Software Release Planning (SRP) is to find, for the software, a subset of the requirements with the highest value while respecting the budget. The value of a requirement however may, to various degrees, depend on selecting or ignoring other requirements. However, existing SRP models ignore either Value-Related Dependencies altogether or the strengths of those dependencies even if they consider them. This paper presents an Integer Programming model for software release planning, which considers the variances of strengths of positive and negative value-related dependencies among software requirements. To capture the imprecision associated with strengths of value-related dependencies we have made use of the algebraic structure of fuzzy graphs. We have further, contributed a scalable technique for automated identification of value-related dependencies based on user preferences for software requirements. The validity of the work is verified through simulations.
Software requirements selection aims to find an optimal subset of the requirements with the highest value while respecting the project constraints. But the value of a requirement may depend on the presence or absence of other requirements in the optimal subset. Such Value Dependencies, however, are imprecise and hard to capture. In this paper, we propose a method based on integer programming and fuzzy graphs to account for value dependencies and their imprecision in software requirements selection. The proposed method, referred to as Dependency-Aware Software Requirements Selection (DARS), is …
Considering user preferences is a determining factor in optimizing the value of a software release. This is due to the fact that user preferences for software features specify the values of those features and consequently determine the value of the release. Certain features of a software however, may encourage or discourage users to prefer (select or use) other features. As such, value of a software feature could be positively or negatively influenced by other features. Such influences are known as Value-related Feature (Requirement) Dependencies. Value-related dependencies need to be consider…
The need to update the calibration of Function Point (FP) complexity weights is discussed, whose aims are to fit specific software application, to reflect software industry trend, and to improve cost estimation. Neuro-Fuzzy is a technique that incorporates the learning ability from neural network and the ability to capture human knowledge from fuzzy logic. The empirical validation using ISBSG data repository Release 8 shows a 22% improvement in software effort estimation after calibration using Neuro-Fuzzy technique.
Software requirement selection aims to find an optimal subset of the requirements with the highest value while respecting the budget. But the value of a requirement may depend on the presence or absence of other requirements in the optimal subset. Existing requirement selection methods, however, do not consider Value Dependencies, thus increasing the risk of value loss. To address this, we have proposed Dependency-Aware Requirement Selection (DARS) method with two main components: (i) a fuzzy-based technique for identifying and modeling value dependencies, and (ii) an Integer Programming model…
The concepts of calibrating Function Points are discussed, whose aims are to fit specific software application, to reflect software industry trend, and to improve cost estimation. Neuro-Fuzzy is a technique which incorporates the learning ability from neural network and the ability to capture human knowledge from fuzzy logic. The empirical validation using ISBSG data repository Release 8 shows a 22% improvement in software effort estimation after calibration using Neuro-Fuzzy technique.
Software packages developed and distributed through package managers extensively depend on other packages. These dependencies are regularly updated, for example to add new features, resolve bugs or fix security issues. In order to take full advantage of the benefits of this type of reuse, developers should keep their dependencies up to date by relying on the latest releases. In practice, however, this is not always possible, and packages lag behind with respect to the latest version of their dependencies. This phenomenon is described as technical lag in the literature. In this paper, we perfor…
This paper presents Tartarian, a tool that supports maintenance of software with long-running, multi-release branches in distributed version control systems. When new maintenance code, such as bug fixes and code improvement, is committed into a branch, it is likely that such code can be applied or reused with some other branches. To do so, a developer may manually identify a commit and cherry pick it. Tartarian can support this activity by providing commit hashtags, which the developer uses as metadata to specify their intentions when committing the code. With these tags, Tartarian uses depend…
The increasing interest in open source software has led to the emergence of large language-specific package distributions of reusable software libraries, such as npm and RubyGems. These software packages can be subject to vulnerabilities that may expose dependent packages through explicitly declared dependencies. Using Snyk's vulnerability database, this article empirically studies vulnerabilities affecting npm and RubyGems packages. We analyse how and when these vulnerabilities are disclosed and fixed, and how their prevalence changes over time. We also analyse how vulnerable packages expose …
Large organizations have diverse product offerings to meet various business needs. To increase revenue, its common these days to offer software products as integrated product suite(s) rather than individual products. Creating and maintaining high quality software products within the integrated product suite requires rigorous product engineering methods. The sheer size of products and dependencies involved tend to raise unidentified defects that may become critical post product upgrades or after every release cycle. It is difficult to track such defects and its widespread across underlying sub-…
Software requirement selection is to find an optimal set of requirements that gives the highest value for a release of software while keeping the cost within the budget. However, value-related dependencies among software requirements may impact the value of an optimal set. Moreover, value-related dependencies can be of varying strengths. Hence, it is important to consider both the existence and the strengths of value-related dependencies during a requirement selection. The existing selection models however, either assume that software requirements are independent or they ignore strengths of re…
Nearly every popular programming language comes with one or more package managers. The software packages distributed by such package managers form large software ecosystems. These packaging ecosystems contain a large number of package releases that are updated regularly and that have many dependencies to other package releases. While packaging ecosystems are extremely useful for their respective communities of developers, they face challenges related to their scale, complexity, and rate of evolution. Typical problems are backward incompatible package updates, and the risk of (transitively) dep…
Software products have become an integral part of human lives, and therefore need to account for human values such as privacy, fairness, and equality. Ignoring human values in software development leads to biases and violations of human values: racial biases in recidivism assessment and facial recognition software are well-known examples of such issues. One of the most critical steps in software development is Software Release Planning (SRP), where decisions are made about the presence or absence of the requirements (features) in the software. Such decisions are primarily guided by the economi…
Modern software systems are often built by leveraging code written by others in the form of libraries and packages to accelerate their development. While there are many benefits to using third-party packages, software projects often become dependent on a large number of software packages. Consequently, developers are faced with the difficult challenge of maintaining their project dependencies by keeping them up-to-date and free of security vulnerabilities. However, how often are project dependencies used in production where they could pose a threat to their project's security? We conduct an em…
Recent advances in deep learning (dl) have led to the release of several dl software libraries such as pytorch, Caffe, and TensorFlow, in order to assist machine learning (ml) practitioners in developing and deploying state-of-the-art deep neural networks (DNN), but they are not able to properly cope with limitations in the dl libraries such as testing or data processing. In this paper, we present a qualitative and quantitative analysis of the most frequent dl libraries combination, the distribution of dl library dependencies across the ml workflow, and formulate a set of recommendations to (i…
Software Defect Prediction aims at predicting which software modules are the most probable to contain defects. The idea behind this approach is to save time during the development process by helping find bugs early. Defect Prediction models are based on historical data. Specifically, one can use data collected from past software distributions, or Versions, of the same target application under analysis. Defect Prediction based on past versions is called Cross Version Defect Prediction (CVDP). Traditionally, Static Code Metrics are used to predict defects. In this work, we use the Class Dependen…
While software development productivity has grown rapidly, the weight values assigned to count standard Function Point (FP) created at IBM twenty-five years ago have never been updated. This obsolescence raises critical questions about the validity of the weight values; it also creates other problems such as ambiguous classification, crisp boundary, as well as subjective and locally defined weight values. All of these challenges reveal the need to calibrate FP in order to reflect both the specific software application context and the trend of todays software development techniques more accurat…
