Relationship between requirements analyzability, interpersonal trust, and software project performance: Moderating role of customization

Based on the information processing perspective, this study empirically investigated the effects of requirements analyzability, an indicator of technological complexity and interpersonal trust as the soft factor of buyer-supplier relationships on software project development performance. Beyond that, the possible moderator role of the degree of software customization was examined on the analyzability-interpersonal trust and analyzability-performance links. Data were collected from 138 companies through a questionnaire-based survey of IT purchasing managers in Turkey. Partial Least Squares Structural Equation Modeling was used to test the research hypotheses. This study indicated that requirements analyzability and interpersonal trust have a significant effect on software performance. Overall, the study provides evidence that interpersonal trust mediates the relationship between requirements analyzability and software project performance. The research findings support the moderation role of customization in the relationship between requirements analyzability and software project performance. However, partial support is provided for the moderating effect of customization on the relationship between requirements analyzability and interpersonal trust.

Applying DTGolog to Large-scale Domains

While decision theoretic planning (DTP) offers great potential benefits to elicit purposeful behavior of the agent operating in uncertain environments, state-based approaches to DTP are known to be computationally intractable in large-scale domains. DTGolog is a decision-theoretic extension of a logic-based high level programming language Golog that completes a given partial Golog program using a form of directed value iteration. DTGolog has been proposed to alleviate some of the computational difficulties associated with DTP. The main advantages of DTGolog are that a DTP problem can be formulated using a logical representation to avoid explicit state enumeration, and the programmer can encode domain-specific knowledge in terms of high-level procedural templates to partially specify behavior of an agent. These templates constrain the search space to manageable size. Despite these clear advantages, there are few studies that investigate the applicability of DTGolog to very large-scale practical domains. In this thesis, we conduct two studies. First, we apply DTGolog to the well known case-study of the London Ambulance Service to demonstrate advantages and potentials of DTGolog as a quantitative evaluation tool for designing decision making agents. Second, we develop a software interface that allows to control the well-known Sony's AIBO robotics platform using DTGolog. We show that DTGolog can be used on this platform with a minimal amount of software customization. We run experiments to test functionality of our interface. The main contribution of this thesis is demonstration of applicability of DTGolog to two different large scale domains that are both practical and interesting.

Applying DTGolog to Large-scale Domains

While decision theoretic planning (DTP) offers great potential benefits to elicit purposeful behavior of the agent operating in uncertain environments, state-based approaches to DTP are known to be computationally intractable in large-scale domains. DTGolog is a decision-theoretic extension of a logic-based high level programming language Golog that completes a given partial Golog program using a form of directed value iteration. DTGolog has been proposed to alleviate some of the computational difficulties associated with DTP. The main advantages of DTGolog are that a DTP problem can be formulated using a logical representation to avoid explicit state enumeration, and the programmer can encode domain-specific knowledge in terms of high-level procedural templates to partially specify behavior of an agent. These templates constrain the search space to manageable size. Despite these clear advantages, there are few studies that investigate the applicability of DTGolog to very large-scale practical domains. In this thesis, we conduct two studies. First, we apply DTGolog to the well known case-study of the London Ambulance Service to demonstrate advantages and potentials of DTGolog as a quantitative evaluation tool for designing decision making agents. Second, we develop a software interface that allows to control the well-known Sony's AIBO robotics platform using DTGolog. We show that DTGolog can be used on this platform with a minimal amount of software customization. We run experiments to test functionality of our interface. The main contribution of this thesis is demonstration of applicability of DTGolog to two different large scale domains that are both practical and interesting.

An Empirical Investigation of Software Customization and Its Impact on the Quality of Software as a Service: Perspectives from Software Professionals

Although customization plays a significant role in the provision of software as a service (SaaS), delivering a customizable SaaS application that reflects the tenant’s specific requirements with acceptable level of quality is a challenge. Drawing on a pr-developed software customization model for SaaS quality, two fundamental objectives of this study were to determine whether different software customization approaches have direct impacts on SaaS quality, and also to assess the construct reliability and construct validity of the model. A questionnaire-based survey was used to collect data from 244 software professionals with experience in SaaS development. Structural equation modeling was employed to test the construct reliability, construct validity, and research hypotheses. The measurement model assessment suggested that the six-construct model with 39 items exhibited good construct reliability and construct validity. The findings of the structural model assessment show that all customization approaches other than the integration approach significantly influence the quality of SaaS applications. The findings also indicate that both configuration and composition approaches have positive impacts on SaaS quality, while the impacts of the other approaches are negative. The empirical assessment and evaluation of this model, which features a rich set of information, provides considerable benefits to both researchers and practitioners.

Maximizing the Value of Packaged Software Customization

Organizations that purchase packaged application software – for example, an Enterprise Resource Planning system – must make choices about customization. Packaged software vendors and practitioners recommend that organizations customize software as little as possible, and instead adapt their processes to meet the “best practices” of the software. However, organizations continue to exceed their budgets on implementing and maintaining customized software. This suggests that either these organizations are making poor decisions, or that the conventional wisdom about customization is incorrect. In this paper the author models the primary factors in the customization decision, most notably the “fit” between desired processes and the procedures inherent in the packaged software. The author then consider costs related to development, maintenance, and technical corrections due to poor integration and performance; and benefits related to increased fit, technical corrections, and user acceptance. This paper extends prior work by (1) modelling nonlinear relationships between the amount of time spent on custom development and the resulting benefits, (2) modelling nonlinear relationships between development costs and maintenance costs, and (3) modelling corrective development as a function of development related to fit and user acceptance. The author uses simulation techniques to illustrate the conditions under which customization is likely to provide value to the organization, as well as conditions under which customization should be avoided.

Development of a valid and reliable software customization model for SaaS quality through iterative method: perspectives from academia

Despite the benefits of standardization, the customization of Software as a Service (SaaS) application is also essential because of the many unique requirements of customers. This study, therefore, focuses on the development of a valid and reliable software customization model for SaaS quality that consists of (1) generic software customization types and a list of common practices for each customization type in the SaaS multi-tenant context, and (2) key quality attributes of SaaS applications associated with customization. The study was divided into three phases: the conceptualization of the model, analysis of its validity using SaaS academic-derived expertise, and evaluation of its reliability by submitting it to an internal consistency reliability test conducted by software-engineer researchers. The model was initially devised based on six customization approaches, 46 customization practices, and 13 quality attributes in the SaaS multi-tenant context. Subsequently, its content was validated over two rounds of testing after which one approach and 14 practices were removed and 20 practices were reformulated. The internal consistency reliability study was thereafter conducted by 34 software engineer researchers. All constructs of the content-validated model were found to be reliable in this study. The final version of the model consists of 6 constructs and 44 items. These six constructs and their associated items are as follows: (1) Configuration (eight items), (2) Composition (four items), (3) Extension (six items), 4) Integration (eight items), (5) Modification (five items), and (6) SaaS quality (13 items). The results of the study may contribute to enhancing the capability of empirically analyzing the impact of software customization on SaaS quality by benefiting from all resultant constructs and items.