Submitted by Maria Medeiros (maria.dilva1@ufcg.edu.br) on 2018-05-18T12:28:38Z No. of bitstreams: 1 LARISSA NADJA BRAZ BRASILEIRO - DISSERTAÇÃO (PPGCC) 2016.pdf: 4032685 bytes, checksum: a8e913ea098aadcbf3418b4a1743ddc4 (MD5) / Made available in DSpace on 2018-05-18T12:28:38Z (GMT). No. of bitstreams: 1 LARISSA NADJA BRAZ BRASILEIRO - DISSERTAÇÃO (PPGCC) 2016.pdf: 4032685 bytes, checksum: a8e913ea098aadcbf3418b4a1743ddc4 (MD5) Previous issue date: 2016 / Capes / Sistemas configuráveis tipicamente usam #ifdefs para denotar variabilidade. Gerar e compilar todas as configurações de um sistema pode consumir tempo. Uma alternativa consiste em usar analisadores sintáticos conscientes de variabilidade, como TypeChef. Porém, eles podem não escalar. Na prática, desenvolvedores podem utilizar estratégias de amostragem (sampling) para compilar apenas um subconjunto das configurações. Este trabalho propõe uma técnica para compilar sistemas configuráveis com #ifdefs baseada no impacto da mudança através da análise apenas das configurações impactadas por uma mudança de código. A técnica foi implementada em uma ferramenta chamada CHECKCONFIGMX, que reporta os novos erros de compilação introduzidos pela transformação. Um estudo empírico foi realizado para avaliar 3,913 transformações aplicadas aos 14 maiores arquivos dos sistemas configuráveis BusyBox, Apache HTTPD, e Expat. CHECKCONFIGMX encontrou 595 erros de compilação de 20 tipos introduzidos por 41 desenvolvedores em 214 commits (5.46% das transformações analisadas). No estudo realizado, a ferramenta reduziu ao menos 50% (uma média de 99%) o número de configurações compiladas em comparação à abordagem exaustiva, sem considerar feature models. CHECKCONFIGMX pode ajudar os desenvolvedores a reduzir o esforço de avaliar transformações de granularidade fina aplicadas a sistemas configuráveis com #ifdefs. / Configurable systems typically use #ifdefs to denote variability. Generating and compiling all configurations may be time-consuming. An alternative consists of using variability aware parsers, such as TypeChef. However, they may not scale. In practice, developers can use sampling strategies to compile only a subset of the configurations. We propose a change-centric approach to compile configurable systems with #ifdefs by analyzing only configurations impacted by a code change. We implement it in a tool called CHECKCONFIGMX, which reports the new compilation errors introduced by the transformation. We perform an empirical study to evaluate 3,913 transformations applied to the 14 largest files of BusyBox, Apache HTTPD, and Expat configurable systems. CHECKCONFIGMX finds 595 compilation errors of 20 types introduced by 41 developers in 214 commits (5.46% of the analyzed transformations). In our study, it reduces at least 50% (an average of 99%) the number of compiled configurations by comparing with the exhaustive approach without considering a feature model. CHECKCONFIGMX may help developers to reduce compilation effort to evaluate fine-grained transformations applied to configurable systems with #ifdefs.

Submitted by Fabio Sobreira Campos da Costa (fabio.sobreira@ufpe.br) on 2016-03-15T15:21:11Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) TESE_SABRINA.pdf: 1152470 bytes, checksum: a89ffc94cb3ee813cf52ca2c043171ba (MD5) / Made available in DSpace on 2016-03-15T15:21:11Z (GMT). No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) TESE_SABRINA.pdf: 1152470 bytes, checksum: a89ffc94cb3ee813cf52ca2c043171ba (MD5) Previous issue date: 2015-03-31 / Software Product Lines (SPLs) allow engineers to systematically build families of software products, defined by a unique combination of features—increments in functionality, improving both the efficiency of the software development process and the quality of the software developed. However, testing these kinds of systems is challenging, as it may require running each test against a combinatorial number of products. We call this problem the High Dimensionality Problem. Another obstacle to product line testing is the absence of Feature Models (FMs), making it difficult to discover the real causes for test failures. We call this problem the Lack of Feature Model Problem. The High Dimensionality Problem is associated to the large space of possible configurations that an SPL can reach. If an SPL has n boolean features, for example, there are 2n possible feature combinations. Therefore, systematically testing this kind of system may require running each test against all those combinations, in the worst case. The Lack of Feature Model Problem is related to the absence of feature models. The FM enables accurate categorization of failing tests as failures of programs or the tests themselves, not as failures due to inconsistent combinations of features. For this reason, the lack of FM presents a huge challenge to discover the true causes for test failures. Aiming to solve these problems, we propose two lightweight techniques: SPLat and SPLif. SPLat is a new approach to dynamically prune irrelevant configurations: the configurations to run for a test can be determined during test execution by monitoring accesses to configuration variables. As a result, SPLat reduces the number of configurations. Consequently, SPLat is lightweight compared to prior works that used static analysis and heavyweight dynamic execution. SPLif is a technique for testing SPLs that does not require a priori availability of feature models. Our insight is to use a profile of passing and failing test runs to quickly identify test failures that are indicative of a problem (in test or code) as opposed to a manifestation of execution against an inconsistent combination of features. Experimental results show that SPLat effectively identifies relevant configurations with a low overhead. We also apply SPLat on two large configurable systems (Groupon and GCC), and it scaled without much engineering effort. Experimental results demonstrate that SPLif is useful and effective to quickly find tests that fail on consistent configurations, regardless of how complete the FMs are. Furthermore, we evaluated SPLif on one large extensively tested configurable system, GCC, where it helped to reveal 5 new bugs, 3 of which have been fixed after our bug reports. / Software Product Lines (SPLs) allow engineers to systematically build families of software products, defined by a unique combination of features—increments in functionality, improving both the efficiency of the software development process and the quality of the software developed. However, testing these kinds of systems is challenging, as it may require running each test against a combinatorial number of products. We call this problem the High Dimensionality Problem. Another obstacle to product line testing is the absence of Feature Models (FMs), making it difficult to discover the real causes for test failures. We call this problem the Lack of Feature Model Problem. The High Dimensionality Problem is associated to the large space of possible configurations that an SPL can reach. If an SPL has n boolean features, for example, there are 2n possible feature combinations. Therefore, systematically testing this kind of system may require running each test against all those combinations, in the worst case. The Lack of Feature Model Problem is related to the absence of feature models. The FM enables accurate categorization of failing tests as failures of programs or the tests themselves, not as failures due to inconsistent combinations of features. For this reason, the lack of FM presents a huge challenge to discover the true causes for test failures. Aiming to solve these problems, we propose two lightweight techniques: SPLat and SPLif. SPLat is a new approach to dynamically prune irrelevant configurations: the configurations to run for a test can be determined during test execution by monitoring accesses to configuration variables. As a result, SPLat reduces the number of configurations. Consequently, SPLat is lightweight compared to prior works that used static analysis and heavyweight dynamic execution. SPLif is a technique for testing SPLs that does not require a priori availability of feature models. Our insight is to use a profile of passing and failing test runs to quickly identify test failures that are indicative of a problem (in test or code) as opposed to a manifestation of execution against an inconsistent combination of features. Experimental results show that SPLat effectively identifies relevant configurations with a low overhead. We also apply SPLat on two large configurable systems (Groupon and GCC), and it scaled without much engineering effort. Experimental results demonstrate that SPLif is useful and effective to quickly find tests that fail on consistent configurations, regardless of how complete the FMs are. Furthermore, we evaluated SPLif on one large extensively tested configurable system, GCC, where it helped to reveal 5 new bugs, 3 of which have been fixed after our bug reports.