An Introduction to MultiAgent Systems.

[서평]「Component Software」 - Beyond Object-Oriented Programming -

Object-Oriented Software Metrics.

Increasingly complex and rapidly changing requirements and technologies are making application development increasingly difficult. This talk examines this phenomenon, and presents a simple pattern for building languages, patterns, frameworks and tools for specific domains, such as user interface construction or database design. Software Factories integrate critical innovations in adaptive assembly, software product lines, and model driven development to reduce the cost of implementing this pattern, making it cost effective for narrower and more specialized domains, such as B2B commerce and employee self service portals.

Software Factories: Assembling Applications with Patterns, Models, Frameworks and Tools

There is a documented gap between academic and practitioner views on software testing. This paper tries to close the gap by investigating both views regarding the benefits and limits of test automation. The academic views are studied with a systematic literature review while the practitioners views are assessed with a survey, where we received responses from 115 software professionals. The results of the systematic literature review show that the source of evidence regarding benefits and limitations is quite shallow as only 25 papers provide the evidence. Furthermore, it was found that benefits often originated from stronger sources of evidence (experiments and case studies), while limitations often originated from experience reports. We believe that this is caused by publication bias of positive results. The survey showed that benefits of test automation were related to test reusability, repeatability, test coverage and effort saved in test executions. The limitations were high initial invests in automation setup, tool selection and training. Additionally, 45% of the respondents agreed that available tools in the market offer a poor fit for their needs. Finally, it was found that 80% of the practitioners disagreed with the vision that automated testing would fully replace manual testing.

Benefits and limitations of automated software testing: systematic literature review and practitioner survey

In software development, migration from a Data Base Management System (DBMS) to another, especially with distinct characteristics, is a challenge for programmers and database administrators. Changes in the application code in order to comply with new DBMS are usually vast, causing migrations infeasible. In order to tackle this problem, we present NoSQLayer, a framework capable to support conveniently migrating from relational (i.e., MySQL) to NoSQL DBMS (i.e., MongoDB). This framework is presented in two parts: (1) migration module; and, (2) mapping module. The first one is a set of methods enabling seamless migration between DBMSs (i.e. MySQL to MongoDB). The latter provides a persistence layer to process database requests, being capable to translate and execute these requests in any DBMS, returning the data in a suitable format as well. Experiments show NoSQLayer as a handful solution suitable to handle large volume of data (e.g., Web scale) in which traditional relational DBMS might be inept in the duty.

A Framework for Migrating Relational Datasets to NoSQL 1 .

In this paper, we present a model-based tool for product derivation. Our tool is centered on the definition of three models (feature, architecture and configuration models) which enable the automatic instantiation of software product lines (SPLs) or frameworks. The Eclipse platform and EMF technology are used as the base for the implementation of our tool. A set of specific Java annotations are also defined to allow generating automatically many of our models based on existing implementations of SPL architectures. We illustrated the use and validation of our tool in the preparation of the automatic derivation of the JUnit framework and a J2ME games product line.

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A Product Derivation Tool Based on Model-Driven Techniques and Annotations.

Code anomalies are likely to be critical to the systems' maintainability when they are related to architectural problems. Many tools have been developed to support the identification of code anomalies. However, those tools are restricted to only analyze source code structure and identify individual anomaly occurrences. These limitations are the main reasons why state-of-art tools are often unable to identify architecturally-relevant code anomalies, i.e. those related to architectural problems. To overcome these shortcomings we propose SCOOP, a tool that includes: (i) architecture-code traces in the analysis of the source code, and (ii) exploits relationships between multiple occurrences of code anomalies to detect the architecturally-relevant ones. Our preliminary evaluation indicated that SCOOP was able to detect anomalous code elements related to 293 out of 368 architectural problems found in 3 software systems.

Supporting the identification of architecturally-relevant code anomalies

Automated tests have been widely used as a supporting mechanism during software development and maintenance activities. It improves the confidence on software releases as it seeks to uncover regression bugs, and serves as a live documentation which is very useful when evolving systems. Concerning multi agent systems (MASs), some characteristics such as agent autonomy and asynchronous message-based interaction bring a degree of non-determinism which presents new testing challenges. This paper proposes JAT, a framework for building and running MASs test scenarios, which relies on the use of aspect-oriented techniques to monitor the autonomous agents during tests and control the test input of asynchronous test cases. The tool has been developed on top of JADE, a widely used agent platform implemented in Java. We have used JAT on testing 3 different MASs. Our experience shows that JAT can be used to build test scenarios which can achieve high fault-detection effectiveness.

JAT: A Test Automation Framework for Multi-Agent Systems

Software metrics and thresholds provide means to quantify several quality attributes of software systems Indeed, they have been used in a wide variety of methods and tools for detecting different sorts of technical debts, such as code smells Unfortunately, these methods and tools do not take into account characteristics of software domains, as the intrinsic complexity of geo-localization and scientific software systems or the simple protocols employed by messaging applications Instead, they rely on generic thresholds that are derived from heterogeneous systems Although derivation of reliable thresholds has long been a concern, we still lack empirical evidence about threshold variation across distinct software domains To tackle this limitation, this paper investigates whether and how thresholds vary across domains by presenting a large-scale study on 3,107 software systems from 15 domains We analyzed the derivation and distribution of thresholds based on 8 well-known source code metrics As a result, we observed that software domain and size are relevant factors to be considered when building benchmarks for threshold derivation Moreover, we also observed that domain-specific metric thresholds are more appropriated than generic ones for code smell detection

Elder Cirilo

Papers

A Framework for Migrating Relational Datasets to NoSQL 1 .

A Product Derivation Tool Based on Model-Driven Techniques and Annotations.

Supporting the identification of architecturally-relevant code anomalies

JAT: A Test Automation Framework for Multi-Agent Systems

Evaluating domain-specific metric thresholds: an empirical study