Proactive Empirical Assessment of New Language Feature Adoption via Automated Refactoring: The Case of Java 8 Default Methods

Programming languages and platforms improve over time, sometimes resulting in new language features that offer many benefits. However, despite these benefits, developers may not always be willing to adopt them in their projects for various reasons. In this paper, we describe an empirical study where we assess the adoption of a particular new language feature. Studying how developers use (or do not use) new language features is important in programming language research and engineering because it gives designers insight into the usability of the language to create meaning programs in that language. This knowledge, in turn, can drive future innovations in the area. Here, we explore Java 8 default methods, which allow interfaces to contain (instance) method implementations. Default methods can ease interface evolution, make certain ubiquitous design patterns redundant, and improve both modularity and maintainability. A focus of this work is to discover, through a scientific approach and a novel technique, situations where developers found these constructs useful and where they did not, and the reasons for each. Although several studies center around assessing new language features, to the best of our knowledge, this kind of construct has not been previously considered. Despite their benefits, we found that developers did not adopt default methods in all situations. Our study consisted of submitting pull requests introducing the language feature to 19 real-world, open source Java projects without altering original program semantics. This novel assessment technique is proactive in that the adoption was driven by an automatic refactoring approach rather than waiting for developers to discover and integrate the feature themselves. In this way, we set forth best practices and patterns of using the language feature effectively earlier rather than later and are able to possibly guide (near) future language evolution. We foresee this technique to be useful in assessing other new language features, design patterns, and other programming idioms

Using Modularity Metrics to assist Move Method Refactoring of Large System

For large software systems, refactoring activities can be a challenging task, since for keeping component complexity under control the overall architecture as well as many details of each component have to be considered. Product metrics are therefore often used to quantify several parameters related to the modularity of a software system. This paper devises an approach for automatically suggesting refactoring opportunities on large software systems. We show that by assessing metrics for all components, move methods refactoring an be suggested in such a way to improve modularity of several components at once, without hindering any other. However, computing metrics for large software systems, comprising thousands of classes or more, can be a time consuming task when performed on a single CPU. For this, we propose a solution that computes metrics by resorting to GPU, hence greatly shortening computation time. Thanks to our approach precise knowledge on several properties of the system can be continuously gathered while the system evolves, hence assisting developers to quickly assess several solutions for reducing modularity issues

A heuristic-based approach to code-smell detection

Encapsulation and data hiding are central tenets of the object oriented paradigm. Deciding what data and behaviour to form into a class and where to draw the line between its public and private details can make the difference between a class that is an understandable, flexible and reusable abstraction and one which is not. This decision is a difficult one and may easily result in poor encapsulation which can then have serious implications for a number of system qualities. It is often hard to identify such encapsulation problems within large software systems until they cause a maintenance problem (which is usually too late) and attempting to perform such analysis manually can also be tedious and error prone. Two of the common encapsulation problems that can arise as a consequence of this decomposition process are data classes and god classes. Typically, these two problems occur together – data classes are lacking in functionality that has typically been sucked into an over-complicated and domineering god class. This paper describes the architecture of a tool which automatically detects data and god classes that has been developed as a plug-in for the Eclipse IDE. The technique has been evaluated in a controlled study on two large open source systems which compare the tool results to similar work by Marinescu, who employs a metrics-based approach to detecting such features. The study provides some valuable insights into the strengths and weaknesses of the two approache

Metrics for Aspect Mining Visualization

Aspect oriented programming has over the last decade become the subject of intense research within the domain of software engineering. Aspect mining, which is concerned with identification of cross cutting concerns in legacy software, is an important part of this domain. Aspect refactoring takes the identified cross cutting concerns and converts these into new software constructs called aspects. Software that have been transformed using this process becomes more modularized and easier to comprehend and maintain. The first attempts at mining for aspects were dominated by manual searching and parsing through source code using simple tools. More sophisticated techniques have since emerged including evaluation of execution traces, code clone detection, program slicing, dynamic analysis, and use of various clustering techniques. The focus of most studies has been to maximize aspect mining performance measured by various metrics including those of aspect mining precision and recall. Other metrics have been developed and used to compare the various aspect mining techniques with each other. Aspect mining automation and presentation of aspect mining results has received less attention. Automation of aspect mining and presentation of results conducive to aspect refactoring is important if this research is going to be helpful to software developers. This research showed that aspect mining can be automated. A tool was developed which performed automated aspect mining and visualization of identified cross cutting concerns. This research took a different approach to aspect mining than most aspect mining research by recognizing that many different categories of cross cutting concerns exist and by taking this into account in the mining process. Many different aspect mining techniques have been developed over time, some of which are complementary. This study was different than most aspect mining research in that multiple complementary aspect mining algorithms was used in the aspect mining and visualization process

Model-Based Run-time Verification of Software Components by Integrating OCL into Treaty

Model Driven Development is used to improve software quality and efficiency by automatically transforming abstract and formal models into software implementations. This is particularly sensible if the model’s integrity can be proven formally and is preserved during the model’s transformation. A standard to specify software model integrity is the Object Constraint Language (OCL). Another topic of research is the dynamic development of software components, enabling software system composition at component run-time. As a consequence, the system’s verification must be realized during system run-time (and not during transformation or compile time). Many established verification techniques cannot be used for run-time verification. A method to enable model-based run-time verification will be developed during this work. How OCL constraints can be transformed into executable software artifacts and how they can be used in the component-based system Treaty will be the major task of this diploma thesis.Modellgetriebene Entwicklung dient der Verbesserung von Qualität und Effizienz in der Software-Entwicklung durch Automatisierung der notwendigen Transformationen von abstrakten bzw. formalen Modellen bis zur Implementierung. Dies ist insbesondere dann sinnvoll, wenn die Integrität der ursprünglichen Modelle formal bewiesen werden kann und durch die Transformation gewährleistet wird. Ein Standard zur Spezifikation der Integrität von Softwaremodellen ist die Object Constraint Language (OCL). Eine weitere Forschungsrichtung im Software-Engineering ist die Entwicklung von dynamischen Komponenten-Modellen, die die Komposition von Softwaresystemen im laufenden Betrieb ermöglichen. Dies bedeutet, dass die Systemverifikation im laufenden Betrieb realisiert werden muss. Die meisten der etablierten Verifikationstechniken sind dazu nicht geeignet. In der Diplomarbeit soll ausgehend von diesem Stand der Technik eine Methode zur modellbasierten Verifikation zur Laufzeit entwickelt werden. Insbesondere soll untersucht werden, wie OCL-Constraints zur Laufzeit in ausführbare Software-Artefakte übersetzt und in dem komponentenbasierten System Treaty verwendet werden können

Proactive Empirical Assessment of New Language Feature Adoption via Automated Refactoring: The Case of Java 8 Default Methods

Programming languages and platforms improve over time, sometimes resulting in new language features that offer many benefits. However, despite these benefits, developers may not always be willing to adopt them in their projects for various reasons. In this paper, we describe an empirical study where we assess the adoption of a particular new language feature. Studying how developers use (or do not use) new language features is important in programming language research and engineering because it gives designers insight into the usability of the language to create meaning programs in that language. This knowledge, in turn, can drive future innovations in the area. Here, we explore Java 8 default methods, which allow interfaces to contain (instance) method implementations. Default methods can ease interface evolution, make certain ubiquitous design patterns redundant, and improve both modularity and maintainability. A focus of this work is to discover, through a scientific approach and a novel technique, situations where developers found these constructs useful and where they did not, and the reasons for each. Although several studies center around assessing new language features, to the best of our knowledge, this kind of construct has not been previously considered. Despite their benefits, we found that developers did not adopt default methods in all situations. Our study consisted of submitting pull requests introducing the language feature to 19 real-world, open source Java projects without altering original program semantics. This novel assessment technique is proactive in that the adoption was driven by an automatic refactoring approach rather than waiting for developers to discover and integrate the feature themselves. In this way, we set forth best practices and patterns of using the language feature effectively earlier rather than later and are able to possibly guide (near) future language evolution. We foresee this technique to be useful in assessing other new language features, design patterns, and other programming idioms

Javan yksikkö- ja integraatiotestaus: JVM:n käyttäytymisvetoiset testaustyökalut vastaan JUnit

This master’s thesis studied how do Behavior-Driven Development testing frameworks change the testing of Java-code compared to JUnit. The research was done as a case study. The case study was conducted in industry context at Vincit Plc, were two projects changed new unit and integration tests classes to use a new BDD-testing framework instead of JUnit. Before designing the study methods, related research and their findings were reviewed to guide the study to inspect problematic areas found in unit testing. Case study data collection methods included surveys, interviews and test code analysis. Case study provided promising results for problematic areas highlighted by earlier research. To summarize the developer practice changes, the collected data displayed an increase in unit test case granularity. Results also displayed unanimously that BDD-testing frameworks guide to write more self-documenting tests than JUnit. The structure of BDD tests highlighted better the different parts of the test. Study also revealed that the majority of participants had easier time understanding tests and removing repetition from test code. Developer perception changes in testing included the majority of study participants enjoying writing of tests more than with JUnit. The same majority also perceived that BDD-testing frameworks promote in writing higher quality test code than JUnit. Generally new test code was perceived more understandable and maintainable than tests with JUnit, although this was not unanimous. Learning curve to be effective varied between studied frameworks. Tool support of BDD-testing frameworks for testing Java Spring Framework were found ranging from adequate to good. In conclusion, this thesis results provide small scale evidence that BDD-testing frameworks could potentially ease the maintainability and readability of unit and integration tests while same time rising the enjoyment in testing.Tässä diplomityössä tutkittiin, kuinka käyttäytymisvetoiset testisovelluskehykset muuttavat Java-koodin testausta verrattuna JUnit:iin. Tutkimus suoritettiin tapaustutkimuksen menetelmin Vincit Oy:ssa. Tutkimukseen valittiin kaksi projektia, joissa uudet yksikkö- ja integraatiotestausluokat kirjoitettiin käyttäytymisvetoisilla testaussovelluskehyksillä JUnit:in sijaan. Työhön liittyvät aiempien tutkimusten havainnot ohjasivat työtä tarkastelemaan näissä löydettyjä ongelmallisia alueita. Tiedonkeruukeinoina käytettiin kyselyitä, haastatteluita sekä testikoodin analyysia. Työn tulokset osoittautuivat lupaaviksi ratkaisuksi aiemmin löydettyihin ongelmallisiin seikkoihin. Kokonaisuudessaan sovelluskehittäjien testauskäytännöissä löytyi useita muutoksia. Yksikkötestien rakenne ohjautui aiempaa hienojakoisemmaksi. Tulokset osoittivat myös yksimielisesti, että käyttäytymisvetoiset testaussovelluskehykset ohjaavat kirjoittamaan aiempaa paremmin itseänsä dokumentoivia testejä. Myös testin eri loogiset osat olivat uusien testien rakenteesta helpommin luettavissa. Suurimmalla osalla tutkimukseen osallistuneista testit olivat aiempaa helpompia ymmärtää sekä niistä oli helpompi poistaa toistoa. Suurin osa koki testien kirjoittamisen myös aiempaa nautittavampana. Valtaosa vastaajista koki uusien menetelmien ohjaavan kirjoittamaan laadukkaampaa testikoodia kuin aiemmin. Yleisesti ottaen uutta testikoodia pidettiin ymmärrettävämpänä ja ylläpidettävämpänä kuin JUnit testejä, tosin ei täysin yksimielisesti. Oppimiskäyrä uusien testauskehyksien parissa vaihteli tutkittujen kehysten välillä. Java Spring-sovelluskehyksen testaustuki vaihteli riittävästä tuesta hyvään tukeen. Kokonaisuudessaan työ tarjosi pienessä skaalassa näyttöä siitä, että käyttäytymisvetoiset testaussovelluskehykset voivat mahdollisesti helpottaa yksikkö- ja integraatiotestien ylläpidettävyyttä, luettavuutta sekä koettua nautintoa näiden parissa