The relationship between organizational culture and the deployment of agile methods

Context

Systems development normally takes place in a specific organizational context, including organizational culture. Previous research has identified organizational culture as a factor that potentially affects the deployment systems development methods.

Objective

The purpose is to analyze the relationship between organizational culture and the post-adoption deployment of agile methods.

Method

This study is a theory development exercise. Based on the Competing Values Model of organizational culture, the paper proposes a number of hypotheses about the relationship between organizational culture and the deployment of agile methods.

Results

Inspired by the agile methods thirteen new hypotheses are introduced and discussed. They have interesting implications, when contrasted with ad hoc development and with traditional systems development methods.

Conclusion

Because of the conceptual richness of organizational culture and the ambiguity of the concept of agility the relationship between organizational culture and the deployment of agile systems development forms a rich and interesting research topic. Recognizing that the Competing Values Model represents just one view of organizational culture, the paper introduces a number of alternative conceptions and identifies several interesting paths for future research into the relationship between organizational culture and agile methods deployment.     

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.     

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.     

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.     

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.     

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.     

Post-agility: What follows a decade of agility?

Context

Agile information systems development (ISD) has received much attention from both the practitioner and researcher community over the last 10-15 years. However, it is still unclear what precisely constitutes agile ISD.

Objective

Based on four empirical studies conducted over a 10-year time period from 1999 to 2008 the objective of this paper is to show how the meaning and practice of agile ISD has evolved over time and on this basis to speculate about what comes next.

Method

Four phases of research has been conducted, using a grounded theory approach. For each research phase qualitative interviews were held in American and/or Danish companies and a grounded theory was inductively discovered by careful data analysis. Subsequently, the four unique theories have been analyzed for common themes, and a global theory was identified across the empirical data.

Results

In 1999 companies were developing software at high-speed in a desperate rush to be first-to-market. In 2001 a new high-speed/quick results development process had become established practice. In 2003 changes in the market created the need for a more balanced view on speed and quality, and in 2008 companies were successfully combining agile and plan-driven approaches to achieve the benefits of both. The studies reveal a two-stage pattern in which dramatic changes in the market causes disruption of established practices and process adaptations followed by consolidation of lessons learnt into a once again stable software development process.

Conclusion

The cyclical history of punctuated process evolution makes it possible to distinguish pre-agility from current practices (agility), and on this basis, to speculate about post-agility: a possible next cycle of software process evolution concerned with proactively pursuing the dual goal of agility and alignment through a diversity of means.     

Beyond the customer: Opening the agile systems development process

Context

A particular strength of agile systems development approaches is that they encourage a move away from ‘introverted’ development, involving the customer in all areas of development, leading to more innovative and hence more valuable information system. However, a move toward open innovation requires a focus that goes beyond a single customer representative, involving a broader range of stakeholders, both inside and outside the organisation in a continuous, systematic way.

Objective

This paper provides an in-depth discussion of the applicability and implications of open innovation in an agile environment.

Method

We draw on two illustrative cases from industry.

Results

We highlight some distinct problems that arose when two project teams tried to combine agile and open innovation principles. For example, openness is often compromised by a perceived competitive element and lack of transparency between business units. In addition, minimal documentation often reduce effective knowledge transfer while the use of short iterations, stand-up meetings and presence of on-site customer reduce the amount of time for sharing ideas outside the team.

Conclusion

A clear understanding of the inter- and intra-organisational applicability and implications of open innovation in agile systems development is required to address key challenges for research and practice.     

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.     

The impact of inadequate customer collaboration on self-organizing Agile teams

Context

Customer collaboration is a vital feature of Agile software development.

Objective

This article addresses the importance of adequate customer involvement on Agile projects, and the impact of different levels of customer involvement on real-life Agile projects.

Method

We conducted a Grounded Theory study involving 30 Agile practitioners from 16 software development organizations in New Zealand and India, over a period of 3 years.

Results

We discovered that Lack of Customer Involvement was one of the biggest challenges faced by Agile teams. Customers were not as involved on these Agile projects as Agile methods demand. We describe the causes of inadequate customer collaboration, its adverse consequences on self-organizing Agile teams, and Agile Undercover — a set of strategies used by the teams to practice Agile despite insufficient or ineffective customer involvement.

Conclusion

Customer involvement is important on Agile projects. Inadequate customer involvement causes adverse problems for Agile teams. The Agile Undercover strategies we’ve identified can assist Agile teams facing similar lack of customer involvement.     

Software product line testing - A systematic mapping study

Context

Software product lines (SPL) are used in industry to achieve more efficient software development. However, the testing side of SPL is underdeveloped.

Objective

This study aims at surveying existing research on SPL testing in order to identify useful approaches and needs for future research.

Method

A systematic mapping study is launched to find as much literature as possible, and the 64 papers found are classified with respect to focus, research type and contribution type.

Results

A majority of the papers are of proposal research types (64%). System testing is the largest group with respect to research focus (40%), followed by management (23%). Method contributions are in majority.

Conclusions

More validation and evaluation research is needed to provide a better foundation for SPL testing.     

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.     

A systematic literature review of actionable alert identification techniques for automated static code analysis

Context

Automated static analysis (ASA) identifies potential source code anomalies early in the software development lifecycle that could lead to field failures. Excessive alert generation and a large proportion of unimportant or incorrect alerts (unactionable alerts) may cause developers to reject the use of ASA. Techniques that identify anomalies important enough for developers to fix (actionable alerts) may increase the usefulness of ASA in practice.

Objective

The goal of this work is to synthesize available research results to inform evidence-based selection of actionable alert identification techniques (AAIT).

Method

Relevant studies about AAITs were gathered via a systematic literature review.

Results

We selected 21 peer-reviewed studies of AAITs. The techniques use alert type selection; contextual information; data fusion; graph theory; machine learning; mathematical and statistical models; or dynamic detection to classify and prioritize actionable alerts. All of the AAITs are evaluated via an example with a variety of evaluation metrics.

Conclusion

The selected studies support (with varying strength), the premise that the effective use of ASA is improved by supplementing ASA with an AAIT. Seven of the 21 selected studies reported the precision of the proposed AAITs. The two studies with the highest precision built models using the subject program’s history. Precision measures how well a technique identifies true actionable alerts out of all predicted actionable alerts. Precision does not measure the number of actionable alerts missed by an AAIT or how well an AAIT identifies unactionable alerts. Inconsistent use of evaluation metrics, subject programs, and ASAs in the selected studies preclude meta-analysis and prevent the current results from informing evidence-based selection of an AAIT. We propose building on an actionable alert identification benchmark for comparison and evaluation of AAIT from literature on a standard set of subjects and utilizing a common set of evaluation metrics.     

Measuring and predicting software productivity: A systematic map and review

Context

Software productivity measurement is essential in order to control and improve the performance of software development. For example, by identifying role models (e.g. projects, individuals, tasks) when comparing productivity data. The prediction is of relevance to determine whether corrective actions are needed, and to discover which alternative improvement action would yield the best results.

Objective

In this study we identify studies for software productivity prediction and measurement. Based on the identified studies we first create a classification scheme and map the studies into the scheme (systematic map). Thereafter, a detailed analysis and synthesis of the studies is conducted.

Method

As a research method for systematically identifying and aggregating the evidence of productivity measurement and prediction approaches systematic mapping and systematic review have been used.

Results

In total 38 studies have been identified, resulting in a classification scheme for empirical research on software productivity. The mapping allowed to identify the rigor of the evidence with respect to the different productivity approaches. In the detailed analysis the results were tabulated and synthesized to provide recommendations to practitioners.

Conclusion

Risks with simple ratio-based measurement approaches were shown. In response to the problems data envelopment analysis seems to be a strong approach to capture multivariate productivity measures, and allows to identify reference projects to which inefficient projects should be compared. Regarding simulation no general prediction model can be identified. Simulation and statistical process control are promising methods for software productivity prediction. Overall, further evidence is needed to make stronger claims and recommendations. In particular, the discussion of validity threats should become standard, and models need to be compared with each other.     

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.     

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.     

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.     

Systematic literature review of machine learning based software development effort estimation models

Context

Software development effort estimation (SDEE) is the process of predicting the effort required to develop a software system. In order to improve estimation accuracy, many researchers have proposed machine learning (ML) based SDEE models (ML models) since 1990s. However, there has been no attempt to analyze the empirical evidence on ML models in a systematic way.

Objective

This research aims to systematically analyze ML models from four aspects: type of ML technique, estimation accuracy, model comparison, and estimation context.

Method

We performed a systematic literature review of empirical studies on ML model published in the last two decades (1991-2010).

Results

We have identified 84 primary studies relevant to the objective of this research. After investigating these studies, we found that eight types of ML techniques have been employed in SDEE models. Overall speaking, the estimation accuracy of these ML models is close to the acceptable level and is better than that of non-ML models. Furthermore, different ML models have different strengths and weaknesses and thus favor different estimation contexts.

Conclusion

ML models are promising in the field of SDEE. However, the application of ML models in industry is still limited, so that more effort and incentives are needed to facilitate the application of ML models. To this end, based on the findings of this review, we provide recommendations for researchers as well as guidelines for practitioners.     

Data warehouse testing: A prototype-based methodology

Context

Testing is an essential part of the development life-cycle of any software product. While most phases of data warehouse design have received considerable attention in the literature, not much has been written about data warehouse testing.

Objective

In this paper we propose a comprehensive approach to testing data warehouse systems. Its main features are earliness with respect to the life-cycle, modularity, tight coupling with design, scalability, and measurability through proper metrics.

Method

We introduce a number of specific testing activities, we classify them in terms of what is tested and how it is tested, and we show how they can be framed within a prototype-based methodology. We apply our approach to a real case study for a large retail company.

Results

The case study we faced, based on an iterative prototype-based medium-size project, confirmed the validity of our approach. In particular, the main benefits were obtained in terms of project transparency, coordination of the development team, and organization of design activities.

Conclusion

Though some general-purpose testing techniques can be applied to data warehouse projects, the effectiveness of testing can be largely improved by applying specifically-devised techniques and metrics.