User Expectations of Hedonic Software Updates

Software updates have recently become a common phenomenon in software development and maintenance. This is due to the rise of ubiquitous and interconnected IT that enables developers to frequently fix bugs, enhance features, or even add new functionalities. This paper contributes to the post-adoption topic of IS research by investigating the understanding of how users perceive software updates of hedonic software. The focus is to understand how and what users perceive and expect from upcoming updates. Pokémon GO is the IT artifact that will be examined with the paper as it is a prime example of an innovative and trending game that was released relatively unfinished, but is constantly improved via updates. We use the IS continuance model to evaluates the players perception on: expectations before the initial use, confirmation or disconfirmation, perceived ease of use, perceived enjoyment, expectations for upcoming software updates, and continuance intention

SEAMLESS UPDATES – HOW SECURITY AND FEATURE UPDATE DELIVERY STRATEGIES AFFECT CONTINUANCE INTENTIONS WITH DIGITAL APPLICATIONS

Although updates have become the rule rather than the exception in modern digital ecosystems, to date they have received little attention in the IS post-adoption literature. We therefore draw on the IS continuance literature and expectation-confirmation theory to investigate, how different delivery strategies of security and feature updates impact users’ continuance intentions (CI). Based on an online experiment with 282 participants, we find a positive effect of security updates on users’ CI only if users are notified after successful implementation. Feature updates, in contrast, elicit a positive effect on users’ CI if they are at least announced before or after successful implementation. We also find that this positive effect of ex-ante announced feature updates diminishes if users have the choice to consume the update or not. In essence, our findings contribute to IS research by extending the mostly monolithic view of information systems by showing how an alterable information system might influence users’ attitudes and behaviors during use. For practitioners, we show that it seems to be beneficial to inform users about updates, even though a silent integration has become possible with modern digital ecosystems, and that updates should be applied consistently. Directions for further research are discussed

Artificial intelligence and software engineering: Status and future trends

The disciplines of Artificial Intelligence and Software Engineering have many commonalities. Both deal with modeling real world objects from the real world like business processes, expert knowledge, or process models. This article gives a short overview about these disciplines and describes some current research topics against the background of common points of contact

Gains and Losses in Functionality – An Experimental Investigation of the Effect of Software Updates on Users’ Continuance Intentions

Although software updates are ubiquitous in professional and private IS usage, their impact on user behaviors has received little attention in post-adoption research. Based on expectation-confirmation-theory and the IS continuance model, we investigate the effects of gaining and loosing features through updates on expert and novice users’ continuance intentions (CI). In a vignette based experiment, we find that updates which add features to software after its release increase novices’ CI above and beyond a level generated by a monolithic software package that contains the entire feature set from the beginning. With diminished CI, experts show a contrary reaction to the same update. Losing features through an update, on the other hand, severely diminishes CI for experts and novices alike. Mediation analysis reveals positive disconfirmation of previous expectations as psychological mechanism behind novices’ counter-intuitive and somewhat non-rational responses to gaining features through an update. Implications for research and practice are derived

Empirical Studies of Android API Usage: Suggesting Related API Calls and Detecting License Violations.

We mine the API method calls used by Android App developers to (1)suggest related API calls based on the version history of Apps, (2) suggest related API calls based on StackOverflow posts, and (3) find potential App copyright and license vio- lations based the similarity of API calls made by them. Zimmermann et al suggested that �Programmers who changed these functions also changed� functions that could be mined from previous groupings of functions found in the version history of a system. Our first contribution is to expand this approach to a community of Apps. Android developers use a set of API calls when creating Apps. These API methods are used in similar ways across multiple applications. Clustering co-changing API methods used by 230 Android Apps, we are able to predict the changes to API methods that individual App developers will make to their application with an average precision of 73% and recall of 25%. Our second contribution can be characterized as �Programmers who discussed these functions were also interested in these functions.� Informal discussion on Stack- Overflow provides a rich source of related API methods as developers provide solu- tions to common problems. Clustering salient API methods in the same highly ranked posts, we are able to create rules that predict the changes App developers will make with an average precision of 64% and recall of 15%. Our last contribution is to find out whether proprietary Apps copy code from open source Apps, thereby violating the open source license. We have provided a set of techniques that determines how similar two Apps are based on the API calls they make. These techniques include android API calls matching, API calls coverage, App categories, Method/Class clusters and released size of Apps. To validate this approach we conduct a case study of 150 open source project and 950 proprietary projects

Supporting Software Maintenance by Mining Software Update Records

This paper describes the application of inductive methods to data extracted from both source code and software maintenance records. We would like to extract relations that indicate which files in, a legacy system, are relevant to each other in the context of program maintenance. We call these relations Maintenance Relevance Relations. Such a relation could reveal existing complex interconnections among files in the system, which may in turn be useful in comprehending them. We discuss the methodology we employed to extract and evaluate the relations. We also point out some of the problems we encountered and our solutions for them. Finally, we present some of the results that we have obtained

Supporting Software Maintenance by Mining Software Update Records

To my father, mother and sister for their endless love and support I have yet to see any problem, however complicated, which, when you looked at it in the right way, did not become still more complicated. Poul Anderson (1926-2001) Science Fiction Writer It is well known that maintenance is the most expensive stage of the software life cycle. Most large real world software systems consist of a very large number of source code files. Important knowledge about different aspects of a software system is embedded in a rich set of implicit relationships among these files. Those relationships are partly reflected in system documentation at its different levels, but more often than not are never made explicit and become part of the expertise of system maintainers. Finding existing relations between source code components is a difficult task, especially in the case of legacy systems. When a maintenance programmer is looking at a piece of code in a source file, one of th

Predicting change propagation using domain-based coupling

Most enterprise systems operate in domains where business rules and requirements frequently change. Managing the cost and impact of these changes has been a known challenge, and the software maintenance community has been tackling it for more than two decades. The traditional approach to impact analysis is by tracing dependencies in the design documents and the source code. More recently the software maintenance history has been exploited for impact analysis. The problem is that these approaches are difficult to implement for hybrid systems that consist of heterogeneous components. In today’s computer era, it is common to find systems of systems where each system was developed in a different language. In such environments, it is a challenge to estimate the change propagation between components that are developed in different languages. There is often no direct code dependency between these components, and they are maintained in different development environments by different developers. In addition, it is the domain experts and consultants who raise the most of the enhancement requests; however, using the existing change impact analysis methods, they cannot evaluate the impact and cost of the proposed changes without the support of the developers. This thesis seeks to address these problems by proposing a new approach to change impact analysis based on software domain-level information. This approach is based on the assumption that domain-level relationships are reflected in the software source code, and one can predict software dependencies and change propagation by exploiting software domain-level information. The proposed approach is independent of the software implementation, inexpensive to implement, and usable by domain experts with no requirement to access and analyse the source code. This thesis introduces domain-based coupling as a novel measure of the semantic similarity between software user interface components. The hypothesis is that the domain-based coupling between software components is correlated with the likelihood of the existence of dependencies and change propagation between these components. This hypothesis has been evaluated with two case studies: • A study of one of the largest open source enterprise systems demonstrates that architectural dependencies can be identified with an accuracy of more than 70% solely based on the domain-based coupling. • A study of 12 years’ maintenance history of the five subsystems of a significant sized proprietary enterprise system demonstrates that the co-change coupling derived from over 75,000 change records can be predicted solely using domain-based coupling, with average recall and precision of more than 60%, which is of comparable quality to other state-of-the-art change impact analysis methods. The results of these studies support our hypothesis that software dependencies and change propagation can be predicted solely from software domain-level information. Although the accuracy of such predictions are not sufficiently strong to completely replace the traditional dependency analysis methods; nevertheless, the presented results suggest that the domain-based coupling might be used as a complementary method or where analysis of dependencies in the code and documents is not a viable option

Users’ Loyalty to Agile Information Systems

Over the past few years, across many industrial sectors, Information Systems (IS) developed with the help of agile methods have become the rule rather than the exception. Because of their high flexibility, such Agile IS development methodologies help firms to keep pace with emerging market requirements. At the same time, customers are also gaining increasing market power due to an expanding digitalization of services and products, which decreases switching barriers and increases transparency. As a result, it has become crucial for firms to develop IS that continuously provide sufficient value to customers. This is one of the main reasons why firms regularly deliver increments of Agile IS for users to update outdated software versions. By doing so, firms try to bind and engage customers lastingly to capture current and future revenue streams and stay competitive. Agile IS and software updates (that deliver increments of Agile IS to users) have been researched thoroughly, however mostly from a technical point of view. Nevertheless, because updates change a system while it is already in use, they have the potential to impact users’ beliefs, attitudes, behaviors, and in particular, loyalty to a software in the post-adoption phase. However, despite the importance of better understanding user responses to Agile IS to provide an adequate theoretical framework, research from a user’s perspective on Agile IS, and especially software updates, is still scarce. Against this backdrop, this thesis presents four empirical studies that were conducted to investigate whether and how Agile IS affect users’ loyalty to IS, to identify potential moderators, and to understand how Agile IS should be designed to facilitate potential positive effects. In these studies, increments of Agile IS are operationalized as software updates and customer loyalty as a user’s continuance intention with a system. By drawing on the IS Continuance Model in a scenario-based online experiment, the first two studies reveal empirically how Agile IS have the potential to increase user continuance intentions. Users of Agile IS show greater IS continuance intentions, despite that some functionality is provided only later on, as compared to a consistently feature-complete traditional IS. This effect is diminished somewhat when the software is introduced with an extensive feature set right from the beginning. Nevertheless, the size of an update does not seem to play a significant role. The second study reveals that this positive effect of updates only emerges if the user is not very knowledgeable regarding the software, because experts in contrast to novices seem to devalue Agile IS (their continuance intentions decrease with Agile IS in comparison to traditional IS). Additionally, the second study shows that the removal of features through updates reduces continuance intentions even more than the equivalent addition of features when considering the absolute magnitude of change. With empirical data from a laboratory experiment, the third study identifies update frequency and update type as further moderators of the effect, and confirms the hypothesized mediation mechanism presumed by the IS Continuance Model. The fourth study examines the role of update delivery strategies, i.e., the timing and presence of a notification and an installation choice. In this study, feature and security updates are distinguished, as both seem to have different characteristics with respect to the delivery strategy (i.e., users ‘need’ security but ‘want’ to add functionality). The findings show that both update types should be announced to users, in the case of a security update, only after successful installation, while presenting an installation choice to users prevents any positive effect for all types of updates. Overall, this thesis highlights the importance of understanding Agile IS and software updates from the user’s perspective. First, the results show that Agile IS have the potential to affect user’s continuance intentions, thereby contributing to a comprehensive theoretical foundation on Agile IS. Also the findings put the user more at the center of investigations in IS. Second, the empirical findings provide evidence in support of a necessary fine-grained understanding of IT Artifacts as malleable compositions of specific features and characteristics. This answers the call of several researchers to put the IT Artifact more at the focus of IS research (Benbasat and Zmud 2003). Third, the results reveal that changes in IS might change users’ attitudes and behaviors over time, which extends the predominant view of IS in post-adoption literature from a mostly static to a more dynamic perspective. With this finding, we answer the call of several IS scholars to consider the evolution of IS more thoroughly (e.g., Jasperson et al. 2005; Benbasat and Barki 2007). For practitioners, the findings of this thesis provide empirically backed rationales to inform management decisions concerning the deployment of Agile IS and offer guidance on strategic or design considerations. Overall, the results show how and when the value provided by IS from a user’s perspective may be increased by the deployment of Agile IS and software updates