Barriers in the selection of offshore software development outsourcing vendors: An exploratory study using a systematic literature review

Context

Software development outsourcing is a contract-based relationship between client and vendor organisations in which a client contracts out all or part of its software development activities to a vendor, who provides agreed services for remuneration.

Objective

The objective is to identify various barriers that have a negative impact on software outsourcing clients in the selection process of offshore software development outsourcing vendors.

Method

We have performed a systematic literature review (SLR) process for the identification of barriers. We have performed all the SLR steps such as the protocol development, initial selection, final selection, quality assessment, data extraction and data synthesis.

Results

We have identified barriers such as ‘language and cultural barriers’, ‘country instability’, ‘lack of project management’, ‘lack of protection for intellectual property rights’ and ‘lack of technical capability’ that generally have a negative impact on outsourcing clients. We have identified only one common frequently cited barrier in three types of organisations (i.e. small, medium and large) which is ‘language and cultural barriers’. We did not identify any common frequently cited barrier in three continents (Asia, North America and Europe) and in two decades (1990-1999 and 2000-mid 2008). The results also reveal the similarities and differences in the barriers identified through different study strategies.

Conclusions

Vendors should address frequently cited barriers such as ‘language and cultural barriers’, ‘country instability’, ‘lack of project management’, ‘lack of protection for intellectual property rights’ and ‘lack of technical capability’ in order to compete in the offshore outsourcing business.     

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.     

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.     

Testing in Service Oriented Architectures with dynamic binding: A mapping study

Context

Service Oriented Architectures (SOA) have emerged as a new paradigm to develop interoperable and highly dynamic applications.

Objective

This paper aims to identify the state of the art in the research on testing in Service Oriented Architectures with dynamic binding.

Method

A mapping study has been performed employing both manual and automatic search in journals, conference/workshop proceedings and electronic databases.

Results

A total of 33 studies have been reviewed in order to extract relevant information regarding a previously defined set of research questions. The detection of faults and the decision making based on the information gathered from the tests have been identified as the main objectives of these studies. To achieve these goals, monitoring and test case generation are the most proposed techniques testing both functional and non-functional properties. Furthermore, different stakeholders have been identified as participants in the tests, which are performed in specific points in time during the life cycle of the services. Finally, it has been observed that a relevant group of studies have not validated their approach yet.

Conclusions

Although we have only found 33 studies that address the testing of SOA where the discovery and binding of the services are performed at runtime, this number can be considered significant due to the specific nature of the reviewed topic. The results of this study have contributed to provide a body of knowledge that allows identifying current gaps in improving the quality of the dynamic binding in SOA using testing approaches.     

SOAdapt: A process reference model for developing adaptable service-based applications

Context

The loose coupling of services and Service-Based Applications (SBAs) have made them the ideal platform for context-based run-time adaptation. There has been a lot of research into implementation techniques for adapting SBAs, without much effort focused on the software process required to guide the adaptation.

Objective

This paper aims to bridge that gap by providing an empirically grounded software process model that can be used by software practitioners who want to build adaptable SBAs. The process model will focus only on the adaptation specific issues.

Method

The process model presented in this paper is based on data collected through interviews with 10 practitioners occupying various roles within eight different companies. The data was analyzed using qualitative data analysis techniques. We used the output to develop a set of activities, tasks, stakeholders and artifacts that were used to construct the process model.

Results

The outcome of the data analysis process was a process model identifying nine sets of adaptation process attributes. These can be used in conjunction with an organisation’s existing development life-cycle or another reference life-cycle.

Conclusion

The process model developed in this paper provides a solid reference for practitioners who are planning to develop adaptable SBAs. It has advantages over similar approaches in that it focuses on software process rather than the specific adaptation mechanism implementation techniques.     

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.     

Improving the applicability of object-oriented class cohesion metrics

Context

Class cohesion is an important object-oriented quality attribute. It refers to the degree of relatedness between the methods and attributes of a class. Several metrics have been proposed to measure the extent to which the class members are related. Most of these metrics have undefined values for a relatively high percentage of classes, which limits their applicability. The classes that have undefined values lack methods, attributes, or parameter types, or they include only a single method.

Objective

We improve the applicability of the class cohesion metrics by defining their values for such special classes. In addition, we theoretically and empirically validate the improved metrics.

Method

We theoretically examine whether the defined values satisfy the key cohesion properties. In addition, we empirically validate the metrics before and after the improvements to test whether the defined values improve the ability of the metrics to evaluate class cohesion. We also explore the correlation between the metrics and the presence of faulty classes to indirectly determine the strength or weakness of the metrics in indicating class quality.

Results

The results show that our assigned values for the undefined cases do not violate the key cohesion properties and considerably improve the ability of the metrics to explain the presence of faulty classes and may therefore improve their ability to indicate the quality of the class design.

Conclusions

Having the class cohesion metrics defined for all possible cases improves the applicability of the metrics and potentially increases their precision in indicating class quality.     

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.     

Transfer learning for cross-company software defect prediction

Context

Software defect prediction studies usually built models using within-company data, but very few focused on the prediction models trained with cross-company data. It is difficult to employ these models which are built on the within-company data in practice, because of the lack of these local data repositories. Recently, transfer learning has attracted more and more attention for building classifier in target domain using the data from related source domain. It is very useful in cases when distributions of training and test instances differ, but is it appropriate for cross-company software defect prediction?

Objective

In this paper, we consider the cross-company defect prediction scenario where source and target data are drawn from different companies. In order to harness cross company data, we try to exploit the transfer learning method to build faster and highly effective prediction model.

Method

Unlike the prior works selecting training data which are similar from the test data, we proposed a novel algorithm called Transfer Naive Bayes (TNB), by using the information of all the proper features in training data. Our solution estimates the distribution of the test data, and transfers cross-company data information into the weights of the training data. On these weighted data, the defect prediction model is built.

Results

This article presents a theoretical analysis for the comparative methods, and shows the experiment results on the data sets from different organizations. It indicates that TNB is more accurate in terms of AUC (The area under the receiver operating characteristic curve), within less runtime than the state of the art methods.

Conclusion

It is concluded that when there are too few local training data to train good classifiers, the useful knowledge from different-distribution training data on feature level may help. We are optimistic that our transfer learning method can guide optimal resource allocation strategies, which may reduce software testing cost and increase effectiveness of software testing process.