing organizational and service-oriented MAS is studied. This framework is implemented as an online application to improve its accessibility.

Results

In this paper, we present Masev, which is an evaluation framework for MAS software engineering. It allows MAS methods, techniques and environments to be analyzed and compared. A case study of the analysis of four methodologies is presented.

Conclusion

It is concluded that Masev simplifies the evaluation and comparison task and summarizes the most important issues for developing MAS, organizational MAS, and service-oriented MAS. Therefore, it could help developers to select the most appropriate MAS method and tools for developing a specific system, and it could be used for MAS software engineering developers to detect and deficiencies in their methods and tools. Also, developers of new tools can understand this application as a way to publish their tools and demonstrate what their contributions are to the state of the art.     

Drivers of agile software development use: Dialectic interplay between benefits and hindrances

Context

Agile software development with its emphasis on producing working code through frequent releases, extensive client interactions and iterative development has emerged as an alternative to traditional plan-based software development methods. While a number of case studies have provided insights into the use and consequences of agile, few empirical studies have examined the factors that drive the adoption and use of agile.

Objective

We draw on intention-based theories and a dialectic perspective to identify factors driving the use of agile practices among adopters of this software development methodology.

Method

Data for the study was gathered through an anonymous online survey of software development professionals. We requested participation from members of a selected list of online discussion groups, and received 98 responses.

Results

Our analyses reveal that subjective norm and training play a significant role in influencing software developers’ use of agile processes and methods, while perceived benefits and perceived limitations are not primary drivers of agile use among adopters. Interestingly, perceived benefit emerges as a significant predictor of agile use only if adopters face hindrances to their agile practices.

Conclusion

We conclude that research in the adoption of software development innovations should examine the effects of both enabling and detracting factors and the interactions between them. Since training, subjective norm, and the interplay between perceived benefits and perceived hindrances appear to be key factors influencing the adoption of agile methods, researchers can focus on how to (a) perform training on agile methods more effectively, (b) facilitate the dialog between developers and managers about perceived benefits and hindrances, and (c) capitalize on subjective norm to publicize the benefits of agile methods within an organization. Further, when managing the transition to new software development methods, we recommend that practitioners adapt their strategies and tactics contingent on the extent of perceived hindrances to the change.     

The agile requirements refinery: Applying SCRUM principles to software product management

Context

Although agile software development methods such as SCRUM and DSDM are gaining popularity, the consequences of applying agile principles to software product management have received little attention until now.

Objective

In this paper, this gap is filled by the introduction of a method for the application of SCRUM principles to software product management.

Method

A case study research approach is employed to describe and evaluate this method.

Results

This has resulted in the ‘agile requirements refinery’, an extension to the SCRUM process that enables product managers to cope with complex requirements in an agile development environment. A case study is presented to illustrate how agile methods can be applied to software product management.

Conclusions

The experiences of the case study company are provided as a set of lessons learned that will help others to apply agile principles to their software product management process.     

A controlled experiment in assessing and estimating software maintenance tasks

Context

Software maintenance is an important software engineering activity that has been reported to account for the majority of the software total cost. Thus, understanding the factors that influence the cost of software maintenance tasks helps maintainers to make informed decisions about their work.

Objective

This paper describes a controlled experiment of student programmers performing maintenance tasks on a C++ program. The objective of the study is to assess the maintenance size, effort, and effort distributions of three different maintenance types and to describe estimation models to predict the programmer’s effort spent on maintenance tasks.

Method

Twenty-three graduate students and a senior majoring in computer science participated in the experiment. Each student was asked to perform maintenance tasks required for one of the three task groups. The impact of different LOC metrics on maintenance effort was also evaluated by fitting the data collected into four estimation models.

Results

The results indicate that corrective maintenance is much less productive than enhancive and reductive maintenance and program comprehension activities require as much as 50% of the total effort in corrective maintenance. Moreover, the best software effort model can estimate the time of 79% of the programmers with the error of or less than 30%.

Conclusion

Our study suggests that the LOC added, modified, and deleted metrics are good predictors for estimating the cost of software maintenance. Effort estimation models for maintenance work may use the LOC added, modified, deleted metrics as the independent parameters instead of the simple sum of the three. Another implication is that reducing business rules of the software requires a sizable proportion of the software maintenance effort. Finally, the differences in effort distribution among the maintenance types suggest that assigning maintenance tasks properly is important to effectively and efficiently utilize human resources.     

Field study on requirements engineering: Investigation of artefacts, project parameters, and execution strategies

Context

Requirements Engineering (RE) is a critical discipline mostly driven by uncertainty, since it is influenced by the customer domain or by the development process model used. Volatile project environments restrict the choice of methods and the decision about which artefacts to produce in RE.

Objective

We aim to investigate RE processes in successful project environments to discover characteristics and strategies that allow us to elaborate RE tailoring approaches in the future.

Method

We perform a field study on a set of projects at one company. First, we investigate by content analysis which RE artefacts were produced in each project and to what extent they were produced. Second, we perform qualitative analysis of semi-structured interviews to discover project parameters that relate to the produced artefacts. Third, we use cluster analysis to infer artefact patterns and probable RE execution strategies, which are the responses to specific project parameters. Fourth, we investigate by statistical tests the effort spent in each strategy in relation to the effort spent in change requests to evaluate the efficiency of execution strategies.

Results

We identified three artefact patterns and corresponding execution strategies. Each strategy covers different project parameters that impact the creation of certain artefacts. The effort analysis shows that the strategies have no significant differences in their effort and efficiency.

Conclusions

In contrast to our initial assumption that an increased effort in requirements engineering lowers the probability of change requests or project failures in general, our results show no statistically significant difference between the efficiency of the strategies. In addition, it turned out that many parameters considered as the main causes for project failures can be successfully handled. Hence, practitioners can apply the artefact patterns and related project parameters to tailor the RE process according to individual project characteristics.     

Resolving unwanted couplings through interactive exploration of co-evolving software entities - An experience report

Context

Frequent changes to groups of software entities belonging to different parts of the system may indicate unwanted couplings between those parts. Visualizations of co-changing software entities have been proposed to help developers identify unwanted couplings. Identifying unwanted couplings, however, is only the first step towards an important goal of a software architect: to improve the decomposition of the software system. An in-depth analysis of co-changing entities is needed to understand the underlying reasons for co-changes, and also determine how to resolve the issues.

Objective

In this paper we discuss how interactive visualizations can support the process of analyzing the identified unwanted couplings.

Method

We applied a tool that interactively visualizes software evolution in 10 working sessions with architects and developers of a large embedded software system having a development history of more than a decade.

Results

The participants of the working sessions were overall very positive about their experiences with the interactive visualizations. In 70% of the cases investigated, a decision could be taken on how to resolve the unwanted couplings.

Conclusion

Our experience suggests that interactive visualization not only helps to identify unwanted couplings but it also helps experts to reason about and resolve them.     

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.     

Analogy-based software effort estimation using Fuzzy numbers

Background

Early stage software effort estimation is a crucial task for project bedding and feasibility studies. Since collected data during the early stages of a software development lifecycle is always imprecise and uncertain, it is very hard to deliver accurate estimates. Analogy-based estimation, which is one of the popular estimation methods, is rarely used during the early stage of a project because of uncertainty associated with attribute measurement and data availability.

Aims

We have integrated analogy-based estimation with Fuzzy numbers in order to improve the performance of software project effort estimation during the early stages of a software development lifecycle, using all available early data. Particularly, this paper proposes a new software project similarity measure and a new adaptation technique based on Fuzzy numbers.

Method

Empirical evaluations with Jack-knifing procedure have been carried out using five benchmark data sets of software projects, namely, ISBSG, Desharnais, Kemerer, Albrecht and COCOMO, and results are reported. The results are compared to those obtained by methods employed in the literature using case-based reasoning and stepwise regression.

Results

In all data sets the empirical evaluations have shown that the proposed similarity measure and adaptation techniques method were able to significantly improve the performance of analogy-based estimation during the early stages of software development. The results have also shown that the proposed method outperforms some well know estimation techniques such as case-based reasoning and stepwise regression.

Conclusions

It is concluded that the proposed estimation model could form a useful approach for early stage estimation especially when data is almost uncertain.