Data collection for software defect predictionAmmAr mobark
It is one of the important stages that software companies need it, it will be after produce the program and published, to know the reactions of the users and their impressions about the program and work on developing and improving it.
The Contents
* BACKGROUND AND RELATED WORK
* EXPERIMENTAL PLANNING
-Research Goal -Research Questions -Experimental Subjects
-Experimental Material -Tasks and Methods
-Experimental Design
عمار عبد الكريم صاحب مبارك
AmmAr Abdualkareem sahib mobark
Partitioning Composite Code Changes to Facilitate Code Review (MSR2015)Sung Kim
Yida's presentation at MSR 2015!
Abstract—Developers expend significant effort on reviewing source code changes, hence the comprehensibility of code changes directly affects development productivity. Our prior study has suggested that composite code changes, which mix multiple development issues together, are typically difficult to review. Unfortunately, our manual inspection of 453 open source code changes reveals a non-trivial occurrence (up to 29%) of such composite changes.
In this paper, we propose a heuristic-based approach to automatically partition composite changes, such that each sub-change in the partition is more cohesive and self-contained. Our quantitative and qualitative evaluation results are promising in demonstrating the potential benefits of our approach for facilitating code review of composite code changes.
Cross-project Defect Prediction Using A Connectivity-based Unsupervised Class...Feng Zhang
Defect prediction on projects with limited historical data has attracted great interest from both researchers and practitioners. Cross-project defect prediction has been the main area of progress by reusing classifiers from other projects. However, existing approaches require some degree of homogeneity (e.g., a similar distribution of metric values) between the training projects and the target project. Satisfying the homogeneity requirement often requires significant effort (currently a very active area of research).
An unsupervised classifier does not require any training data, therefore the heterogeneity challenge is no longer an issue. In this paper, we examine two types of unsupervised classifiers: a) distance-based classifiers (e.g., k-means); and b) connectivity-based classifiers. While distance-based unsupervised classifiers have been previously used in the defect prediction literature with disappointing performance, connectivity-based classifiers have never been explored before in our community.
We compare the performance of unsupervised classifiers versus supervised classifiers using data from 26 projects from three publicly available datasets (i.e., AEEEM, NASA, and PROMISE). In the cross-project setting, our proposed connectivity-based classifier (via spectral clustering) ranks as one of the top classifiers among five widely-used supervised classifiers (i.e., random forest, naive Bayes, logistic regression, decision tree, and logistic model tree) and five unsupervised classifiers (i.e., k-means, partition around medoids, fuzzy C-means, neural-gas, and spectral clustering). In the within-project setting (i.e., models are built and applied on the same project), our spectral classifier ranks in the second tier, while only random forest ranks in the first tier. Hence, connectivity-based unsupervised classifiers offer a viable solution for cross and within project defect predictions.
Review Participation in Modern Code Review: An Empirical Study of the Android...The University of Adelaide
This work empirically investigates the factors influence review participation in the MCR process. Through a case study of the Android, Qt, and OpenStack open source projects, we find that the amount of review participation in the past is a significant indicator of patches that will suffer from poor review participation. Moreover, the description length of a patch and the purpose of introducing new features also share a relationship with the likelihood of receiving poor review participation.
This full article of this work is published in the Empirical Software Engineering journal. Available online at http://dx.doi.org/10.1007/s10664-016-9452-6
Mining Sociotechnical Information From Software RepositoriesMarco Aurelio Gerosa
A large amount of data is produced during collaborative software development. The analysis of such data sets a great opportunity to better understand Software Engineering from the perspective of evidence-based research. Mining software repositories studies have explored both the technical and social aspects of software development contributed to the discovery of important information about how software development evolves and how developers collaborate. Several repositories store data regarding source code production (version control systems), communication between developers and users (forums and mailing lists), and coordination of activities (issue tracker, task managers, etc.). In the open source world, such data is available in large ecosystems of software development. Platforms such as GitHub host millions of repositories, which receive contributions from millions of developers worldwide. Some project repositories register data from more than a decade of development, enabling the analysis of projects from a historical perspective. In this talk, I will discuss some of the uses and challenges of mining software repositories, focusing on some works conducted in our group, such as: identification of change dependencies, evaluation of architectural degradation from commit meta-data, core-periphery analysis of developers participation, change-proneness prediction, analysis of the impact of refactoring on code quality, and relations between quality attributes of the test and the code being tested.
Using cyclomatic complexity to measure code complexityJane Chung
To make sure your code is maintainable and programmer-friendly, you should use CCN to analyze your code complexity.
--
Brought to you by Skygear.io -- an open source development kit for mobile, web & IoT apps.
Find us on Twitter @Oursky
Findability through Traceability - A Realistic Application of Candidate Tr...Markus Borg
Conference presentation from ENASE 2012 in Wroclaw, Poland.
Abstract: Since software development is of dynamic nature, the impact analysis is an inevitable work task. Traceability is known as one factor that supports this task, and several researchers have proposed traceability recovery tools to propose trace links in an existing system. However, these semi-automatic tools have not yet proven useful in industrial applications. Based on an established automation model, we analyzed the potential value of such a tool. We based our analysis on a pilot case study of an impact analysis process in a safety-critical development context, and argue that traceability recovery should be considered an investment in ndability. Moreover, several risks involved in an increased level of impact analysis automation are already plaguing the state-
of-practice workflow. Consequently, deploying a traceability recovery tool involves a lower degree
of change than has previously been acknowledged.
A Method to Detect License Inconsistencies for Large-Scale Open Source ProjectsYuhao Wu
The reuse of free and open source software (FOSS) components is becoming more and more popular. They usually contain one or more software licenses describing the requirements and conditions which should be followed when been reused. Licenses are usually written in the header of source code files as program comments. Removing or modifying the license header by re-distributors will result in the inconsistency of license with its ancestor, and may potentially cause license infringement. But to the best of our knowledge, no research has been devoted to investigate such kind of license infringements nor license inconsistencies. In this paper, we describe and categorize different types of license inconsistencies and propose a feasible method to detect them. Then we apply this method to Debian 7.5 and present the license inconsistencies found in it. With a manual analysis, we summarized various reasons behind these license inconsistencies, some of which imply license infringement and require the attention from the developers. This analysis also exposes the difficulty to discover license infringements, highlighting the usefulness of finding and maintaining source code provenance.
Updated slides for my talk at the CHAQ meeting in Antwerp. I also added slides on some of my experiences on performing empirical studies with open source and industrial software systems.
Data collection for software defect predictionAmmAr mobark
It is one of the important stages that software companies need it, it will be after produce the program and published, to know the reactions of the users and their impressions about the program and work on developing and improving it.
The Contents
* BACKGROUND AND RELATED WORK
* EXPERIMENTAL PLANNING
-Research Goal -Research Questions -Experimental Subjects
-Experimental Material -Tasks and Methods
-Experimental Design
عمار عبد الكريم صاحب مبارك
AmmAr Abdualkareem sahib mobark
Partitioning Composite Code Changes to Facilitate Code Review (MSR2015)Sung Kim
Yida's presentation at MSR 2015!
Abstract—Developers expend significant effort on reviewing source code changes, hence the comprehensibility of code changes directly affects development productivity. Our prior study has suggested that composite code changes, which mix multiple development issues together, are typically difficult to review. Unfortunately, our manual inspection of 453 open source code changes reveals a non-trivial occurrence (up to 29%) of such composite changes.
In this paper, we propose a heuristic-based approach to automatically partition composite changes, such that each sub-change in the partition is more cohesive and self-contained. Our quantitative and qualitative evaluation results are promising in demonstrating the potential benefits of our approach for facilitating code review of composite code changes.
Cross-project Defect Prediction Using A Connectivity-based Unsupervised Class...Feng Zhang
Defect prediction on projects with limited historical data has attracted great interest from both researchers and practitioners. Cross-project defect prediction has been the main area of progress by reusing classifiers from other projects. However, existing approaches require some degree of homogeneity (e.g., a similar distribution of metric values) between the training projects and the target project. Satisfying the homogeneity requirement often requires significant effort (currently a very active area of research).
An unsupervised classifier does not require any training data, therefore the heterogeneity challenge is no longer an issue. In this paper, we examine two types of unsupervised classifiers: a) distance-based classifiers (e.g., k-means); and b) connectivity-based classifiers. While distance-based unsupervised classifiers have been previously used in the defect prediction literature with disappointing performance, connectivity-based classifiers have never been explored before in our community.
We compare the performance of unsupervised classifiers versus supervised classifiers using data from 26 projects from three publicly available datasets (i.e., AEEEM, NASA, and PROMISE). In the cross-project setting, our proposed connectivity-based classifier (via spectral clustering) ranks as one of the top classifiers among five widely-used supervised classifiers (i.e., random forest, naive Bayes, logistic regression, decision tree, and logistic model tree) and five unsupervised classifiers (i.e., k-means, partition around medoids, fuzzy C-means, neural-gas, and spectral clustering). In the within-project setting (i.e., models are built and applied on the same project), our spectral classifier ranks in the second tier, while only random forest ranks in the first tier. Hence, connectivity-based unsupervised classifiers offer a viable solution for cross and within project defect predictions.
Review Participation in Modern Code Review: An Empirical Study of the Android...The University of Adelaide
This work empirically investigates the factors influence review participation in the MCR process. Through a case study of the Android, Qt, and OpenStack open source projects, we find that the amount of review participation in the past is a significant indicator of patches that will suffer from poor review participation. Moreover, the description length of a patch and the purpose of introducing new features also share a relationship with the likelihood of receiving poor review participation.
This full article of this work is published in the Empirical Software Engineering journal. Available online at http://dx.doi.org/10.1007/s10664-016-9452-6
Mining Sociotechnical Information From Software RepositoriesMarco Aurelio Gerosa
A large amount of data is produced during collaborative software development. The analysis of such data sets a great opportunity to better understand Software Engineering from the perspective of evidence-based research. Mining software repositories studies have explored both the technical and social aspects of software development contributed to the discovery of important information about how software development evolves and how developers collaborate. Several repositories store data regarding source code production (version control systems), communication between developers and users (forums and mailing lists), and coordination of activities (issue tracker, task managers, etc.). In the open source world, such data is available in large ecosystems of software development. Platforms such as GitHub host millions of repositories, which receive contributions from millions of developers worldwide. Some project repositories register data from more than a decade of development, enabling the analysis of projects from a historical perspective. In this talk, I will discuss some of the uses and challenges of mining software repositories, focusing on some works conducted in our group, such as: identification of change dependencies, evaluation of architectural degradation from commit meta-data, core-periphery analysis of developers participation, change-proneness prediction, analysis of the impact of refactoring on code quality, and relations between quality attributes of the test and the code being tested.
Using cyclomatic complexity to measure code complexityJane Chung
To make sure your code is maintainable and programmer-friendly, you should use CCN to analyze your code complexity.
--
Brought to you by Skygear.io -- an open source development kit for mobile, web & IoT apps.
Find us on Twitter @Oursky
Findability through Traceability - A Realistic Application of Candidate Tr...Markus Borg
Conference presentation from ENASE 2012 in Wroclaw, Poland.
Abstract: Since software development is of dynamic nature, the impact analysis is an inevitable work task. Traceability is known as one factor that supports this task, and several researchers have proposed traceability recovery tools to propose trace links in an existing system. However, these semi-automatic tools have not yet proven useful in industrial applications. Based on an established automation model, we analyzed the potential value of such a tool. We based our analysis on a pilot case study of an impact analysis process in a safety-critical development context, and argue that traceability recovery should be considered an investment in ndability. Moreover, several risks involved in an increased level of impact analysis automation are already plaguing the state-
of-practice workflow. Consequently, deploying a traceability recovery tool involves a lower degree
of change than has previously been acknowledged.
A Method to Detect License Inconsistencies for Large-Scale Open Source ProjectsYuhao Wu
The reuse of free and open source software (FOSS) components is becoming more and more popular. They usually contain one or more software licenses describing the requirements and conditions which should be followed when been reused. Licenses are usually written in the header of source code files as program comments. Removing or modifying the license header by re-distributors will result in the inconsistency of license with its ancestor, and may potentially cause license infringement. But to the best of our knowledge, no research has been devoted to investigate such kind of license infringements nor license inconsistencies. In this paper, we describe and categorize different types of license inconsistencies and propose a feasible method to detect them. Then we apply this method to Debian 7.5 and present the license inconsistencies found in it. With a manual analysis, we summarized various reasons behind these license inconsistencies, some of which imply license infringement and require the attention from the developers. This analysis also exposes the difficulty to discover license infringements, highlighting the usefulness of finding and maintaining source code provenance.
Updated slides for my talk at the CHAQ meeting in Antwerp. I also added slides on some of my experiences on performing empirical studies with open source and industrial software systems.
Nowadays, we are surrounded by system of systems, autonomous systems, interconnected systems or distributed heterogeneous systems with an increase in architecture complexity.
Keeping these systems operational is a challenge as the number of potential failures which may affect their availability also increases drastically. In order to optimize availability, maintenance activities have to be designed within the design phase of the system.
Whatever the implementation choice, detection, diagnostic or prevention of failures require tests.
The goal for autonomous systems also pushes towards embedded detection and prevention capabilities and thus arguing and decision making between system engineers and maintenance engineers to share solutions in their respective activities.
In this presentation, we talk about the ability of a system designed with Capella to be tested, including in the maintenance phase. This means to interconnect several kinds of models representing different perspectives: System Design (MBSE), RAMS Analysis (Reliability, Availability, Maintainability and Safety) and Testability.
We present how a MBSE approach with Capella can be used to initiate a testability study performed with the eXpress tool from DSI International.
Creating and Analyzing Source Code Repository Models - A Model-based Approach...Markus Scheidgen
With mining software repositories (MSR), we analyze the rich data created during the whole evolution of one or more software projects. One major obstacle in MSR is the heterogeneity and complexity of source code as a data source. With model-based technology in general and reverse engineering in particular, we can use abstraction to overcome this obstacle. But, this raises a new question: can we apply existing reverse engineering frameworks that were designed to create models from a single revision of a software system to analyze all revisions of such a system at once? This paper presents a framework that uses a combination of EMF, the reverse engineering framework Modisco, a NoSQL-based model persistence framework, and OCL-like expressions to create and analyze fully resolved AST-level model representations of whole source code repositories. We evaluated the feasibility of this approach with a series of experiments on the Eclipse code-base.
Not Only Statements: The Role of Textual Analysis in Software QualityRocco Oliveto
My keynote at the 2012 Workshop on Mining Unstructured Data (co-located with the 10th Working Conference on Reverse Engineering - WCRE'12). Kingston, Ontario, Canada. October 17th, 2012.
COSMOS:
DevOps for Complex Cyber-physical Systems
Sebastiano Panichella
Zurich University of Applied Sciences (ZHAW)
Workshop on Adaptive CPSoS (WASOS) 2023
Some Pitfalls with Python and Their Possible Solutions v1.0Yann-Gaël Guéhéneuc
Python is a very popular programming language that comes with many pitfalls. This presentation describes some of these pitfalls, especially when they could trick unsuspecting object-oriented developers. It proposes solutions to these pitfalls, in particular regarding inheritance, which is easily broken because of the implementation choice of Python for explicit delegation, its method resolution order, and its use of the C3 algorithm. It discusses some advantages of using Python, especially regarding meta-classes.
Advice for writing a NSERC Discovery grant application v0.5Yann-Gaël Guéhéneuc
NSERC Discovery grant applications are judged according to four criteria: (1) Excellence of the researcher, (2) Merit of the proposal, (3) Contribution to the training of HQP, and (4) Cost of research. Each criterion has six possible merit indicators: Exceptional, Outstanding, Very strong, Strong, Moderate, and Insufficient. This presentation describes the process from a candidate's point of view and a reviewer's point of view. It discusses funding decisions, including bins and ER vs. ECR. It gives some advice, including graduating PhD students, having a story, and limiting the number of main objectives.
Ptidej Architecture, Design, and Implementation in Action v2.1Yann-Gaël Guéhéneuc
A set of process, architecture, design, and implementation patterns from a real, large program, the Ptidej Tool Suite. This set shows concrete problems and their solutions in Java. It includes: Be A Profiler, Tests as Documentation, Multi-layered Architecture, Proxy Console, Proxy Disk, Hidden Language, Internal Observer, Run-time Deprecation, String Parsimony, Object Identity, Object Address, Final Construction, StringBuffer as Positioning Element.
Examples of (bad) consequences of a lack of software quality and some solutions. This presentation presents some examples of (bad) consequences of a lack of software quality, in particular how poor software quality led to the direct deaths of 89 people. It then provides some background on software quality, especially the concept of Quality Without a Name. It then discusses many principles, their usefulness, and their positive consequences on software quality. Some of these principles are well-known in object-oriented programming while many others are taken from the book 97 Programmers. They include: abstraction, encapsulation, inheritance, types, polymorphism, SOLID, GRASP, YAGNI, KISS, DRY, Do Not Reinvent the Wheel, Law of Demeter, Beware of Assumptions, Deletable Code, coding with reason, and functional programming. They pertain to dependencies, domains, and tools.
(In details: Beautify is Simplicity, The Boy Scout Rule, You Gotta Care About the Code, The Longevity of Interim Solutions, Beware the Share, Encapsulate Behaviour not Just State, Single Responsibility Principle, WET Dilutes Performance Bottlenecks, Convenience Is Not an -ility, Code in the Language of the Domain, Comment Only What the Code Cannot Say, Distinguish Business Exception from Technical, Prefer Domain-specific Types to Primitive Types, Automate Your Coding Standards, Code Layout Matters, Before You Refactor, Improve Code by Removing It, Put the Mouse Down and Step Away from the Keyboard)
Some Pitfalls with Python and Their Possible Solutions v0.9Yann-Gaël Guéhéneuc
Python is a very popular programming language that comes with many pitfalls. This presentation describes some of these pitfalls, especially when they could trick unsuspecting object-oriented developers. It proposes solutions to these pitfalls, in particular regarding inheritance, which is easily broken because of the implementation choice of Python for explicit delegation, its method resolution order, and its use of the C3 algorithm. It discusses some advantages of using Python, especially regarding meta-classes.
An Explanation of the Unicode, the Text Encoding Standard, Its Usages and Imp...Yann-Gaël Guéhéneuc
Unicode is currently the world standard for encoding text. It supports all of the world's major writing systems. With its version 15.1 of 2023/09/12, it defines 149,813 characters and 161 scripts. This presentation starts with the, seemingly, simple example of the polar bear emoji. It then defines the key terms of any such standard. It then asks how a software system can render orthographic characters into glyphs, i.e., to render characters into (combined) glyphs. It introduces the concept of abstract characters and describes a brief history of encoding standards, from ASCII to Unicode. It shows how, by adding one level of indirection, the Unicode standard answers this question. It then presents code examples to display text written in Unicode: HarfBuzz (for shaping) and FreeType (for rendering).
An Explanation of the Halting Problem and Its ConsequencesYann-Gaël Guéhéneuc
The halting problem is an important, famous, and consequential problem in computer science. It is about writing a program that decides if another problem will stop. There is no general solution to this problem, which shows that such a problem is undecidable, with important consequences: for example, it is not possible to write tests that would exhaustively test entirely an arbitrary program. This presentation was written in collaboration with <a href="https://www.iro.umontreal.ca/~hahn/">Gena Hahn</a>.
A presentation summarising FPGAs, their history, their benefits, and showing how to program them. It provides some historical background on the development of computers, from the Difference Engine to the Intel 4004 to the AMD Ryzen Threadripper PRO 3995WX. It shows how the number of transistors increased dramatically but also how this increase led to more complexity and more bugs. It then introduces Field-programmable gate arrays (FPGA) as an alternative. It then presents how to program such FPGA using data-flow graphs. It discusses some tools (Yosys, NextPnR, and IceStorm) and illustrates them with a typical "Hello World" (i.e., blinking an LED) using Cygwin on Windows 10.
A set of brief presentations of some of the women and men who made the history of computer science and software engineering.
- 1936: Alan Turing
- 1948: Claude Elwood Shannon
- 1950: Grace Murray Hopper
- 1960: John McCarthy
- 1966: Frances E. Allen
- 1967: Ole-Johan Dahl
- 1967: Kristen Nygaard
- 1969: Charles A. R. Hoare
- 1970: Edgar F. Codd
- 1972: Dave Parnas
- 1974: Manny Lehman
- 1975: Frederick Brooks
- 1986: Edward Yourdon
- 1987: Barbara Liskov
- 1994: Erich Gamma
- 1997: Grady Booch
- 2001: Butler Lampson
A tutorial on the history, use, and caveats of Java generics. Using the simple example of an interface for sort algorithms, the tutorial presents the history of generics and describes the problems being solved by generics. It also provides definitions, and examples in Java and C++, and discusses Duck Typing. It then describes two scenarios: (1) Scenario 1: you want to enforce type safety for containers and remove the need for typecasts when using these containers and (2) Scenario 2: you want to build generic algorithms that work on several types of (possibly unrelated) things. It also summarises caveats with generics, in particular type erasure.
A tutorial on reflection, with a particular emphasis on Java, with a comparison with C++, Python, and Smalltalk. It describes different scenarios in which reflection is useful, a brief history of reflection and MOPs, a comparison with C++, Python, and Smalltalk, and some particulars about Java. The source code of the examples in Java (Eclipse project), Smalltalk (Squeak image v3.10.6), Python (Eclipse project), and C++ (Eclipse projects and Visual Studio solution) are available. (C++ Eclipse projects require Mirror.) Big thanks to Matúš Chochlík and Marcus Denker for their kind and precious help with C++ and Smalltalk.
The tutorial focuses on four common problems:
- Avoid using instanceof when code must bypass the compiler and virtual machine’s choice of the method to call.
- Create external, user-defined pieces of code loaded, used, and unloaded at run-time.
- Translate data structures or object states into a format that can be stored (file, network...).
- Monitor the execution of a program to understand its behaviour, and measure its space and time complexity.
It shows working examples of Java, Smalltalk, Python, and C++ code solving the four common problems through four scenarios:
- Scenario 1: invoke an arbitrary method on an object (see the problems with instanceof and plugins).
- Scenario 2: access the complete (including private) state of an object (see the problem with serialisation).
- Scenario 3: count the number of instances of a class created at runtime (see the problem with debugging/profiling).
- Scenario 4: patch the method of a class to change its behaviour (see the problem with patching).
It also discusses the different kinds of interconnections among objects that are available in common programming languages (linking, forking, subclassing, inter-process communication, and dynamic loading/invoking), a bit of theory about reflection, and specifically the class-loading mechanism of Java.
REST APIs are nowadays the de-facto standard for Web applications. However, as more systems and services adopt the REST architectural style, many problems arise regularly. To avoid these repetitive problems, developers should follow good practices and avoid bad practices. Thus, research on good and bad practices and how to design a simple but effective REST API are essential. Yet, to the best of our knowledge, there are only a few concrete solutions to recurring REST API practices, like “API Versioning”. There are works on defining or detecting some practices, but not on solutions to the practices. We present the most up-to-date list of REST API practices and formalize them in the form of REST API (anti)patterns. We validate our design (anti)patterns with a survey and interviews of 55 developers.
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I ...Juraj Vysvader
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I didn't get rich from it but it did have 63K downloads (powered possible tens of thousands of websites).
Providing Globus Services to Users of JASMIN for Environmental Data AnalysisGlobus
JASMIN is the UK’s high-performance data analysis platform for environmental science, operated by STFC on behalf of the UK Natural Environment Research Council (NERC). In addition to its role in hosting the CEDA Archive (NERC’s long-term repository for climate, atmospheric science & Earth observation data in the UK), JASMIN provides a collaborative platform to a community of around 2,000 scientists in the UK and beyond, providing nearly 400 environmental science projects with working space, compute resources and tools to facilitate their work. High-performance data transfer into and out of JASMIN has always been a key feature, with many scientists bringing model outputs from supercomputers elsewhere in the UK, to analyse against observational or other model data in the CEDA Archive. A growing number of JASMIN users are now realising the benefits of using the Globus service to provide reliable and efficient data movement and other tasks in this and other contexts. Further use cases involve long-distance (intercontinental) transfers to and from JASMIN, and collecting results from a mobile atmospheric radar system, pushing data to JASMIN via a lightweight Globus deployment. We provide details of how Globus fits into our current infrastructure, our experience of the recent migration to GCSv5.4, and of our interest in developing use of the wider ecosystem of Globus services for the benefit of our user community.
Code reviews are vital for ensuring good code quality. They serve as one of our last lines of defense against bugs and subpar code reaching production.
Yet, they often turn into annoying tasks riddled with frustration, hostility, unclear feedback and lack of standards. How can we improve this crucial process?
In this session we will cover:
- The Art of Effective Code Reviews
- Streamlining the Review Process
- Elevating Reviews with Automated Tools
By the end of this presentation, you'll have the knowledge on how to organize and improve your code review proces
top nidhi software solution freedownloadvrstrong314
This presentation emphasizes the importance of data security and legal compliance for Nidhi companies in India. It highlights how online Nidhi software solutions, like Vector Nidhi Software, offer advanced features tailored to these needs. Key aspects include encryption, access controls, and audit trails to ensure data security. The software complies with regulatory guidelines from the MCA and RBI and adheres to Nidhi Rules, 2014. With customizable, user-friendly interfaces and real-time features, these Nidhi software solutions enhance efficiency, support growth, and provide exceptional member services. The presentation concludes with contact information for further inquiries.
Field Employee Tracking System| MiTrack App| Best Employee Tracking Solution|...informapgpstrackings
Keep tabs on your field staff effortlessly with Informap Technology Centre LLC. Real-time tracking, task assignment, and smart features for efficient management. Request a live demo today!
For more details, visit us : https://informapuae.com/field-staff-tracking/
TROUBLESHOOTING 9 TYPES OF OUTOFMEMORYERRORTier1 app
Even though at surface level ‘java.lang.OutOfMemoryError’ appears as one single error; underlyingly there are 9 types of OutOfMemoryError. Each type of OutOfMemoryError has different causes, diagnosis approaches and solutions. This session equips you with the knowledge, tools, and techniques needed to troubleshoot and conquer OutOfMemoryError in all its forms, ensuring smoother, more efficient Java applications.
A Comprehensive Look at Generative AI in Retail App Testing.pdfkalichargn70th171
Traditional software testing methods are being challenged in retail, where customer expectations and technological advancements continually shape the landscape. Enter generative AI—a transformative subset of artificial intelligence technologies poised to revolutionize software testing.
Innovating Inference - Remote Triggering of Large Language Models on HPC Clus...Globus
Large Language Models (LLMs) are currently the center of attention in the tech world, particularly for their potential to advance research. In this presentation, we'll explore a straightforward and effective method for quickly initiating inference runs on supercomputers using the vLLM tool with Globus Compute, specifically on the Polaris system at ALCF. We'll begin by briefly discussing the popularity and applications of LLMs in various fields. Following this, we will introduce the vLLM tool, and explain how it integrates with Globus Compute to efficiently manage LLM operations on Polaris. Attendees will learn the practical aspects of setting up and remotely triggering LLMs from local machines, focusing on ease of use and efficiency. This talk is ideal for researchers and practitioners looking to leverage the power of LLMs in their work, offering a clear guide to harnessing supercomputing resources for quick and effective LLM inference.
Developing Distributed High-performance Computing Capabilities of an Open Sci...Globus
COVID-19 had an unprecedented impact on scientific collaboration. The pandemic and its broad response from the scientific community has forged new relationships among public health practitioners, mathematical modelers, and scientific computing specialists, while revealing critical gaps in exploiting advanced computing systems to support urgent decision making. Informed by our team’s work in applying high-performance computing in support of public health decision makers during the COVID-19 pandemic, we present how Globus technologies are enabling the development of an open science platform for robust epidemic analysis, with the goal of collaborative, secure, distributed, on-demand, and fast time-to-solution analyses to support public health.
How to Position Your Globus Data Portal for Success Ten Good PracticesGlobus
Science gateways allow science and engineering communities to access shared data, software, computing services, and instruments. Science gateways have gained a lot of traction in the last twenty years, as evidenced by projects such as the Science Gateways Community Institute (SGCI) and the Center of Excellence on Science Gateways (SGX3) in the US, The Australian Research Data Commons (ARDC) and its platforms in Australia, and the projects around Virtual Research Environments in Europe. A few mature frameworks have evolved with their different strengths and foci and have been taken up by a larger community such as the Globus Data Portal, Hubzero, Tapis, and Galaxy. However, even when gateways are built on successful frameworks, they continue to face the challenges of ongoing maintenance costs and how to meet the ever-expanding needs of the community they serve with enhanced features. It is not uncommon that gateways with compelling use cases are nonetheless unable to get past the prototype phase and become a full production service, or if they do, they don't survive more than a couple of years. While there is no guaranteed pathway to success, it seems likely that for any gateway there is a need for a strong community and/or solid funding streams to create and sustain its success. With over twenty years of examples to draw from, this presentation goes into detail for ten factors common to successful and enduring gateways that effectively serve as best practices for any new or developing gateway.
Custom Healthcare Software for Managing Chronic Conditions and Remote Patient...Mind IT Systems
Healthcare providers often struggle with the complexities of chronic conditions and remote patient monitoring, as each patient requires personalized care and ongoing monitoring. Off-the-shelf solutions may not meet these diverse needs, leading to inefficiencies and gaps in care. It’s here, custom healthcare software offers a tailored solution, ensuring improved care and effectiveness.
In software engineering, the right architecture is essential for robust, scalable platforms. Wix has undergone a pivotal shift from event sourcing to a CRUD-based model for its microservices. This talk will chart the course of this pivotal journey.
Event sourcing, which records state changes as immutable events, provided robust auditing and "time travel" debugging for Wix Stores' microservices. Despite its benefits, the complexity it introduced in state management slowed development. Wix responded by adopting a simpler, unified CRUD model. This talk will explore the challenges of event sourcing and the advantages of Wix's new "CRUD on steroids" approach, which streamlines API integration and domain event management while preserving data integrity and system resilience.
Participants will gain valuable insights into Wix's strategies for ensuring atomicity in database updates and event production, as well as caching, materialization, and performance optimization techniques within a distributed system.
Join us to discover how Wix has mastered the art of balancing simplicity and extensibility, and learn how the re-adoption of the modest CRUD has turbocharged their development velocity, resilience, and scalability in a high-growth environment.
Cyaniclab : Software Development Agency Portfolio.pdfCyanic lab
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1. Deep Learning Anti-patterns from Code Metrics
History
35th IEEE International Conference on Software Maintenance and Evolution
September 30th - October 4th 2019
Cleveland, OH USA
Antoine Barbez Foutse Khomh Yann-Gaël Guéhéneuc
2. Problem
Definition
Anti-patterns
"structures in the design that indicate violation of fundamental design
principles and negatively impact design quality"
"Certain structures in the code that suggest (sometimes they scream for)
the possibility of refactoring."
Suryanarayana et al. (2014)
Fowler (1999)
1/16
3. Problem
Definition
Detection
- Rely on structural metrics, e.g., LOC, Cyclomatic Complexity …
- Computed for each code component to be classified
1. Structural Anti-patterns Detection
2/16
4. Problem
Definition
Detection
1. Structural Anti-patterns Detection
- Rely on structural metrics, e.g., LOC, Cyclomatic Complexity …
- Computed for each code component to be classified
Example 1: Rule-based approaches
Lanza and Marinescu (2007)
2/16
5. Problem
Definition
Detection
- Rely on structural metrics, e.g., LOC, Cyclomatic Complexity …
- Computed for each code component to be classified
Example 1: Rule-based approaches
Example 2: Machine-learning-based approaches
1. Structural Anti-patterns Detection
2/16
6. Problem
Definition
Detection
- Anti-patterns affect how source code evolve over time when
changes are applied to the system
- Rely on an analysis of co-changes occurring between code
components
2. Historical Anti-patterns Detection
3/16
7. Problem
Definition
Detection
- Anti-patterns affect how source code evolve over time when
changes are applied to the system
- Rely on an analysis of co-changes occurring between code
components
Example: HIST (Historical Information for Smell deTection)
2. Historical Anti-patterns Detection
Palomba et al. (2013)
3/16
9. Approach Convolutional Analysis of code Metrics Evolution
Main idea:
- Analyze the history of source code metrics
- Use a Convolutional Neural Network to perform
classification
Relies on structural and historical information
Processes changes at a code-level granularity
A deep-learning-based approach
5/16
10. Approach Input: example
Let’s compute the history of the class Dog
for three metrics:
• Number of Methods Declared (NMD)
• Number of Attributes Declared (NAD)
• Lines Of Code (LOC)
With an history length of Lh = 10
6/16
21. Study Design God Class
« … one object with a lion’s share of the responsibilities, while most
other objects only hold data or execute simple processes. »
Brown et al. (1998)
9/16
22. Study Design God Class
« … one object with a lion’s share of the responsibilities, while most
other objects only hold data or execute simple processes. »
Brown et al. (1998)
Selected metrics:
• ATFD (Access To Foreign Data) • NADC (Number of Associated Data
Classes)
• LCOM5 (Lack of COhesion in
Methods)
• NMD (Number of Methods Declared)
• LOC (Lines Of Code) • WMC (Weighted Method Count)
• NAD (Number of Attributes
Declared)
9/16
23. Study Design Studied Systems
System #Class #God Class
Android Opt Telephony 192 10
Android Support 109 4
Apache Ant 694 7
Apache Lucene 155 3
Apache Tomcat 925 5
Apache Xerces 512 15
ArgoUML 1230 22
Jedit 423 5
Total 4240 71
10/16
24. Study Design Studied Systems
Evaluation
System #Class #God Class
Android Opt Telephony 192 10
Android Support 109 4
Apache Ant 694 7
Apache Lucene 155 3
Apache Tomcat 925 5
Apache Xerces 512 15
ArgoUML 1230 22
Jedit 423 5
Total 4240 71
10/16
25. Study Design Studied Systems
Evaluation
Training
&
Tuning
System #Class #God Class
Android Opt Telephony 192 10
Android Support 109 4
Apache Ant 694 7
Apache Lucene 155 3
Apache Tomcat 925 5
Apache Xerces 512 15
ArgoUML 1230 22
Jedit 423 5
Total 4240 71
10/16
26. Study 1 Definition
RQ1: To what extent historical values of source code metrics can
improve detection performances?
Approach: Monitor the performances achieved by CAME with different
length of metrics history: Lh ∈ {1, 10, 50, 100, 250, 500, 1000}
For each value of Lh:
- Perform hyper-parameters tuning
- Build and train 10 distinct CNNs
- Retrieve mean and std of precision, recall and F-measure
11/16
27. Study 1 Results
RQ1: To what extent historical values of source code metrics can
improve detection performances?
12/16
28. Study 2 Definition
RQ2: How does CAME compare to other static ML algorithms?
• Decision Tree
• Multi Layer Perceptron (MLP)
• Support Vector Machine (SVM)
13/16
29. Study 2 Definition
RQ2: How does CAME compare to other static ML algorithms?
RQ3: How does CAME compare to existing detection techniques?
• Decision Tree
• Multi Layer Perceptron (MLP)
• Support Vector Machine (SVM)
• DECOR Moha et al. (2010)
• HIST Palomba et al. (2013)
• JDeodorant Fokaefs et al. (2011)
13/16
30. Study 2 Results
Approaches Precision Recall F-measure
Decision Tree 68 % 29 % 40 %
MLP 41 % 86 % 56 %
SVM 68 % 14 % 24 %
CAME 71 % 86 % 77 %
RQ2: How does CAME compare to other static ML algorithms?
14/16
31. Study 2 Results
Approaches Precision Recall F-measure
DECOR 24 % 36 % 29 %
HIST 20 % 43 % 27 %
JDeodorant 4 % 57 % 8 %
CAME 71 % 86 % 77 %
RQ3: How does CAME compare to existing detection techniques?
15/16
32. Study 2 References
G. Suryanarayana, G. Samarthyam, T. Sharma, Refactoring for Software Design Smells:
Managing Technical Debt, Morgan Kaufmann, 2014.
W. J. Brown, R. C. Malveau, W. H. Brown, H. W. McCormick III, et T. J. Mowbray, Anti
Patterns: Refactoring Software, Architectures, and Projects in Crisis, 1st éd. John Wiley and
Sons, March 1998.
M. Fowler, Refactoring: Improving the Design of Existing Code. Boston, MA,
USA:Addison-Wesley, 1999.
F. Palomba, G. Bavota, M. D. Penta, R. Oliveto, A. D. Lucia, et D. Poshyvanyk, “Detecting
bad smells in source code using change history information.” dans ASE, 2013, pp. 268–278.
N. Moha, Y. Guéhéneuc, D. Laurence, et L. M. Anne-Franccoise, “Decor: A method for
the specification and detection of code and design smells”, IEEE Transactions on Software
Engineering (TSE), vol. 36, no. 1, pp. 20–36, 2010.
M. Fokaefs, N. Tsantalis, E. Stroulia, et A. Chatzigeorgiou, “Jdeodorant: identification and
application of extract class refactorings”, dans Software Engineering (ICSE), 2011 33rd
International Conference on. IEEE, 2011, pp. 1037–1039.
M. Lanza et R. Marinescu, Object-oriented metrics in practice: using software metrics to
characterize, evaluate, and improve the design of object-oriented systems. Springer Science
& Business Media, 2007. 16/16