Ant Colony Optimization for Requirement selection in Incremental Software development

This proposal shows that ACO systems can be applied to problems of requirements selection in software incremental development, with the idea of obtaining better results of those produced by expert judgment alone. The evaluation of the ACO systems should be done through a compared analysis with greedy and simulated annealing algorithms, performing experiments with some problems instance

The relationship between search based software engineering and predictive modeling

Search Based Software Engineering (SBSE) is an approach to software engineering in which search based optimization algorithms are used to identify optimal or near optimal solutions and to yield insight. SBSE techniques can cater for multiple, possibly competing objectives and/or constraints and applications where the potential solution space is large and complex. This paper will provide a brief overview of SBSE, explaining some of the ways in which it has already been applied to construction of predictive models. There is a mutually beneficial relationship between predictive models and SBSE. The paper sets out eleven open problem areas for Search Based Predictive Modeling and describes how predictive models also have role to play in improving SBSE

Towards Prioritizing Documentation Effort

Programmers need documentation to comprehend software, but they often lack the time to write it. Thus, programmers must prioritize their documentation effort to ensure that sections of code important to program comprehension are thoroughly explained. In this paper, we explore the possibility of automatically prioritizing documentation effort. We performed two user studies to evaluate the effectiveness of static source code attributes and textual analysis of source code towards prioritizing documentation effort. The first study used open-source API Libraries while the second study was conducted using closed-source industrial software from ABB. Our findings suggest that static source code attributes are poor predictors of documentation effort priority, whereas textual analysis of source code consistently performed well as a predictor of documentation effort priority

A review of software change impact analysis

Change impact analysis is required for constantly evolving systems to support the comprehension, implementation, and evaluation of changes. A lot of research effort has been spent on this subject over the last twenty years, and many approaches were published likewise. However, there has not been an extensive attempt made to summarize and review published approaches as a base for further research in the area. Therefore, we present the results of a comprehensive investigation of software change impact analysis, which is based on a literature review and a taxonomy for impact analysis. The contribution of this review is threefold. First, approaches proposed for impact analysis are explained regarding their motivation and methodology. They are further classified according to the criteria of the taxonomy to enable the comparison and evaluation of approaches proposed in literature. We perform an evaluation of our taxonomy regarding the coverage of its classification criteria in studied literature, which is the second contribution. Last, we address and discuss yet unsolved problems, research areas, and challenges of impact analysis, which were discovered by our review to illustrate possible directions for further research

A systematic review of quality attributes and measures for software product lines

[EN] It is widely accepted that software measures provide an appropriate mechanism for understanding, monitoring, controlling, and predicting the quality of software development projects. In software product lines (SPL), quality is even more important than in a single software product since, owing to systematic reuse, a fault or an inadequate design decision could be propagated to several products in the family. Over the last few years, a great number of quality attributes and measures for assessing the quality of SPL have been reported in literature. However, no studies summarizing the current knowledge about them exist. This paper presents a systematic literature review with the objective of identifying and interpreting all the available studies from 1996 to 2010 that present quality attributes and/or measures for SPL. These attributes and measures have been classified using a set of criteria that includes the life cycle phase in which the measures are applied; the corresponding quality characteristics; their support for specific SPL characteristics (e. g., variability, compositionality); the procedure used to validate the measures, etc. We found 165 measures related to 97 different quality attributes. The results of the review indicated that 92% of the measures evaluate attributes that are related to maintainability. In addition, 67% of the measures are used during the design phase of Domain Engineering, and 56% are applied to evaluate the product line architecture. However, only 25% of them have been empirically validated. In conclusion, the results provide a global vision of the state of the research within this area in order to help researchers in detecting weaknesses, directing research efforts, and identifying new research lines. In particular, there is a need for new measures with which to evaluate both the quality of the artifacts produced during the entire SPL life cycle and other quality characteristics. There is also a need for more validation (both theoretical and empirical) of existing measures. In addition, our results may be useful as a reference guide for practitioners to assist them in the selection or the adaptation of existing measures for evaluating their software product lines. © 2011 Springer Science+Business Media, LLC.This research has been funded by the Spanish Ministry of Science and Innovation under the MULTIPLE (Multimodeling Approach For Quality-Aware Software Product Lines) project with ref. TIN2009-13838.Montagud Gregori, S.; Abrahao Gonzales, SM.; Insfrán Pelozo, CE. (2012). A systematic review of quality attributes and measures for software product lines. Software Quality Journal. 20(3-4):425-486. https://doi.org/10.1007/s11219-011-9146-7S425486203-4Abdelmoez, W., Nassar, D. 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Mining Version Histories for Detecting Code Smells

Code smells are symptoms of poor design and implementation choices that may hinder code comprehension, and possibly increase change- and fault-proneness. While most of the detection techniques just rely on structural information, many code smells are intrinsically characterized by how code elements change over time. In this paper, we propose HIST (Historical Information for Smell deTection), an approach exploiting change history information to detect instances of five different code smells, namely Divergent Change, Shotgun Surgery, Parallel Inheritance, Blob, and Feature Envy.We evaluate HIST in two empirical studies. The first, conducted on twenty open source projects, aimed at assessing the accuracy of HIST in detecting instances of the code smells mentioned above. The results indicate that the precision of HIST ranges between 72% and 86%, and its recall ranges between 58% and 100%. Also, results of the first study indicate that HIST is able to identify code smells that cannot be identified by competitive approaches solely based on code analysis of a single system’s snapshot. Then, we conducted a second study aimed at investigating to what extent the code smells detected by HIST (and by competitive code analysis techniques) reflect developers’ perception of poor design and implementation choices. We involved twelve developers of four open source projects that recognized more than 75% of the code smell instances identified by HIST as actual design/implementation problems

Strong higher order mutation-based test data generation

This paper introduces SHOM, a mutation-based test data generation approach that combines Dynamic Symbolic Execution and Search Based Software Testing. SHOM targets strong mutation adequacy and is capable of killing both first and higher order mutants. We report the results of an empirical study using 17 programs, including production industrial code from ABB and Daimler and open source code as well as previously studied subjects. SHOM achieved higher strong mutation adequacy than two recent mutation-based test data generation approaches, killing between 8% and 38% of those mutants left unkilled by the best performing previous approach. © 2011 ACM

Restructuring source code identifiers

In software engineering, maintenance cost 60% of overall project lifecycle costs of any software product. Program comprehension is a substantial part of maintenance and evolution cost and, thus, any advancement in maintenance, evolution, and program understanding will potentially greatly reduce the total cost of ownership of any software products. Identifiers are an important source of information during program understanding and maintenance. Programmers often use identifiers to build their mental models of the software artifacts. Thus, poorly-chosen identifiers have been reported in the literature as misleading and increasing the program comprehension effort. Identifiers are composed of terms, which can be dictionary words, acronyms, contractions, or simple strings. We conjecture that the use of identical terms in different contexts may increase the risk of faults, and hence maintenance effort. We investigate our conjecture using a measure combining term entropy and term context-coverage to study whether certain terms increase the odds ratios of methods to be fault-prone. We compute term entropy and context-coverage of terms extracted from identifiers in Rhino 1.4R3 and ArgoUML 0.16. We show statistically that methods containing terms with high entropy and context-coverage are more fault-prone than others, and that the new measure is only partially correlated with size. We will build on this study, and will apply summarization technique for extracting linguistic information form methods and classes. Using this information, we will extract domain concepts from source code, and propose linguistic based refactoring

srcSlice: very efficient and scalable forward static slicing

A highly efficient lightweight forward static slicing approach is presented and evaluated. The approach does not compute the program/system dependence graph but instead dependence and control information is com-puted as needed while computing the slice on a variable. The result is a list of line numbers, dependent vari-ables, aliases, and function calls that are part of the slice for all variables (both local and global) for the entire system. The method is implemented as a tool, called srcSlice, on top of srcML, an XML representation of source code. The approach is highly scalable and can generate the slices for all variables of the Linux kernel in approximately 20min on a typical desktop. Benchmark results are compared with the CodeSurfer slicing tool from GrammaTech Inc., and the approach compares well with regard to accuracy of slices. Copyright

A Heuristic-Based Approach to Locate Concepts in Execution Traces

ABSTRACT Maintenance is the last phase of software life cycle and plays an important role in the life cycle of a system. More than 50% of the cost of the whole life cycle belongs to the maintenance phase. One of the most challenging problem of software maintenance is program comprehension. Program comprehension is a crucial part of maintenance and is a major factor in providing effective software maintenance and enabling successful evolution of a software system. A common problem in understanding software systems is that software systems often lack an adequate documentation. Most of the time, the only available source to understand the program is the source code. Therefore, developers must resort to reading the system source code, without specific tool support but code browsers, to understand the systems and perform their maintenance and evolution tasks. Concept or feature location and identification aim at helping developers to perform their maintenance and evolution tasks, by identifying abstractions (i.e., features) and the location of the implementation of these abstractions. Specifically, they aim at identifying code fragments, i.e., set of method calls in traces and the related method declarations in the source code, responsible for the implementation of domain concepts and user-observable features. The literature reports approaches built upon static and dynamic analyses; Information Retrieval (IR) and hybrid (static and dynamic) techniques. This thesis proposes a novel approach to identify cohesive and decoupled fragments in execution traces, which likely participate in implementing concepts related to some features. The approach relies on search-based optimization techniques using metaheuristic algorithm, textual analysis of the system source code using latent semantic indexing, and trace compression techniques. The proposed approach is evaluated to identify features from execution traces of two open source systems from different domains, JHotDraw and ArgoUML. Results show that the approach is stable and is generally able to locate concepts with a high precision.----------RESUMÉ La maintenance de logiciels est la dernière phase du cycle de vie des logiciels. Elle joue un rôle important dans le cycle de vie d’un logiciel car plus de 50% du coût du cycle de vie appartient à la maintenance. Un des défis importants avec la maintenance de logiciels est la compréhension. La compréhension de logiciels est une partie cruciale de la maintenance et est un facteur majeur pour une maintenance efficace ainsi que pour une évolution réussie d’un logiciel. Un problème commun à la compréhension de logiciels est souvent le manque d’une documentation adéquate. Quelques années après le déploiement, c’est possible que la documentation n’existe plus ou si elle existe, elle est surement dépassée. Les développeurs qui maintiennent le logiciel, la plupart du temps, sont différents de ceux qui l’ont développé. Par conséquent, les développeurs doivent recourir à la lecture du code source du système, avec rien d’autre que des navigateurs de code, pour comprendre le logiciel et accomplir leurs tâches de maintenance et d’évolution. L’identification et la localisation de concepts ou de fonctionnalités visent à aider les développeurs à effectuer leurs tâches de maintenance et d’évolution, en identifiant des abstractions et l’emplacement de l’implémentation de ces abstractions. Autrement dit, ils visent à identifier des fragments de code source, c’est à dire l’ensemble d’appels de méthodes dans des séquences d’instructions et les déclarations de ces méthodes dans le code source, responsables de la mise en oeuvre des concepts du domaine du logiciel et des caractéristiques observables par l’utilisateur. Dans la littérature il existe des approches d’analyse statique et dynamiquve ; Recherche Documentaire (Information Retrieval - IR) et des approches d’analyse hybride (statique et dynamique). Cette thèse propose une nouvelle approche pour identifier des fragments cohésifs et découplés dans des traces d’exécution, qui participent probablement à mettre en oeuvre les concepts liés à certaines fonctionnalités. L’approche repose sur des techniques optimisées pour la recherche en utilisant un algorithme de métaheuristiques, analyse textuelle du code source du logiciel en utilisant l’indexation sémantique latente et des techniques de compression de traces. Pour évaluer l’approche proposée, nous avons effectué une étude empirique en appliquant l’approche proposée sur deux logiciels libres, ArgoUML et JHotDraw. Les résultats ont montré que l’approche est stable, et, globalement, localise les concepts avec une précision élevée