Abstract Despite the particular standards, technologies, and trends (W3C, RESTful, microservices, etc.) that a team decides to follow for the development of a service‐oriented system, most likely the team members will have to use one or more services that solve general‐purpose problems like cloud computing, networking and content delivery, storage and database, management and governance, and application integration. Typically, general‐purpose services are long‐lived, they have several responsibilities, their interfaces are complex, and they grow over time. The way that these services evolve also affects the evolution of any system that will depend on them. Consequently, the selection of the particular services that will be used is a main concern for the team. In this paper, we report a pattern, calledthe athletic heart syndrome, which facilitates the selection of services that evolve properly. Patterns specify best practices that emerge from multiple real‐world cases. In our context,the athletic heart syndromecomes out from a study that concerns the evolution of a set of popular, long‐lived Amazon services that cover different domains. According tothe athletic heart syndrome, the developers should select services whose heartbeat of changes looks like the heartbeat of an athlete when he is at rest. Specifically, the heartbeat of changes should consist mostly of calm periods, interrupted by few spikes of change. Similarly, the incremental growth of the services should involve mainly calm periods of maintenance, separated by spikes of growth. Selecting services that adhere to the pattern signifies high chances that the services evolve to deal with changing requirements. The pattern further guarantees that the service evolution involves both the expansion of the services with new functionalities and the maintenance of existing ones. The pattern also assures that the complexity increase in the service interfaces will be smooth and tolerable. Finally, conformance with the pattern implies that the growth of the services will be predictable.

Schema integration has been a long-standing challenge for the data-engineering community that has received steady attention over the past three decades. General-purpose integration approaches construct unified schemas that encompass all schema elements. Schema integration has been revisited in the past decade in service-oriented computing since the input/output data-types of service interfaces are heterogeneous XML schemas. However, service integration differs from the traditional integration problem, since it should generalize schemas (mining abstract data-types) instead of unifying all schema elements. To mine well-formed abstract data-types, the fundamental Liskov Substitution Principle (LSP), which generally holds between abstract data-types and their subtypes, should be followed. However, due to the heterogeneity of service data-types, the strict employment of LSP is not usually feasible. On top of that, XML offers a rich type system, based on which data-types are defined via combining type patterns (e.g., composition, aggregation). The existing integration approaches have not dealt with the challenges of a defining subtyping relation between XML type patterns. To address these challenges, we propose a relaxed version of LSP between XML type patterns and an automated generalization process for mining abstract XML data-types. We evaluate the effectiveness and the efficiency of the process on the schemas of two datasets against two representative state-of-the-art approaches.

A class that provides a fat interface violates the interface segregation principle, which states that the clients of the class should not be coupled with methods that they do not need. Coping with this problem involves extracting interfaces that satisfy the needs of the clients. In this paper, we envision an interface extraction method that serves a combination of four principles: (1) fitness, as the extracted interfaces have to fit the needs of the clients, (2) clarity, as the interfaces should not be cluttered with duplicated methods declarations due to the clients' similar needs, (3) flexibility, as it should be easy to maintain the extracted interfaces to cope with client changes, without affecting parts of the software that are not concerned by the changes, and (4) practicality, as the interface extraction should account for practical issues like the number of extracted interfaces, domain/developer specific constraints on what to include in the interfaces, etc. Our preliminary results show that it is feasible to extract interfaces by respecting the aforementioned principles. Moreover, our results reveal a number of open issues around the trading between fitness, clarity, flexibility and practicality.

The essence of refactoring is to improve software quality via the systematic combination of primitive refactorings. Yet, there are way too many refactorings. Choosing which refactorings to use, how to combine them and how to integrate them in more complex evolution tasks is really hard. Our vision is to provide the developer with a "trip advisor" for the archipelago of refactorings. The core idea of our approach is the map of the archipelago of refactorings, which identies the basic relations that guide the systematic and eective combination of refactorings. Based on the map, the trip advisor makes suggestions that allow the developer to decide how to start, assess the possible alternatives, have a clear picture of what has to be done before, during and after the refactorings and assess the possible implications.

Software cohesion concerns the degree to which the elements of a module belong together. Cohesive software is easier to understand, test and maintain. In the context of service-oriented development, cohesion refers to the degree to which the operations of a service interface belong together. In the state of the art, software cohesion is improved based on refactoring methods that rely on information, extracted from the software implementation. This is a main limitation towards using these methods in the case of web services: web services do not expose their implementation; instead all that they export is the web service interface specification. To deal with this problem, we propose an approach that enables the cohesion-driven decomposition of service interfaces, without information on how the services are implemented. Our approach progressively decomposes a given service interface into more cohesive interfaces; the backbone of the approach is a suite of cohesion metrics that rely on information, extracted solely from the specification of the service interface. We validate the approach in 22 real-world services, provided by Amazon and Yahoo. We assess the effectiveness of the proposed approach, concerning the cohesion improvement, and the number of interfaces that result from the decomposition of the examined interfaces. Moreover, we show the usefulness of the approach in a user study, where developers assessed the quality of the produced interfaces.

The state of the art service search engines allow the users to pick the services they need, based on the quality properties, offered by these services. To this end, the users should interact with the search engines based on the quality models that are imposed by the engines. This is a significant restriction towards making the service-oriented paradigm attractive to the general public. In this paper, we propose an approach that allows a user to specify his perception of quality in terms of a simple, user-defined quality model. The proposed approach automatically maps the user-defined quality model to the search engine's quality model. This mapping forms the basis for ordering, grouping and, in general manipulating, the results of the user's service discovery requests.

Several lines of research rely on the concept of service abstractions to enable the organization, the composition and the adaptation of services. However, what is still missing, is a systematic approach for extracting service abstractions out of the vast amount of services that are available all over the Web. To deal with this issue, we propose an approach for mining service abstractions, based on an agglomerative clustering algorithm. Our experimental findings suggest that the approach is promising and can serve as a basis for future research.

A design issue that often appears in real-world services is that their interfaces are not cohesive, i.e., they consist of many and possibly unrelated operations. This issue may complicate the comprehension of the services functionalities and the maintenance of the applications that use them. Currently, the state of the art on case studies that focus on the evaluation of the cohesion of services offered by major service providers is limited, while research efforts on corresponding cohesion metrics are at a quite early stage. In particular, there exist coarse-grained metrics of cohesion lack, which consider that the operations of a service interface are related if the types of certain of their input/output data exactly match. The problem in this approach is that operations which operate on data characterized by similar, but not exactly matching, types are treated as being totally unrelated. Consequently, the aforementioned metrics may overestimate the cohesion lack of service interfaces. In this paper, we undertake a more elaborate approach to evaluate a set of real world services provided by Amazon. Specifically, we propose two fine-grained metrics of cohesion lack, which are defined with respect to the structural similarity of the input/output data types of interface operations. The proposed metrics are formally defined and analytically assessed with respect to fundamental properties of software metrics. Finally we report the results from our case study.

The appropriate deployment of web service operations at the service provider site plays a critical role in the efficient provision of services to clients. In this paper, the authors assume that a service provider has several servers over which web service operations can be deployed. Given a workflow of web services and the topology of the servers, the most efficient mapping of operations to servers must then be discovered. Efficiency is measured in terms of two cost functions that concern the execution time of the workflow and the fairness of the load distribution among the servers. The authors study different topologies for the workflow structure and the server connectivity and propose a suite of greedy algorithms for each combination.

In this paper, we propose a framework that reduces the complexity of service substitution. The framework is based on two substitution relations and corresponding theorems. The proposed relations and theorems allow organizing available services into groups. Then, the complexity of retrieving candidate substitute services for the target service and generating corresponding adapters scales up with the number of available groups, instead of scaling up with the number of available services.

We address the problem of efficiently distributing query messages among peers in a wireless ad hoc network. We assume that peers are organized in classes. Each peer possesses a local database and can answer queries posed by other peers. Each peer can also pose queries to all the peers belonging to a certain class and/or within a certain range of distance in the network. Contrary to traditional p2p lookup queries, we are interested in collecting answers from as many peers as possible. To efficiently serve this purpose, we take advantage of routing and application layer specifics (e.g., class information, network distance) to avoid flooding and at the same time preserve compatibility with traditional routing and transport mechanisms.

Pattern-based Java bytecode compression techniques rely on the identification of identical instruction sequences that occur more than once. Each occurrence of such a sequence is substituted by a single instruction. The sequence defines a pattern that is used for extending the standard bytecode instruction set with the instruction that substitutes the pattern occurrences in the original bytecode. Alternatively, the pattern may be stored in a dictionary that serves for the bytecode decompression. In this case, the instruction that substitutes the pattern in the original bytecode serves as an index to the dictionary. In this paper, we investigate a bytecode compression technique that considers a more general case of patterns. Specifically, we employ the use of an advanced pattern discovery technique that allows locating patterns of an arbitrary length, which may contain a variable number of wildcards in place of certain instruction opcodes or operands. We evaluate the benefits and the limitations of this technique in various scenarios that aim at compressing the reference implementation of MIDP, a standard Java environment for the development of applications for mobile devices.

Good quality models for the analysis of complex enterprise information systems (EIS) are hard to build and require lots of experience and effort, which are not always available. A possible solution to deal with the previous issue is to build automated procedures for quality model generation. Such procedures will encapsulate previous existing knowledge on quality modeling and their use will reduce the cost of developing quality models. The authors concentrate on the performance and reliability of EIS and investigate the automatic generation of quality models from EIS architectural descriptions comprising additional information related to the aspects that affect the quality of the EIS.